Terminological knowledge structure for intermediary expert systems
Identifieur interne : 001098 ( Main/Exploration ); précédent : 001097; suivant : 001099Terminological knowledge structure for intermediary expert systems
Auteurs : Raya Fidel [États-Unis] ; Efthimis N. Efthimiadis [États-Unis]Source :
- Information Processing and Management [ 0306-4573 ] ; 1994.
English descriptors
- Teeft :
- Additional keys, Additional knowledge, American petroleum institute, American society, Aszs szgcr classification research workshop, Attribute, Automatic indexing, British library, Broader descriptor, Classification scheme, Classification schemes, Database, Decision tree, Descriptor, Descriptor field, Different types, Disambiguation, Document retrieval systems, Educational database, Efthimiadis, Expert searchers, Expert system, Expert systems, Fideland efthimiadis, Frequency data, Hedge, Human indexers, Humphrey kwasnik, Humphreys lindberg, Iess, Inclusive search, Index terms, Indexer, Indexing, Indexing languages, Indexing manuals, Indexing policy, Inference engine, Information processing, Information processing management, Information retrieval, Information science, Information systems, Information technology, Intellectual indexing, Intermediary, Intermediary mechanism, International journal, Knowledge base, Knowledge structure, Language system, Many synonyms, Node, Nonlexical, Nonlexical expressions, Online, Online bibliographic databases, Online review, Online searchers, Other search keys, Problematic search keys, Professional searcher, Professional searchers, Query, Query expansion, Query formulation, Relevance feedback, Retrieval, Retrieval performance, Retrieval system, Retrieval techniques, Search keys, Search tactics, Searcher, Semantic relatedness, Semantic scale, Semantic vocabulary, Sparck jones, Subject domain, Such attributes, Such textword databases, Such tools, Synonym, Terminological, Terminological attributes, Terminological databanks, Terminological difficulties, Terminological knowledge, Terminological knowledge structure, Terminological research, Text processing, Textword, Textword synonyms, Thesaurus, User, Verbal protocols, Vocabulary control, Word sense disambiguation.
Abstract
An intermediary expert system (IES) helps both end users and professional searchers to conduct their online database searching. To provide advice about term selection and query expansion, an IES should include a terminological knowledge structure. Terminological attributes as well as other properties could provide the starting point for building a knowledge base, and knowledge acquisition could rely on knowledge-base techniques coupled with statistical techniques. The searching behavior of expert online searchers would provide one source of knowledge. The knowledge structure would include three constructs for each term: frequency data, a hedge, and a position in a classification scheme. Switching vocabularies or languages could provide a meta-schema and facilitate the interoperability of databases in similar subject domains. To develop such knowledge structure, future research should focus on terminological attributes, word and phrase disambiguation, automated text processing, and the role of thesauri and classification schemes in indexing and retrieval. In particular, such research should develop techniques that combine knowledge-base and statistical methods and that consider user preferences.
Url:
DOI: 10.1016/0306-4573(95)80003-C
Affiliations:
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To provide advice about term selection and query expansion, an IES should include a terminological knowledge structure. Terminological attributes as well as other properties could provide the starting point for building a knowledge base, and knowledge acquisition could rely on knowledge-base techniques coupled with statistical techniques. The searching behavior of expert online searchers would provide one source of knowledge. The knowledge structure would include three constructs for each term: frequency data, a hedge, and a position in a classification scheme. Switching vocabularies or languages could provide a meta-schema and facilitate the interoperability of databases in similar subject domains. To develop such knowledge structure, future research should focus on terminological attributes, word and phrase disambiguation, automated text processing, and the role of thesauri and classification schemes in indexing and retrieval. In particular, such research should develop techniques that combine knowledge-base and statistical methods and that consider user preferences.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Washington (État)</li></region><settlement><li>Seattle</li></settlement><orgName><li>Université de Washington</li></orgName></list><tree><country name="États-Unis"><region name="Washington (État)"><name sortKey="Fidel, Raya" sort="Fidel, Raya" uniqKey="Fidel R" first="Raya" last="Fidel">Raya Fidel</name></region><name sortKey="Efthimiadis, Efthimis N" sort="Efthimiadis, Efthimis N" uniqKey="Efthimiadis E" first="Efthimis N." last="Efthimiadis">Efthimis N. Efthimiadis</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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