HK1246468B - Intelligent surfacing of reminders - Google Patents

Description

Smart emergence of reminders

Technical Field

Background Art

Calendar and scheduling applications and services typically organize and display a user's activities, tasks, work, appointments, meetings, and other types of events. They may also provide event reminders or notifications that are presented to the user based on the date and time of the event. Existing services may be limited to presenting or triggering reminders at the time of the event, a default time period before the event, or a user-specified time period, which may or may not provide sufficient advance notice to the user. Some methods of triggering reminders are based on geo-fencing and/or detecting communications with individuals associated with the reminder.

Summary of the Invention

This summary is provided to introduce a selection of principles in a simplified form, which are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

In various embodiments, systems, methods, and computer storage media are provided for triggering event reminders or notifications to users at relevant times based on contextual information. Reminders can be triggered based on information such as calendar information, user profile information, and/or one or more conditions such as frequently visited locations, frequently traveled routes, travel times, meeting participants, proximity to another individual, etc. In one embodiment, another individual associated with the reminder is identified, and a future time is predicted when the user is expected to be within the proximity of the other individual. The time at which the reminder is triggered can then be based on an amount of time in advance of when the user is expected to be within the proximity of the other individual.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is described in detail below with reference to the accompanying drawings, in which:

FIG1 depicts an exemplary operating environment suitable for use with embodiments of the present invention;

FIG2 depicts a flow chart of an exemplary method for triggering presentation of reminders suitable for use with embodiments of the present invention;

FIG3 depicts a flow chart of an exemplary method for triggering presentation of reminders suitable for use with embodiments of the present invention;

FIG4 depicts an exemplary system for triggering presentation of reminders suitable for use with embodiments of the present invention; and

FIG5 depicts an exemplary system for triggering the presentation of reminders suitable for use with embodiments of the present invention.

DETAILED DESCRIPTION

Triggering an event reminder or notification in a user device before an associated event or task can provide the user with sufficient time to travel and/or make any preparations that may be required for the event or task. Contextual information can be used to determine how far in advance to surface a notification or trigger a notification. Contextual information about the event can be determined from user profile information (such as frequently visited locations, frequently traveled routes, locations associated with the event, individuals associated with the user, locations associated with the user, the user's current location, etc.). Contextual information about the event can also be determined from other information in the user's calendar and/or information from another user's calendar. In one embodiment, data or parameters associated with the reminder are combined with the contextual information to determine a relevant time for causing the reminder to surface. The relevant time can include a time long enough before the event that allows the user to travel from the current location to the event and arrive before (or earlier than) the time at which the event is scheduled to occur. The relevant time can include a time before a predicted aggregation of circumstances that enable the event (such as for an event that is not bound to a specific time) to occur.

As used herein, the term "event" includes sudden events, accidental events, planned important events, tasks to be performed, information to be remembered, and the like. Thus, by way of example and not limitation, events may include meetings, missions, tasks, special important events, and generally anything that a user wants or needs to be reminded of. Some events may be associated with a specific location, time, and/or individual, such as a work meeting with colleagues in a specific conference room at a specific date and time. However, events are not necessarily associated with a specific location, time, or individual. For example, the task of "buying milk on the way home from work today" does not specify a specific grocery store and is not associated with an individual (other than the user). The task of "borrowing a gardening book from the library on 12th Street" does not specify a specific date, time, or individual. The task of "paying Fred the five dollars I owe him" does not specify a specific date or location. Some embodiments determine the relevant time for triggering an event notification regardless of whether the event is associated with a specific location, date, or time.

According to some embodiments of the present invention, event reminder data is analyzed to identify individuals (other than the user) associated with the reminder/event. Event reminder data may include parameters for configuring reminders, such as location, date, time, subject, mentions of other users or individuals, and the like. Another user or individual can be identified based on descriptive terms or names within the reminder data combined with contextual information about the user. Based on the contextual information associated with the user, a future time is determined when the user is predicted or expected to be within the proximity of the individual associated with the reminder. The contextual information may include information such as calendar information, scheduled events, other reminders, known routes the user has historically traveled, and known locations the user has historically visited. In one embodiment, based on specific events within the user's calendar data, a future time is determined when the user is predicted or expected to be within the proximity of the individual associated with the reminder. For example, when the user's calendar data includes a second event associated with another individual, the scheduled time for the second event is a future time when the user is expected to be within the proximity of the individual. For example, the second event may be a planned dinner with the other individual. Alternatively, the future time at which a user is expected to be within the proximity of an individual can be based on information from the user's calendar information (and/or other contextual information) and the calendar information (and/or contextual information) of another individual. In one embodiment, the calendar and/or contextual data of another individual can be used to determine that the individual will be at the same location (or a nearby location) as the user's future location, which is determined from the user's calendar and/or contextual data. For the purpose of coordinating events with certain other users, the user can be provided with the option of allowing other parts of their calendar information and/or its contextual information to be accessed. As used herein, the term "proximity range" refers to the amount of distance and/or travel time that falls within a threshold, wherein the threshold is specified as the amount of acceptable distance or travel time that the user needs to travel in order to complete a task, event, etc. For example, if a user needs to perform a task related to another individual (e.g., give Joe twenty dollars), the proximity range threshold is a five-minute travel time, and when the user is at a specific location, it is predicted that the user and the other individual will be within a five-minute walk (or a five-minute drive) of each other, then the following reminder or suggestion can be presented to the user: the task can be performed at the specific location.

In one embodiment, a trigger time (i.e., the lead time for triggering the reminder) is determined, and the reminder is triggered based on the determined trigger time. The trigger time can be determined based on the amount of travel time required to reach the location of the second event. For example, a starting location of the user can be predicted, and a predicted route from the starting location to the location of the second event can be determined. The travel time can be determined based on factors such as distance along the route, speed limits, traffic patterns, weather conditions, etc. In one embodiment, the trigger time can be determined at least in part based on geo-fencing, for example, the reminder can be triggered when the user leaves or arrives at a specific location (such as a workplace, home, store, etc.), or the reminder can be triggered some determined amount of time before or after the user leaves or arrives at the specific location. The determined amount of time can be determined based on the travel time and/or any other factors described above.

