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Granitzer et al., 2005 - Google Patents

Experiments with hierarchical text classification

Granitzer et al., 2005

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Document ID
5524175496631690215
Author
Granitzer M
Auer P
Publication year
Publication venue
Proc. of 9th IASTED International Conference on Artifical Intelligence

External Links

Snippet

This paper applies Boosting to hierarchical text classification where the hierarchical structure is given as directed acyclic graph and compares the results to Support Vector Machines. Hierarchical classification is performed topdown and in each node a flat classifier …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

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    • 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
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    • G06F17/30705—Clustering or classification
    • G06F17/30707—Clustering or classification into predefined classes
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    • G06F17/30634—Querying
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    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
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    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/12—Computer systems based on biological models using genetic models
    • G06N3/126—Genetic algorithms, i.e. information processing using digital simulations of the genetic system
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