Semantic Search for Information System Domain Bibliographic Data
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Abstract
- Searching through digital information by using keywords usually returns incorrect results and does not reflect user requirements. The researchers have developed semantic search or ontology that increases efficiency of information retrieval. However, one of the problems of semantic search is that development depends on the expert knowledge. To solve the problem above, this research proposes sub class creation via semi-automatic techniques and finding relation of class by association rules. The proposed method is composed of 4 steps: 1) feature selection using Chi-Square and Support Vector Machine Radial basis function (SVMR) in order to reduce phrases and send statistics value into a subclass to aid the semi-automatic ontology, 2) semantic terms mapping using association rule methods, 3) development of Semantic Search for Information System Domain Bibliographic Data, and 4) evaluation of the developed information retrieval system. The result of the proposed method produced precision at 97.07%.
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