作者: B.P. Mc Cune , R.M. Tong , J.S. Dean , D.G. Shapiro
关键词: Set (abstract data type) 、 Hierarchy 、 Natural language processing 、 Rubric 、 Context (language use) 、 Document retrieval 、 Human–computer information retrieval 、 Artificial intelligence 、 Computer science 、 Ranking 、 Vector space model 、 Information retrieval 、 Expert system 、 Rule-based system
摘要: A research prototype software system for conceptual information retrieval has been developed. The goal of the system, called RUBRIC, is to provide more automated and relevant access unformatted textual databases. approach use production rules from artificial intelligence define a hierarchy subtopics, with fuzzy context expressions specific word phrases at bottom. RUBRIC allows definition detailed queries starting level, partial matching query document, selection only highest ranked documents presentation user, explanation how why particular document was selected. Initial experiments indicate that rule set better matches human judgment than standard Boolean keyword expression, given equal amounts effort in defining each. techniques presented may be useful stand-alone systems, front-ends existing or real-time filtering routing.