In one embodiment, reminders are presented in a specific location or page within a user interface. For example, the user interface may have a "Home" page or a "Need to Know" section, or some other designated portion of the user interface where the user can view any pending reminders that have appeared. Thus, when a reminder is triggered, it can be placed in a designated portion of the user interface, where the user can view the reminder if they choose. Additionally, the reminder can persist in that location for a period of time, so that if the user later returns to the designated portion of the user interface, the reminder is still presented. In one embodiment, the user is not notified that the reminder has been placed in the designated portion of the user interface, but must instead view that portion of the interface to determine whether the reminder has been placed there. In another embodiment, the user may receive notification that the reminder has been placed in the designated portion of the user interface, such as an audible tone, vibration, or pop-up message. In some embodiments, instead of placing the reminder in the designated portion of the user interface, the reminder is presented to the user directly while the user is viewing other portions of the user interface, or in addition to being placed in the designated portion of the user interface. For example, the reminder may be presented as a pop-up message, a dialog box, or other type of unsolicited message. Reminders can be presented regardless of whether the user is actively viewing the device and can utilize an audible tone or vibration to attract the user's attention to view the reminder.

In a first aspect, a method for triggering presentation of a reminder is provided. The method includes accessing a reminder describing an event associated with a user of a user device. Identifying an individual, other than the user, associated with the first event. Predicting a future time when the user will be within proximity of the other individual. Determining a time to trigger the reminder for presentation to the user such that the time to trigger the reminder occurs before the future time when the user is predicted to be within proximity of the individual. Determining that the time to trigger the reminder has occurred, and based on this determination, triggering the reminder for presentation to the user.

In a second aspect, a system for triggering the presentation of a calendar event reminder is provided. The system includes one or more computing devices and a data storage device configured to store calendar information associated with a user of a user device. The system also includes a data collection component configured to collect contextual information associated with the user, and a data storage configured to store the contextual information. The system also includes an inference engine configured to access an event reminder that describes an event associated with a user of the user device, identifies an individual other than the user associated with the event, and determines a future time when the user is predicted to be within a predetermined proximity of the individual, determines a time to trigger the reminder to be presented to the user, such that the triggering time will occur in a time period prior to the future time when the user is predicted to be within the predetermined proximity of the individual. The system also includes a reminder appearance component configured to determine that the time to trigger the reminder has occurred, and trigger the reminder to be presented to the user.

In a third aspect, a method for triggering the presentation of a calendar event reminder is provided. An event reminder is accessed, the time reminder describing an event associated with a user of a user device. An individual associated with the event, other than the user, is identified. A future time is predicted when the user will be within a predetermined proximity of the individual, the individual being located at a point along a route predicted to be traveled by the user. A time is determined to trigger the reminder for presentation to the user, such that the time to trigger the reminder occurs within a time period prior to the predicted future time when the user will be within the predetermined proximity of the individual. It is determined that the time to trigger the reminder has occurred, and the reminder is triggered for presentation to the user.

Referring first to FIG. 2 , in particular, a flowchart depicts an exemplary method for triggering presentation of a reminder suitable for use with embodiments of the present invention, and generally referred to as method 200. Method 200 is merely an example of one suitable method and is not intended to suggest any limitation as to the scope of use or functionality of the present invention. Method 200 should also not be interpreted as having any dependency or requirement relating to any single component or combination of components illustrated herein.

At step 210, reminders describing events associated with a user of a user device are accessed. The user device may be a user device similar to computing device 100 described below with respect to FIG. 1 . Reminders may include information about events, such as tasks, casual events, gatherings, special occasions, meetings, locations, dates, times, one or more other individuals, and the like. Reminders may be stored in memory on the user device as part of a calendar application, a schedule application, or other type of application that stores and utilizes reminders. Alternatively, reminders may be stored remotely, such as on a network server that communicates with the user device and manages reminders for multiple user devices. Examples of reminders that may be presented to the user may include "Buy milk at Acme Grocery Store after get off work tonight," "Meet Sam and Tom in Conference Room 15 at 2 PM on June 4, 2015," "Pay back the twenty dollars I owe Joe," and the like. In one embodiment, reminders need not be associated with a specific individual, a specific location, or a specific date/time.

In step 212, individuals associated with the event (other than the user) are identified. In the example reminder above, Sam and Tom are individuals associated with the meeting reminder, and Joe is an individual associated with the reminder to pay back the money. One difference between these two reminders is that the meeting reminder is associated with a location and date/time, while the reminder to pay back the money is not associated with a location or time. Individuals can be identified in various ways. Based on identifying terms or names (e.g., "Joe," "Tom Smith," "the kids," etc.), individuals can be identified from a user profile associated with the user, which stores contextual information about the user. Examples of contextual information that may be helpful in identifying individuals include identification of family members, friends, coworkers, and generally anyone associated with the user. It may also include an indication of the type of relationship or association the user has with the individual. In one embodiment, a user can designate specific individuals as members of an "inner circle" associated with the user. Members of the inner circle can be assigned various priority levels, which can be used when surfacing reminders. For example, a user's spouse may be designated as a member of the inner circle, while the user's real estate agent may not be. In this case, when both a reminder associated with a spouse and a reminder associated with a real estate agent appear, because the spouse is designated in the user's Inner Circle, the reminder associated with the spouse may be given more prominence, prominence, or other emphasis based on the spouse's priority level relative to the real estate agent. Similarly, both a spouse and a friend may be included in the user's Inner Circle, but the user may designate the spouse as having a higher priority level than the friend. Thus, based on the priority levels assigned to the spouse and the friend, the reminder associated with the spouse will be given emphasis relative to the reminder associated with the friend, even though both are in the Inner Circle. Other examples of individuals that a user may wish to prioritize include children, other family members, work supervisors, and the like.

In step 214, a future time is determined at which the user is predicted to be within the proximity of the individual associated with the reminder. The future time can be determined based on contextual information associated with the user. The contextual information can include information such as calendar information, scheduled events, other reminders, known routes that the user has historically traveled and/or the number of times the user has traveled, known locations that the user has historically visited and/or the number of times the user has visited, etc. Similarly, known information about another individual can be used to predict the location of the other individual. This can include: (1) information that is known in the user's contextual information and does not require access to the other individual's personal information (e.g., calendar invitations that include the individual, the individual's home location, the individual's work location, etc.); and (2) information that requires access to the other individual's personal information (e.g., calendar information, reminders, current GPS from the individual's mobile device, etc.). The other individual's personal information can be accessed based on permission granted by the other individual. In one embodiment, permission can be granted based on a designation that one or both individuals are within the other individual's inner circle. The proximity of the user to the other individual can be determined based on the distance between the user and the other individual (e.g., straight-line distance or distance along a route such as a street, sidewalk, etc.). Distance need not be determined solely based on typical units of measurement (e.g., miles, feet, etc.), but may also be determined based on factors such as whether the user and the individual are in the same building, within a certain number of buildings of each other, etc. Proximity may also be based on the amount of travel time between the user and the individual, such as the amount of walking time, driving time, or other means of transportation.

In one embodiment, a future time is determined based on the user's calendar information. A second event associated with the same individual and scheduled for a future time is identified. Thus, the scheduled time for the second event is identified as a future time when the user is predicted to be within the vicinity of the individual. For example, suppose the reminder is "Pay back the twenty dollars I owe Joe." When accessing the user's calendar information, another event—"Meet Joe for squash next Saturday at 3:00 PM"—may be identified. Next Saturday at 3:00 PM may thus be identified as a future time when the user is predicted to be within Joe's vicinity, making it an appropriate time to pay the money back. The second event may be different from the first. For example, in the above example, "Meet Joe for squash next Saturday at 3:00 PM" and "Pay back the twenty dollars I owe Joe" may be stored as separate, unrelated events in the user's calendar/reminder information. Thus, these two events are independent of each other, meaning that they can occur without the other and do not specifically need to occur at the same time or location.

In the above example, the reminder "Pay back the twenty dollars I owe Joe" is not associated with a specific place or time, e.g., it is not scheduled for a specific place or time. However, in one embodiment, even if a reminder is associated with a specific time and/or location, different times and/or locations can be identified as opportunities to perform the task/event and suggested to the user. For example, suppose the reminder is "Pay back the twenty dollars I owe Joe at church next Sunday." Based on the user's calendar information, a second event, "Meet Joe for squash next Saturday at 3:00 PM," may be identified as an earlier opportunity to pay Joe back, and the reminder may surface in advance of the squash game.

At step 216, a relevant time is determined for triggering a reminder for presentation to the user. The relevant time may be long enough before the second event for the user to take any necessary actions to complete any tasks or preparations associated with the reminder. The time to trigger the reminder may be a specific time or may be based on a geofence (such as when the user leaves or arrives at a specific location). In one embodiment, a future location of the user is predicted to be within the proximity of an individual at the predicted future time. A starting location of the user is identified, and a route that the user will travel from the starting location to the future location is predicted. The amount of travel time required to follow the predicted route from the starting location to the future location can be determined, and the time to trigger the reminder can be determined based at least in part on the required travel time. For example, if the user is at home next Saturday before meeting Joe, a relevant reminder may be triggered before Joe leaves home so that the user is reminded to bring twenty dollars to the racquetball game. The user's location before the scheduled event can be determined based on information collected from the user's mobile phone, global positioning system (GPS), or other indication of the user's presence at a specific location. The user's location can also be predicted based on historical travel or visit patterns stored as part of the user's contextual information. For example, if it is determined from contextual information that the user always (or typically) visits a particular coffee shop every Saturday at 2:00 p.m., the coffee shop may be predicted as the user's current location at 2:00 p.m. on that Saturday. A relevant time to trigger a reminder may be early enough for the user to be able to visit a local ATM (or go home) to get cash (if needed) and still arrive on time for the racquetball game.

In one embodiment, the starting location is predicted or identified as the user's current location. In another embodiment, the starting location is identified based on the user's predicted future location, as described above. For example, the user's user profile data can be accessed to identify the user's historical travel patterns and identify one or more locations that the user frequently visits. In one embodiment, one or more locations can be identified where the user has historically visited these locations at the same time on the same day of the week, or where the user has historically visited these locations before visiting a location where the user is predicted to be within the proximity of the individual. Based on the probability or confidence score associated with each historically visited location, the most likely starting location can be determined from the historically visited locations. Thus, the user's predicted future location before the time when the user will be within the proximity of the individual is identified as the user's starting location.

In one embodiment, predicting a route that a user will travel from a starting location to a future location includes accessing user profile data associated with the user and identifying one or more routes that the user has historically traveled from the starting location to the future location. Based on a probability or confidence score associated with each historical travel route, a most likely route can be determined from the user's historically traveled routes. Thus, the most likely route is identified as the predicted route that the user will travel from the starting location to the future location.

In step 218, a determination is made as to whether a time has occurred to trigger the reminder, for example, based on a correspondence between the current time and a specific predetermined time, or based on a correspondence between the user's current location and a geofence. For example, based on the user's location at a coffee shop, the trigger time might be 2:30 p.m., allowing for travel time to the nearest ATM and from the ATM to the racquetball courts. In step 220, once the trigger time has occurred, the reminder is triggered for presentation to the user. In one embodiment, once the reminder is triggered, it is configured to persist for a period of time prior to the time when the user will be within the proximity of the individual. In one embodiment, when a user has multiple user devices, the reminder can surface on any or all of the user devices. If the user has both a smartphone and a tablet device, the reminder may surface on both. In one embodiment, the reminder can surface on the device currently in use. Alternatively, the reminder can surface on a specific device based on one or more user preferences associated with the reminder or with the user device.

3 , a flowchart depicts an exemplary method for triggering the presentation of reminders suitable for use with embodiments of the present invention, and is generally referred to as method 300. Method 300 is merely an example of one suitable method and is not intended to suggest any limitation as to the scope of use or functionality of the present invention. Method 300 should also not be interpreted as having any dependency or requirement relating to any single component or combination of components illustrated herein.

