RUBRIC: A System for Rule-Based Information Retrieval

作者: B.P. Mc Cune , R.M. Tong , J.S. Dean , D.G. Shapiro

DOI: 10.1109/TSE.1985.232827

关键词: Set (abstract data type)HierarchyNatural language processingRubricContext (language use)Document retrievalHuman–computer information retrievalArtificial intelligenceComputer scienceRankingVector space modelInformation retrievalExpert systemRule-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.

参考文章(1)
Brian P. McCune, Richard M. Tong, Daniel G. Shapiro, Jeffrey S. Dean, A comparison of uncertainty calculi in an expert system for information retrieval international joint conference on artificial intelligence. pp. 194- 197 ,(1983)