[go: up one dir, main page]

He et al., 2021 - Google Patents

Automatic topic labeling using graph-based pre-trained neural embedding

He et al., 2021

Document ID
3209932445015521024
Author
He D
Ren Y
Khattak A
Liu X
Tao S
Gao W
Publication year
Publication venue
Neurocomputing

External Links

Snippet

It is necessary to reduce the cognitive overhead of interpreting the native topic term list of the Latent Dirichlet Allocation (LDA) style topic model. In this regard, automatic topic labeling has become an effective approach to generate meaningful alternative representations of …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30634—Querying
    • G06F17/30657—Query processing
    • G06F17/30675—Query execution
    • G06F17/30684—Query execution using natural language analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30634—Querying
    • G06F17/30657—Query processing
    • G06F17/30675—Query execution
    • G06F17/3069—Query execution using vector based model
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20—Handling natural language data
    • G06F17/27—Automatic analysis, e.g. parsing
    • G06F17/2765—Recognition
    • G06F17/277—Lexical analysis, e.g. tokenisation, collocates
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20—Handling natural language data
    • G06F17/27—Automatic analysis, e.g. parsing
    • G06F17/2705—Parsing
    • G06F17/2715—Statistical methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30705—Clustering or classification
    • G06F17/3071—Clustering or classification including class or cluster creation or modification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20—Handling natural language data
    • G06F17/21—Text processing
    • G06F17/22—Manipulating or registering by use of codes, e.g. in sequence of text characters
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30705—Clustering or classification
    • G06F17/30707—Clustering or classification into predefined classes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20—Handling natural language data
    • G06F17/27—Automatic analysis, e.g. parsing
    • G06F17/2785—Semantic analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20—Handling natural language data
    • G06F17/28—Processing or translating of natural language
    • G06F17/2809—Data driven translation
    • G06F17/2827—Example based machine translation; Alignment
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30861—Retrieval from the Internet, e.g. browsers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/02—Knowledge representation
    • G06N5/022—Knowledge engineering, knowledge acquisition
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99933—Query processing, i.e. searching
    • Y10S707/99936—Pattern matching access

Similar Documents

Publication Publication Date Title
Shaheen et al. Large scale legal text classification using transformer models
Papagiannopoulou et al. Local word vectors guiding keyphrase extraction
Jiang et al. Sentence level topic models for associated topics extraction
Gupta et al. Analyzing the dynamics of research by extracting key aspects of scientific papers
Toshevska et al. Comparative analysis of word embeddings for capturing word similarities
Rahman et al. Improvement of query-based text summarization using word sense disambiguation
He et al. Automatic topic labeling using graph-based pre-trained neural embedding
Atkinson et al. Rhetorics-based multi-document summarization
Litvak et al. Cross-lingual training of summarization systems using annotated corpora in a foreign language
Patel et al. Extractive Based Automatic Text Summarization.
Zandbiglari et al. A text analytics framework for supplier capability scoring supported by normalized google distance and semantic similarity measurement methods
Morsy et al. Accounting for language changes over time in document similarity search
Ghosh Natural language processing: Basics, challenges, and clustering applications
Patel et al. An automatic text summarization: A systematic review
Iwatsuki et al. Using formulaic expressions in writing assistance systems
Kumar et al. Analysis of Indian and American poetry using topic modeling and Deep learning
Elayeb et al. SPEEDSER: A Possibilistic System for Query Disambiguation, Expansion and Translation
Minkov et al. Adaptive graph walk-based similarity measures for parsed text
Moratanch et al. A novel framework for semantic oriented abstractive text summarization
Ifrim et al. Learning word-to-concept mappings for automatic text classification
Toshevska The ability of word embeddings to capture word similarities
Gao et al. Boosting Short Text Classification by Solving the OOV Problem
D’Silva et al. Automatic Text Summarization of Konkani Texts Using Latent Semantic Analysis
Gabsi et al. MeSH-based disambiguation method using an intrinsic information content measure of semantic similarity
Ahmed et al. Automatically temporal labeled data generation using positional lexicon expansion for focus time estimation of news articles