In step 310, a reminder is accessed that describes an event associated with the user of the user device. The user device may be a user device similar to the computing device 100 described below with respect to FIG. 1 . A reminder describes an event that is associated in some way with the user of the user device and is configured to be presented on the user device at a certain point in time to remind the user of the event. The reminder may include information about the event, such as a task, a casual event, a party, a meeting, a special occasion, a location, a date, a time, one or more other individuals associated with the reminder, and the like. In some embodiments, the reminder need not be associated with an individual, a location, or a specific date/time. The reminder may be stored on the user device, or may be stored remotely, such as in the cloud or on a network server that communicates with the user device and manages reminders for multiple user devices. Examples of reminders presented to the user may include "Deliver the quarterly report to Paul," "Buy a jacket at Acme Clothing Store," "Pay back the twenty dollars I owe Joe," and the like.

In step 312, individuals associated with the event (other than the user) are identified. In the example reminder above, Paul is the individual associated with delivering the quarterly report, and Joe is the individual associated with paying the money back. There are no other individuals besides the user associated with purchasing the jacket. In some embodiments, the reminder need not be associated with a specific individual, location, or date/time. Individuals can be identified in various ways. Based on an identifying term or name (e.g., "Paul," "wife," "children," etc.), individuals can be identified from a user profile associated with the user, which stores contextual information about the user. Examples of contextual information that may be helpful in identifying individuals include a list of family members, friends, co-workers, anyone generally associated with the user, and an indication of their relationship or relevance to the user.

At step 314, a future time is determined at which the user is predicted to be within a predetermined proximity of an individual at a point along the predicted route that the user will travel. The proximity of an individual can be determined based on the distance between the point along the predicted route and the individual (such as a straight-line distance or a distance along a route such as a street, sidewalk, etc.). The proximity can also be based on the amount of travel time between the point along the predicted route and the individual, such as the amount of walking time, driving time, or other means of transportation time. In one embodiment, the proximity is based on the amount of distance and/or travel time required to deviate from the predicted route in order to meet up with the other individual.

The future time can be determined based on contextual information associated with the user. The contextual information can include information such as calendar information, scheduled events, other reminders, known routes that the user has historically traveled and/or the user's travel times, known locations that the user has historically visited and/or the number of times the user has visited, the user's home location, the user's current location, etc. Similarly, the location of another individual can be predicted using known information about the other individual. This can include: (1) information that is known in the user's contextual information and does not require access to the other individual's personal information (e.g., a calendar invitation that includes the individual, the individual's home location, the individual's work location, etc.); and (2) information that requires access to the other individual's personal information (e.g., calendar information, reminders, current GPS from the individual's mobile device, etc.). The other individual's personal information can be accessed based on the permission granted by the other individual.

As an example, assume the reminder is "Pay me back the twenty dollars I owe Joe." When accessing the user's calendar information, the event "Meet with the real estate agent at Acme Real Estate" scheduled for next Saturday at 3:30 PM may be identified. The route the user will take to Acme Real Estate for the scheduled event may be predicted based on at least one or more of the user's calendar information, the user's user profile, the user's historical travel patterns, a starting location, etc. In one embodiment, predicting the route the user will take includes identifying the user's current route and predicting the remainder of the current route as the route.

Joe's location at the time the user will travel the route to Acme Properties can also be predicted. For example, Joe's calendar information can be accessed, and the event "Workout at Acme Gym next Saturday at 3:00 PM" can be identified. In some embodiments, Joe's location at the time the user will travel the route to Acme Properties is determined from Joe's user profile information and/or Joe's historical travel patterns. It can then be determined that Acme Gym is within a predetermined proximity of a point along the predicted route the user will take to Acme Properties. A time can be predicted for the user to arrive at that point along the route, and it can be determined that Joe will be at Acme Gym at that time. Thus, the predicted time is identified as a predicted future time when the user will be within the predetermined proximity of an individual.

In some embodiments, determining a predicted future time at which a user will be within proximity of another individual includes selecting a route and then suggesting the route to the user. For example, a starting location of the user may be identified, and a destination location to which the user is predicted to travel at a future time may be identified. In one embodiment, the user's destination location is independent of the location at which the other individual is predicted to be located, for example, the two locations are not the same location. One or more potential routes from the starting location to the destination location may be identified based on information such as mapping data, geospatial data, and the like. A route may be selected from the one or more potential routes based on determining the location at which the individual is predicted to be located at the future time, and determining that a point along one of the potential routes is within proximity of the location at which the individual is predicted to be located. The route may be suggested to the user, and the future time at which the user is predicted to be within proximity of the individual may be determined by identifying the time at which the user is predicted to arrive at a point along the suggested route.

At step 316, a relevant time is determined for triggering the reminder for presentation to the user. The relevant time may be long enough before the moment the user is within the proximity of the individual to allow the user to take any necessary actions and/or prepare to complete any tasks associated with the reminder. The time to trigger the reminder can be a specific time or can be based on a geofence (such as when the user leaves or arrives at a specific location). Additionally, since the user may not know where Joe will be on Saturday, the reminder may be modified to indicate that Joe will be at Acme Gym when the user is traveling the predicted route. The reminder may also be modified to suggest that the user deviate from the predicted route, stop at the gym, and pay Joe back. For example, if the user will be home next Saturday before traveling to Acme Real Estate, a relevant reminder may be triggered before the user leaves home and presented with a message such as: "Pay Joe the twenty dollars I owe him at Acme Gym while traveling to Acme Real Estate." This reminder thus informs the user of a convenient opportunity to pay Joe back and also serves to remind the user to have the twenty dollars with them. The time the reminder is triggered may vary depending on the user's location. For example, the Acme estate might be a 15-minute drive from the user's home, but if the user is visiting the park with friends, it might be a 45-minute drive from the park to the Acme estate. Thus, based on the determined travel time associated with the route from the particular location to the Acme estate, the reminder would need to be triggered earlier at the park than at the user's home. The user's location prior to the scheduled event can be determined based on information gathered from the user's mobile phone, GPS, cell tower location, WiFi connection, and/or other indications that the user is at a particular location. The user's location can also be predicted based on historical travel or visit patterns stored as part of the user's contextual information. For example, if it is determined from contextual information that the user always (or typically) visits a particular coffee shop every Saturday at 2:30 PM, the coffee shop can be predicted as the user's location based on this visit pattern. A relevant time to trigger the reminder might be early enough for the user to be able to visit a local ATM (or return home) to obtain cash (if needed) and still have time to stop at the Acme gym on the way to the Acme estate.

