Granitzer, 2003 - Google Patents
Hierarchical text classification using methods from machine learningGranitzer, 2003
View PDF- Document ID
- 1757064291536382530
- Author
- Granitzer M
- Publication year
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Snippet
Due to the permantently growing amount of textual data, automatic methods for organizing the data are needed. Automatic text classification is one of this methods. It automatically assigns documents to a set of classes based on the textual content of the document …
- 238000010801 machine learning 0 title abstract description 7
Classifications
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- 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
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- G—PHYSICS
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- G06F17/30705—Clustering or classification
- G06F17/3071—Clustering or classification including class or cluster creation or modification
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- G—PHYSICS
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- G06F17/30613—Indexing
- G06F17/30619—Indexing indexing structures
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- G—PHYSICS
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- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
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- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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- G—PHYSICS
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/68—Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of references in which the sequence of the image signals or the references is relevant, e.g. addressable memory
- G06K9/6807—Dividing the references in groups prior to recognition, the recognition taking place in steps; Selecting relevant dictionaries
- G06K9/6842—Dividing the references in groups prior to recognition, the recognition taking place in steps; Selecting relevant dictionaries according to the linguistic properties, e.g. English, German
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- 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
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