caa a22 4500 475799267 CHVBK 20180406123732.0 cr unu---uuuuu 170329e20000301xx s 000 0 eng 10.1023/A:1008783718847 doi (NATIONALLICENCE)springer-10.1023/A:1008783718847 Enhancing Concept-Based Retrieval Based on Minimal Term Sets [Elektronische Daten] [A.H. Alsaffar, J.S. Deogun, V.V. Raghavan, H. Sever] There is considerable interest in bridging the terminological gap that exists between the way users prefer to specify their information needs and the way queries are expressed in terms of keywords or text expressions that occur in documents. One of the approaches proposed for bridging this gap is based on technologies for expert systems. The central idea of such an approach was introduced in the context of a system called Rule Based Information Retrieval by Computer (RUBRIC). In RUBRIC, user query topics (or concepts) are captured in a rule base represented by an AND/OR tree. The evaluation of AND/OR tree is essentially based on minimum and maximum weights of query terms for conjunctions and disjunctions, respectively. The time to generate the retrieval output of AND/OR tree for a given query topic is exponential in number of conjunctions in the DNF expression associated with the query topic. In this paper, we propose a new approach for computing the retrieval output. The proposed approach involves preprocessing of the rule base to generate Minimal Term Sets (MTSs) that speed up the retrieval process. The computational complexity of the on-line query evaluation following the preprocessing is polynomial in m. We show that the computation and use of MTSs allows a user to choose query topics that best suit their needs and to use retrieval functions that yield a more refined and controlled retrieval output than is possible with the AND/OR tree when document terms are binary. We incorporate p-Norm model into the process of evaluating MTSs to handle the case where weights of both documents and query terms are non-binary. Kluwer Academic Publishers, 2000 concept-based retrieval nationallicence Boolean retrieval nationallicence RUBRIC nationallicence DNF rules nationallicence AND/OR trees nationallicence minimal term sets nationallicence p-Norm nationallicence Alsaffar A.H. Department of Computer Science & Engineering, University of Nebraska-Lincoln, 68588, Lincoln, NE, USA aut Deogun J.S. Department of Computer Science & Engineering, University of Nebraska-Lincoln, 68588, Lincoln, NE, USA aut Raghavan V.V. The Center for Advanced Computer Studies, University of Louisiana-Lafayette, 70504, Lafayette, LA, USA aut Sever H. Department of Computer Science & Engineering, Hacettepe University, 06532, Beytepe, Ankara, Turkey aut Journal of Intelligent Information Systems Kluwer Academic Publishers 14/2-3(2000-03-01), 155-173 0925-9902 14:2-3<155 2000 14 10844 https://doi.org/10.1023/A:1008783718847 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1008783718847 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Alsaffar A.H. Department of Computer Science & Engineering, University of Nebraska-Lincoln, 68588, Lincoln, NE, USA aut NATIONALLICENCE 700 1- Deogun J.S. Department of Computer Science & Engineering, University of Nebraska-Lincoln, 68588, Lincoln, NE, USA aut NATIONALLICENCE 700 1- Raghavan V.V. The Center for Advanced Computer Studies, University of Louisiana-Lafayette, 70504, Lafayette, LA, USA aut NATIONALLICENCE 700 1- Sever H. Department of Computer Science & Engineering, Hacettepe University, 06532, Beytepe, Ankara, Turkey aut NATIONALLICENCE 773 0- Journal of Intelligent Information Systems Kluwer Academic Publishers 14/2-3(2000-03-01), 155-173 0925-9902 14:2-3<155 2000 14 10844 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer