The week's pick
Random Articles
Reseach Article
Information Retrieval using Dempster-Shafer Theory
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 102 - Number 13 |
| Year of Publication: 2014 |
| Authors: Phuke V. A, H. N. Bharathi |
10.5120/17879-8876
|
Phuke V. A, H. N. Bharathi . Information Retrieval using Dempster-Shafer Theory. International Journal of Computer Applications. 102, 13 ( September 2014), 33-37. DOI=10.5120/17879-8876
Abstract
Information retrieval model focuses on the problem of retrieving documents relevant to a user's information need represented as a query. One of the major difficulty of information retrieval is to find the relevance of documents with respect to the user query or information need. The choice of similarity measure is decisive for improving search effectiveness of a IR model. Different similarity measures have been proposed to find most relevant documents with the given query. Vector space model is a popular model and is widely used for information retrieval. The judgment of the relevance between a query and a document is evaluated using cosine similarity between them. However, vector space model does not give reasonable results in terms of precision and recall value. Information retrieval model using Dempster-Shafer theory also known as evidence theory is used in this paper. In this model, each query-document pair is taken as a piece of evidence for the relevance between a document and a query. The evidence is combined using Dempster's rule of combination and the belief committed to the relevance is obtained which then ranked accordingly. To validate the feasibility of this approach, evidences for sample document collection i. e. TREC-9 filtering track i. e. OSHUMED dataset are considered and the results are compared with traditional VSM model in terms of precision and recall measures. It is found that Dempster Shafer Model's performance is better than VSM for information retrieval.
References
- Salton, G. , Wong, A. , Yang, C. S. , "A vector space model for automatic indexing". Communications of the ACM. vol-18, 1975.
- Theophylactou M, Lalmas M. A , "Dempster-Shafer belief model for document retrieval using noun phrases", In: Proceeding of BCS Information Retrieval Colloquium. Grenoble, France, 1998 pp 213-228.
- Shi L, Nie J Y, Cao G. , "Relating dependent indexes using Dempster-Shafer theory", In: Proceedings of the 17th ACM Conference on Information and Knowledge Management. Napa Valley, California, USA, 2008: pp 429-438.
- Lalmas M, Moutoginni E. ,"A Dempster-Shafer indexing for the focused retrieval of a hierarchically structured document space: Implementation and experiments on a web museum collection", In: Proceedings of RIAO, 6th Conference on Content-Based Multimedia Information Access. College de France, France, 2000 pp 53-95.
- Shi C, Zhang J, Deng B. , "A new document retrieval model using Dempster-Shafer theory of evidence", In: Proceedings of the IEICE General Conference. Nanjing, China, 2008:pp 746-749.
- Jiuling Zhang, Beixing Deng, Xing Li,"Using the Dempster-Shafer Theory of Evidence to Rank Documents", IEEE computer science TSINGHUA SCIENCE AND TECHNOLOGY pp 241-247 Volume 17, Number 3, June 2012.
- Hazra Imran , Aditi Sharan, "A Framework for Efficient Document Ranking Using Order and Non Order Based Fitness Function", IMCES 2010,Hong Cong.
- Ian Ruthven and Mounia Lalmas, "Representing and retrieving structured documents using the Dempster-Shafer theory of evidence: modelling and evaluation", Journal of Documentation, Vol. 54 , pp. 529 – 565, 1998.
- Hatcher, Gospodnetic, McCandless, "Lucene in Action",second edition,Manning publication-2009.
- Stephen Robertson ,"Threshold setting and performance optimization in adaptive filtering ", Information Retrieval vol. 5, pp 239–256 (2002)
Index Terms
Keywords