Terminological knowledge structure for intermediary expert systems

摘要

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.