Semantic SimilarityBased Information Retrieval Method
WANG Jin1, CHEN EnHong1, SHI DeMing1, ZHANG ZhenYa2
1.Department of Computer Science and Technology, University of Science and Technology of China, Hefei 230027 2.Department of Electronical Engineering and Information Science, University of Science and Technology of China, Hefei 230027
Abstract：With exponential growth of web information and emergence of semantic web, semantic information retrieval becomes a hotspot of current research. In this paper, a novel information retrieval method based on semantic similarity is studied. By exploiting the advantage of ontology in describing semantic as well as in computing the ConceptSimilarity and PropertySimilarity for the semantic retrieval algorithm, the proposed method greatly improves the retrieval precision. The statistic analysis of the semantic retrieval experiment results illustrates that the retrieval accuracy is improved significantly with the increase of the feature vector concepts and the properties of the retrieved documents.
[1] Navigli R, Velardi P. An Analysis of Ontology-Based Query Expansion Strategies [EB/OL] // Proc of the 14th European Conference on Machine Learning. Dubrovnik, Croatia. [2003-12-20]. http://www.dsi.vniroma1.it/~navigli/pubs/ECML_2003.Navigli_Velardi.pdf [2] Abdelali A, Cowie J, Farwell D. Cross-Language Information Retrieval Using Ontology [EB/OL]. [2003-12-01]. http://www.sciences.univ-natites.fr/info/recherche/taln2003/articles/abdelali.pdf [3] Liu Qun, Li Sujian. HowNet-Based Computation of Words Semantic Similarity. Computational Linguistics and Chinese Language Processing, 2002, 7(2): 59-76 (in Chinese) (刘 群,李素建.基于《知网》的词汇语义相似度计算.中文计算语言学, 2002, 7(2): 59-76 [4] Cinque L, Malizia A, Navigli R. A Semantic-Based System for Querying Personal Digital Libraries // Proc of the Workshop on Document Analysis Systems. Florence, Italy, 2004, 39-46 [5] Navigli R, Velardi P. A Knowledge-Based Approach to Ontology Learning and Semantic Annotation[EB/OL] // Proc of the 16th International Conference on Advanced Information Systems Engineering. Riga, Latvia. [2004-11-12]. http://ftp.in formatik.rath-aachen.de/Publications/CEUR-ws/vol-125/paper 7.pdf [6] Buntine W, Lfstrm J L, Perttu S, Valtonen K. Topic-Specific Scoring of Documents for Relevant Retrieval // Proc of the Workshop on Learning in Web Search. Bonn, Germany, 2005: 33-41 [7] Sjberg M, Laaksonen J. Content-Based Retrieval of Web Pages and Other Hierarchical Objects with Self-Organizing Maps // Proc of the 15th International Conference on Artificial Neural Networks. Warsaw, Poland, 2005: 841-846 [8] Wang Jin, Chen Enhong, Zhang Zhengya, et al. An Ontology-Based Cross Language Information Retrieval Model. Journal of Chinese Information Processing, 2004, 18(3): 1-8,60 (in Chinese) (王 进, 陈恩红, 张振亚,等. 基于本体的跨语言信息检索模型. 中文信息学报, 2004, 18(3): 1-8,60) [9] Wang Jin, Chen Enhong, Shi Deming. A Model and Application of an Ontology-Based Semantic Information Retrieval // Proc of the Conference on Fuzzy Logic and Computational Intelligence. Shenzhen, China, 2005, Ⅰ: 524-529 (in Chinese) (王 进, 陈恩红, 施德明. 一种基于本体的语义信息检索模型与实现.//中国模糊逻辑与计算智能联合学术会议.深圳, 2005, Ⅰ: 524-529)
2006, Vol. 19 