At step 318, a determination is made as to whether a time has occurred to trigger the reminder (e.g., the current time corresponds to a specific predetermined time, or is based on a geofence). For example, based on the user's location at a coffee shop, the trigger time might be 2:45 PM, allowing travel time to the nearest ATM, travel time from the ATM to the Acme property, and time to stay at the Acme gym. At step 320, once the trigger time has occurred, the reminder is triggered for presentation to the user.

With reference to Figure 4, an exemplary system for presenting a trigger reminder suitable for use with an embodiment of the present invention is depicted and is referred to as system 400 as a whole. System 400 is merely an example of a suitable system and is not intended to impose any limitations on the scope of use or functionality of the present invention. System 400 should also not be interpreted as having any dependencies or requirements related to any single component or combination of components shown herein. Other arrangements and elements may be used in addition to or in place of those shown, and some elements may be omitted entirely for clarity. In addition, many of the elements described herein are functional entities that may be implemented as discrete or distributed components, or used in combination with other components, and implemented in any suitable combination and location.

System 400 includes server 410, data collection component 412, inference engine 414, reminder surfacing component 416, user profile data store 418, calendar information store 420, and may optionally include user device 422. The various components of system 400 may communicate via network 426.

The server 410 includes one or more computing devices and may be a server, multiple servers, or other computing devices configured to communicate via the network 426. The server 410 may include one or more applications or services on a user device, across multiple user devices, and/or in the cloud. The data collection component 412 is configured to collect contextual information associated with the user. In one embodiment, the contextual information includes user preferences, identities of individuals associated with the user, frequently visited locations, frequently traveled routes, locations associated with events, locations associated with the user, the user's current location, and the like. The contextual information may be collected or derived from a variety of sources. In some embodiments, contextual data can be obtained from one or more sensors, such as sensors that provide the following data: smartphone data, home sensor data, GPS data, vehicle signal data, wearable device data, user device data, gyroscope data, accelerometer data, calendar data, email data, schedule data, credit card usage data, purchase history data, weather data, other sensor data that can be sensed or otherwise detected by a sensor (or detector) component, data that can be derived from a sensor component associated with a user or event (including location, motion, direction, position, user access, user activity, network access, device charging, or other data that can be provided by one or more sensor components), and other more data. The data collection component 412 can also be configured to collect contextual information associated with other individuals associated with the user (including individuals associated with the user's calendar events and/or reminders).

The user profile storage 418 is configured to store contextual information collected by the data collection component 412. The user profile storage 418 may include one or more computer storage media and/or one or more computing devices, and may include one or more applications or services on the user device, across multiple user devices, and/or in the cloud. The user profile storage 418 may include one or more storage devices. In one embodiment, in addition to the contextual information collected by the data collection component 412, the user profile storage 418 also stores contextual information inferred or otherwise derived from the collected data or other information associated with the user. For example, indications of frequently visited locations, frequently traveled routes, regularly attended events, etc., which can be inferred from historical location/travel data and calendar data, may be stored.

Calendar information storage 420 may include one or more computer storage media and/or one or more computing devices and may include one or more applications or services on a user device, across multiple user devices, or in the cloud. Calendar information storage 420 stores information related to a user's calendar application and/or calendar application, or other types of applications that utilize or maintain scheduled events and reminders. Calendar and calendar applications typically organize and display a user's activities, tasks, assignments, appointments, meetings, and other types of events. They may also provide event reminders or notifications that are presented to the user based on the date and time of the event. In one embodiment, calendar information storage 420 stores information associated with multiple users.

Inference engine 414 may include one or more computing devices configured to derive contextual information associated with a user. Inference engine 414 may include one or more applications or services on a user device, across multiple user devices, and/or in the cloud. In one embodiment, inference engine 414 derives contextual information associated with a user based on information accessed from calendar information storage 420 and user profile storage 418. Inference engine 414 is configured to derive various information that can be used to determine when a reminder should surface or be triggered. For example, in one embodiment, inference engine 414 accesses event reminders describing events associated with the user within the user's calendar information. Inference engine 414 identifies individuals associated with the event, other than the user, and determines a future time at which the user is predicted to be within a proximity threshold of the individual. The user's proximity to another individual may be determined based on the distance between the user and the other individual (e.g., straight-line distance or distance along a route such as a street, sidewalk, etc.). The proximity may also be based on the amount of travel time between the user and the individual, such as walking time, driving time, or other means of transportation. In one embodiment, an individual's proximity is determined based on the distance and/or travel time between another individual and a point along the route the user is predicted to travel. The proximity can also be determined based on the distance and/or travel time required to deviate from the predicted route in order to meet the other individual. A threshold associated with the proximity can be determined based on the user's preference for a specific distance or specific travel time and/or a predetermined distance or travel time, within which the user is determined to be within the proximity of the individual. In one embodiment, the threshold associated with the proximity is determined at least in part based on the nature of the relationship between the user and the other individual and/or the priority level associated with the other individual. For example, when a task is associated with a close family member, the user may be willing to travel farther to perform the task than when the task is associated with a friend. In this case, a larger proximity threshold can be used than when the task is associated with a friend. The priority level associated with the other individual can be based on whether the individual is designated within the user's inner circle and/or based on the priority levels assigned to individuals within the user's inner circle.

The future time can be determined based on contextual information associated with the user. The contextual information can include information such as calendar information, scheduled events, other reminders, known routes that the user has historically traveled and/or the number of times the user has traveled, known locations that the user has historically visited and/or the number of times the user has visited, etc. Similarly, the location of another individual can be predicted using known information about the other individual. This can include: (1) information that is known in the user's contextual information and does not require access to the other individual's personal information (e.g., calendar invitations that include the individual, the individual's home location, the individual's work location, etc.); and (2) information that requires access to the other individual's personal information (e.g., calendar information, reminders, current GPS from the individual's mobile device, etc.). The other individual's personal information can be accessed based on the permission granted by the other individual. A time is determined to trigger a reminder for presentation to the user, and the time can be determined to occur in a time period before the future time when the user is predicted to be in the vicinity of the individual. The time to trigger the reminder can be a specific time, or can be based at least in part on a geofence (such as when the user leaves or arrives at a specific location). In one embodiment, the reminder appearance component 416 is configured to determine that a time to trigger a reminder has occurred (eg, the current time corresponds to a specific predetermined time, or is based on a geofence), and trigger the reminder for presentation to the user.

