Ontology Based Semantic Measures in Document Similarity Ranking

Abstract

Recent work has shown that ontologies are useful to improve the performance of retrieval. In this paper, we present a new distance measure using ontologies. Ontology based correlation analysis is implemented to find the relations between the terms. Combining the ontology based correlation analysis and the traditional vector space model, the document similarity is calculated. Our results show that ontology based distance measure makes better relevance measure. The proposed method has been evaluated on USGS Science directory collection. Preliminary experiments results show that our method may generate relevant document in the top rank.