RUBRIC: A System for Rule-Based Information Retrieval
IEEE Transactions on Software Engineering - Special issue on COMPSAC 1982 and 1983
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SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
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SPIRE '00 Proceedings of the Seventh International Symposium on String Processing Information Retrieval (SPIRE'00)
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IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
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One of the main issues in the field of information retrieval is to bridge the terminological gap existing between the way in which users specify their information needs and the way in which queries are expressed. One of the approaches for this purpose, called Rule Based Information Retrieval by Computer (RUBRIC), involves the use of production rules to capture user query concepts (or topics). In RUBRIC, a set of related production rules is represented as an AND/OR tree. The retrieval output is determined by Boolean evaluation of the AND/OR tree. However, since the Boolean evaluation ignores the termterm association unless it is explicitly represented in the tree, the terminological gap between users' queries and their information needs can still remain. To solve this problem, we adopt the generalized vector space model (GVSM) in which the term-term association is well established, and extend the RUBRIC model based on GVSM. Experiments have been performed on some variations of the extended RUBRIC model, and the results have also been compared to the original RUBRIC model based on recall-precision.