With reference to Figure 5, an exemplary system for presenting a trigger reminder suitable for use with an embodiment of the present invention is depicted and is referred to as system 500 as a whole. System 500 is merely an example of a suitable system and is not intended to impose any limitations on the scope of use or functionality of the present invention. System 500 should also not be interpreted as having any dependencies or requirements related to any single component or combination of components shown herein. Other arrangements and elements may be used in addition to or in place of those shown, and some elements may be omitted entirely for clarity. In addition, many of the elements described herein are functional entities that may be implemented as discrete or distributed components, or used in combination with other components, and implemented in any suitable combination and location.

System 500 includes an alert component 510, a user profile store 512, an auxiliary service component 514, a data collection component 516, and an inference engine 518. System 500 communicates with one or more user devices 520, which are not necessarily part of system 500.

In one embodiment, reminder component 510 includes one or more computing devices configured to manage reminders. Reminder component 510 may include one or more applications or services on a user device, across multiple user devices, in the cloud, or a combination thereof. Reminder component 510 communicates with user device 520 and may receive data such as reminder data and contextual user information from user device 520. Reminder data may include parameters used to configure reminders, such as location, date, time, subject, references to other users or individuals, and so on. Contextual user information may include current location, local time, GPS and other sensor data, calendar information, user preferences, email data, text message data, and so on. Contextual information may be stored in user profile storage 512. In one embodiment, reminder component 510 stores and maintains reminders to be displayed (i.e., presented) to the user at a certain point in time. Stored reminders may include any or all of the aforementioned reminder parameters received from user device 520. In one embodiment, stored reminders include one or more parameters received from inference engine 518. For example, inference engine 518 may provide a trigger time for triggering a particular reminder. The data transmitted from the reminder component 510 to the user device 520 may include a reminder to be presented to the user on the user device. In one embodiment, the reminder component 510 is configured to determine that a time to trigger a reminder has occurred and trigger the reminder to be presented to the user. In one embodiment, the reminder component 510 ensures that reminders are intelligently synchronized across devices, for example, triggering reminders on the appropriate device of the user based on which device or devices the user is currently using. The reminder component 510 may also parse or infer information about individuals named in events or reminders, such as whether the individual is related to the user through a work relationship, personal relationship, social relationship, family relationship, etc.

The user profile storage 512 may include one or more computer storage media and/or one or more computing devices, and may include one or more storage devices. The user profile storage 512 may include one or more applications or services on a user device, across multiple user devices, or in the cloud. In one embodiment, the user profile storage 512 is configured to store contextual information associated with the user device 520 and/or the user of the user device 520. The contextual information may be received from the reminder component 510 and may also be received from either or both of the data collection component 516 and the inference engine 518. In an embodiment, in addition to the contextual information, the user profile storage 512 stores contextual information inferred or otherwise derived from other contextual data and/or other information associated with the user. For example, indications of frequently visited locations, frequently traveled routes, regularly attended events, etc. determined from the user's historical travel patterns may be stored.

In one embodiment, the inference engine 518 includes one or more computing devices and one or more applications or services that may be included on a user device, across multiple user devices, and/or in the cloud. The inference engine 518 may be configured to derive contextual information associated with the user based on any information received from the user device 520, calendar information, reminder information, and user profile information. The user profile storage 512 may include one or more computer storage media and/or one or more applications or services on the user device, across multiple user devices, and/or in the cloud. The inference engine 518 may derive various information that can be used to determine when a reminder should be surfaced or triggered. For example, in one embodiment, the inference engine 518 accesses an event reminder that describes an event associated with the user. The inference engine 518 identifies individuals associated with the event, other than the user, and determines a future time at which the user is predicted to be within a predetermined proximity of the individual. The proximity of the user to the individual may be determined based on the distance between the user and the individual (e.g., straight-line distance or distance along a route such as a street, sidewalk, etc.). The proximity may also be based on the amount of travel time between the user and the individual, such as walking time, driving time, or other transportation time. In one embodiment, the proximity of an individual is determined based on the distance and/or travel time between the other individual and a point along the route that the user is predicted to travel. The proximity can also be determined based on the distance and/or travel time required to deviate from the predicted route in order to meet the other individual.

The future time can be determined based on contextual information associated with the user. The contextual information can include information such as calendar information, scheduled events, other reminders, known routes that the user has historically traveled and/or the number of times the user has traveled, known locations that the user has historically visited and/or the number of times the user has visited, etc. Similarly, the location of another individual can be predicted using known information about the other individual. This can include: (1) information that is known in the user's contextual information and does not require access to the other individual's personal information (e.g., calendar invitations that include the individual, the individual's home location, the individual's work location, etc.); and (2) information that requires access to the other individual's personal information (e.g., calendar information, reminders, current GPS from the individual's mobile device, etc.). The other individual's personal information can be accessed based on the permission granted by the other individual. A time is determined to trigger a reminder for presentation to the user, and the time can be determined to occur in a time period before the future time when the user is predicted to be within the proximity of the individual. The time to trigger the reminder can be a specific scheduled time, or can be based on a geofence (such as when the user leaves or arrives at a specific location). In one embodiment, the inference engine 518 provides the trigger time to the reminder component 510, which associates the trigger time with the reminder and can determine that the time to trigger the reminder has occurred (e.g., the current time corresponds to a specific scheduled time, or based on a geofence).

