A method for verifying a vector-based text classification system

A method for verifying a vector-based text classification system

Journal Descriptor Indexing (JDI) is a vector-based text classification system developed at NLM (National Library of Medicine), originally in Lisp and now as a Java tool. Consequently, a testing suite was developed to verify training set data and results of the JDI tool. A methodology was developed...

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Veröffentlicht in:AMIA ... Annual Symposium proceedings 2008-11, p.1030-1030
Hauptverfasser: Lu, Chris J, Humphrey, Susanne M, Browne, Allen C
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Artificial Intelligence
Information Storage and Retrieval - methods
Natural Language Processing
Pattern Recognition, Automated - methods
Terminology as Topic
United States
Vocabulary, Controlled
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Zusammenfassung:Journal Descriptor Indexing (JDI) is a vector-based text classification system developed at NLM (National Library of Medicine), originally in Lisp and now as a Java tool. Consequently, a testing suite was developed to verify training set data and results of the JDI tool. A methodology was developed and implemented to compare two sets of JD vectors, resulting in a single index (from 0 - 1) measuring their similarity. This methodology is fast, effective, and accurate.
ISSN:1559-4076