In one embodiment, the data collection component 516 includes one or more computing devices and is configured to collect contextual information associated with the user. The data collection component 516 may include one or more applications or services on a user device, across multiple user devices, or in the cloud. In one embodiment, the contextual information includes user preferences, identification of individuals associated with the user, frequently visited locations, frequently traveled routes, locations associated with events, locations associated with the user, the user's current location, and the like. Contextual information can be collected or derived from various sources. In some embodiments, contextual data can be obtained from one or more sensors, such as sensors that provide the following data: smartphone data, home sensor data, GPS data, vehicle signal data, wearable device data, user device data, gyroscope data, accelerometer data, calendar data, email data, schedule data, credit card usage data, purchase history data, weather data, other sensor data that can be sensed or otherwise detected by a sensor (or detector) component, data derived from a sensor component associated with a user or event (including position, motion, direction, location, user access, user activity, network access, device charging, or other data that can be provided by one or more sensor components), and other more data.

In one embodiment, the auxiliary service component 514 includes one or more computing devices and is configured to present context-related reminders and related content to the user based on reminder data determined by the reminder component 510, user profile data from the user profile storage 512, and/or other context data about the user. The auxiliary service component 514 may include one or more applications or services on a user device, across multiple user devices, in the cloud, or a combination thereof. For example, in one embodiment, the auxiliary service component 514 manages the presentation of reminders to the user across multiple user devices 520 associated with the user. Based on the reminder data and user context data, the auxiliary service component 514 can determine on which user device 520 to present the reminder, and the context of the presentation, including how to present (or in what format and how much content to present, which may depend on the user device or context), when to present, and which supplementary content to present with it. Specifically, in some embodiments, the auxiliary service component 514 applies the sensed user data and context information to determine the presentation of the reminder.

In some embodiments, the auxiliary service component 514 generates user interface features associated with the notification. These features may include interface elements (such as graphical buttons, sliders, menus, audio prompts, alerts, alarms, vibrations, pop-ups, notification or status bar items, in-app notifications, or other similar features for interfacing with the user), queries, and prompts. Some embodiments of the auxiliary service component 514 capture user responses to notifications or user activities associated with notifications.

User device 520 may include any type of computing device capable of being used by a user. For example, in one embodiment, user device 520 may be similar to computing device 100 described below with respect to FIG. By way of example and not limitation, a user device may be embodied as a personal computer, a laptop computer, a mobile or mobile device, a smartphone, a tablet computer, a smartwatch, a wearable computer, a personal digital assistant (PDA), an MP3 player, a GPS or device, a video player, a handheld communication device, a gaming device or system, an entertainment system, an in-vehicle computer system, an embedded system controller, a remote control, an appliance, a consumer electronic device, a workstation, or any combination of these described devices, or any other suitable device.

With reference now to FIG1 , an exemplary operating environment suitable for implementing embodiments of the present invention is illustrated and generally referred to as computing device 100. Computing device 100 is merely an example of one suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the present invention. Neither should computing environment 100 be interpreted as having any dependency or requirement relating to any single component or combination of components illustrated herein.

Some embodiments of the present invention may be described in the general context of computer code or machine-usable instructions, which include computer-executable instructions (such as program modules) executed by a computer or other machine (such as a personal digital assistant or handheld device). Generally, program modules, including routines, programs, objects, components, data structures, etc., refer to code that performs a specific task or implements a specific abstract data type. Some embodiments of the present invention may be practiced in various system configurations (including handheld devices, consumer electronic devices, general-purpose computers, more specialized computing devices, etc.). Some embodiments of the present invention may also be implemented in a distributed computing environment, where tasks are performed by remote processing devices linked through a communication network.

Referring to FIG. 1 , computing device 100 includes a bus 110 that directly or indirectly couples the following devices: memory 112 , one or more processors 114 , one or more presentation components 116 , input/output ports 118 , an input/output component 120 , and a schematic power supply 122 . Bus 110 represents one or more buses (such as an address bus, a data bus, or a combination thereof). Although various blocks in FIG. 1 are illustrated with lines for clarity, the demarcation of various components is not so clear; for example, gray and fuzzy lines would be more accurate. For example, presentation components such as display devices can be considered I/O components. Furthermore, processors have memory. We recognize that this is a quirk of the art and reiterate that FIG. 1 is merely illustrative of an exemplary computing device that can be used in conjunction with one or more embodiments of the present invention. No distinction is made between categories such as "workstation," "server," "laptop," "handheld device," etc., as all are encompassed within the scope of FIG. 1 and referred to as a "computing device."

The computing device 100 typically includes a variety of computer-readable media. By way of example and not limitation, the computer-readable media may include random access memory (RAM); read-only memory (ROM); electrically erasable programmable read-only memory (EEPROM); flash memory or other memory technology; CDROM, digital versatile disk (DVD) or other optical or holographic media; magnetic cassettes, magnetic tape, disk storage or other magnetic storage devices, carrier waves, or any other medium that can be used to encode the desired information and accessed by the computing device 100.

Memory 112 includes computer storage media in the form of volatile and/or non-volatile memory. The memory can be removable, non-removable, or a combination thereof. Exemplary hardware devices include solid-state memory, hard drives, optical drives, etc. As used herein, computer storage media itself does not include signals.

Computing device 100 includes one or more processors that read data from various entities such as memory 112 or I/O components 120. Presentation component 116 presents data indications to a user or other device. Exemplary presentation components include a display device, a speaker, a printing component, a vibration component, etc. I/O ports 118 allow computing device 100 to be logically coupled to other devices including I/O components 120, some of which may be internal. Exemplary components include a microphone, a joystick, a game pad, a satellite dish, a scanner, a printer, a wireless device, etc.

As can be seen from the foregoing, the present invention is well suited to achieve all of the goals and objectives set forth above, along with other advantages that are readily apparent and inherent to the structure. It will be understood that certain features and subcombinations are useful and can be used without reference to other features and subcombinations. This is contemplated by and within the scope of the claims. Since many possible embodiments of the present invention can be made without departing from the scope of the invention, it will be understood that all matter set forth herein or shown in the accompanying drawings is to be interpreted as illustrative and not restrictive.

Claims (18)

1. A method for triggering the presentation of an alert on a mobile device, comprising: Accessing the reminder stored in one or more computer storage media via a processing device, wherein the reminder describes a task associated with a user of the mobile device, and wherein the task described in the reminder is not defined with respect to a specific time; Identify the individuals associated with the task, wherein the individuals are persons other than the user; Predict the future time when the user will be in the vicinity of the individual; The time for triggering the alert to be presented to the user is determined such that the time for triggering the alert occurs before the future time in which the user is predicted to be within the individual's neighborhood, wherein the time for triggering the alert is determined by: Predict the future location of the user that will be within the vicinity of the individual at a predicted future time; Identify the user's starting position; Predict the route the user will take from the starting position to the future position; Determine the amount of time to travel along the predicted route from the starting position to the future position; and The time for triggering the alert is determined, at least in part, based on the amount of travel time. It has been determined that the time used to trigger the alert has occurred; and Based on the determination that the time for triggering the reminder has occurred, the reminder is presented to the user. 2. The method of claim 1, wherein predicting the future time when the user will be within the vicinity of the individual comprises: Access the calendar information associated with the user; Identify events from the user's calendar information, wherein the events are associated with the individual and have a planned future time; and The planned future time of the event is identified as the future time when the user is predicted to be within the individual's vicinity. 3. The method of claim 2, wherein the event is an event separate from the task. 4. The method of claim 1, wherein predicting the route the user will take from the starting position to the future position comprises: Access the user profile data associated with the user; Identify one or more routes that the user has historically traveled from the starting position to the future position; Based on the probability associated with each of the one or more routes, determine the most probable route from the one or more routes that the user has historically traveled; and The most likely route is identified as the predicted route by which the user will travel from the starting position to the future position. 5. The method of claim 1, wherein identifying the user's starting position includes identifying the user's current position as the user's starting position. 6. The method of claim 1, wherein identifying the user's starting position comprises: Access the user profile data associated with the user; The user's historical travel patterns are identified from the user profile data; Based at least in part on the user's historical travel pattern, a second future location of the user is predicted, and the user will be located at the second future location before the predicted future time. The predicted second future location is identified as the user's starting location. 7. The method of claim 1, wherein the reminder, once triggered, is configured to last for a period of time prior to the predicted future time when the user will be within the vicinity of the individual. 8. A system for triggering the presentation of calendar event reminders on a mobile device, comprising: One or more computer storage media configured to store calendar information associated with a user of a user device; A data collection component, including one or more processing devices, is configured to collect contextual information associated with the user; One or more computer storage media configured to store the context information associated with the user; An inference engine comprising one or more processing devices, the inference engine being configured to: Access event alerts, which describe tasks associated with a user of a user device, wherein the tasks described in the event alerts are not defined with respect to a specific time. Identify the individuals associated with the task, wherein the individuals are persons other than the user; and Determine the future time at which the user is predicted to be within a predetermined neighborhood of the individual; Determine the time for triggering the alert to be presented to the user, wherein the time for triggering the alert occurs in a time period prior to the future time in which the user is predicted to be within the predetermined proximity range of the individual, wherein, in order to determine the time period prior to the future time in which the user is predicted to be within the predetermined proximity range of the individual, the inference engine is further configured to: Identify the user's current location; Identify the future location of the user that is predicted to be within the predetermined proximity range of the individual; Determine the route the user is predicted to take from the current location to the future location; Determine the travel time from the current location to the future location along the route; and Based at least in part on the amount of travel time, determine the time period preceding the future time in which the user is predicted to be within the predetermined neighborhood of the individual; A notification display component including one or more processing devices, the notification display component being configured to: It has been determined that the time used to trigger the alert has occurred; and The reminder is then presented to the user. 9. The system of claim 8, wherein determining the future time in which the user is predicted to be within the predetermined proximity range of the individual comprises: Access the calendar information associated with the user; Access the calendar information associated with the individual; The user's calendar information identifies a first event associated with a first location and a first time; The individual's calendar information identifies a second event associated with a second location and a second time; It is determined that the first location is within the vicinity of the second location; Determine that the first time is within the vicinity of the second time; and The time associated with the first event or the time associated with the second event is identified as the future time at which the user is predicted to be within the predetermined proximity range of the individual. 10. The system of claim 9, wherein the first event and the second event are independent of each other. 11. A method for triggering the presentation of a calendar event reminder, comprising: Through one or more processing devices: Access event alerts stored in an information storage associated with a scheduling application, wherein the event alerts describe events associated with a user of a user device; Identify the individuals associated with the event, wherein the individuals are persons other than the user; Determining a predicted future time, wherein the user will be located at a point along the predicted route the user will travel and within a predetermined proximity range of the individual, wherein determining the predicted future time includes: Determine the predicted route that the user will travel in a first future time. Determine the predicted location of the individual at a second future time; Determine that the point along the predicted route is within the predetermined proximity range of the individual's predicted location; It is determined that the user will arrive at the point along the predicted route at the same time the individual is located at the individual's predicted location; The time associated with the time when the user will arrive at the point along the route is identified as the predicted future time when the user will be within the predetermined proximity range of the individual; Determine the time to trigger the alert for presentation to the user, wherein the time to trigger the alert is determined to occur within a time period preceding the predicted future time when the user will be within the predetermined proximity range of the individual; It has been determined that the time that triggered the reminder has occurred; and Based on the determination that the time for triggering the reminder has occurred, the reminder is presented to the user. 12. The method of claim 11, wherein determining the predicted route that the user will travel in the first future time is based at least in part on one or more of the following: Calendar information associated with the user; User profile information associated with the user; or One or more historical travel patterns associated with the user. 13. The method of claim 11, wherein determining the predicted location of the individual at the second future time is based at least in part on one or more of the following: Calendar information associated with the individual; User profile information associated with the individual; or One or more historical movement patterns associated with the individual. 14. The method of claim 11, wherein the destination location to which the user is predicted to travel is independent of the location to which the individual is predicted to be located. 15. The method of claim 11, wherein determining the route that the user is predicted to travel in the first future time comprises: Indicates the route the user is currently traveling; Determine the predicted remainder of the current route the user will travel; and The predicted remainder of the current route is identified as the route that the user is predicted to travel at the first future time. 16. The method of claim 11, wherein the predicted route is a route suggested to the user. 17. The method of claim 11, wherein the event described in the event alert is not defined with respect to a specific time. 18. The method of claim 11, wherein once triggered, the reminder is configured to continue for a period of time prior to the predicted future time when the user will be within a predetermined proximity range of the individual.