The week's pick
Random Articles
Reseach Article
OntDR: An Ontology-based Augmented Method for Document Retrieval
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 53 - Number 17 |
| Year of Publication: 2012 |
| Authors: Poonam Yadav, R. P. Singh |
10.5120/8511-2182
|
Poonam Yadav, R. P. Singh . OntDR: An Ontology-based Augmented Method for Document Retrieval. International Journal of Computer Applications. 53, 17 ( September 2012), 7-13. DOI=10.5120/8511-2182
Abstract
The document retrieval is one of the fast growing and complex research area in the field of information retrieval. An effective Information retrieval can be obtained only under strong document retrieval algorithm. As compared to the information retrieval, document retrieval is also a tedious process. The accurate retrieval of a document needs highly precise and mathematically vibrant methods. A number of researches have been targeted for the document retrieval, which yielded expected result within their boundaries. In this paper, we proposed an ontology-based augmented method for document retrieval. The ontology defined in our proposed approach gives extra freedom to choose between the documents and thus give an accurate retrieval of the documents. The mutual association (MA) value specifies the interrelated documents in the problem space. The array index values, which we provide, give accurate distinction between each document. The results and analysis of our proposed method showed expected results and a comparative analysis was subjected for analyzing the proposed method with an existing algorithm. The F-measure comparison showed the performance improvement of the proposed method with respect to the existing method.
References
- R. Meersman and Z. Tari, "Ontology Learning for Search Applications", International transactions from Springer, pp. 1050-1062, 2007.
- Jan Paralic and Ivan Kostial, "Ontology-based Information Retrieval", Information and Intelligent System, Croatia, pp. 23-28, 2003.
- Eelco Mossel, "Crosslingual Ontology-Based Document Retrieval", In Proceedings of the RANLP 2007 workshop of Natural Language Processing and Knowledge Representation for eLearning Environments, Borovets, Bulgaria, 2007.
- D. Vallet, M. Fernández and P. Castells. "An Ontology Based Information Retrieval Model. " In Proceedings of the 2nd European Semantic Web Conference on the Semantic Web Research and Applications, pp. 455-470, 2005.
- L. Lemnitzer, P. Monachesi, K. Simov, A. Killing, D. Evans and C. Vertan. "Improving the search for learning objects with keywords and ontologies" In Proceedings of the Second European Conference on Technology Enhanced Learning, Crete, Greece, 2007.
- Pablo Castells, Miriam Fernández, David Vallet, Phivos Mylonas and Yannis Avrithis, "Self-Tuning Personalized Information Retrieval in an Ontology-Based Framework", In Proceedings of the International Workshop on Web Semantics, pp. 977-986, 2005.
- Xing Jiang and Ah-Hwee Tan, "OntoSearch: A Full-Text Search Engine for the Semantic Web", In Proceedings of the 21st National Conference on Artificial Intelligence, 2006.
- Khan L, McLeod D, and Hovy E, "Retrieval effectiveness of an ontology-based model for information selection", The VLDB Journal, pp. 71–85, 2004.
- Contreras J, Benjamins V R, Bl´azquez M, Losada S, Salla R, Sevilla J, Navarro D, Casillas J, Mompo A, Paton D, Corcho O, Tena P, and Martos I, "A semantic portal for the International Affairs sector", In EKAW Springer, Berlin, pp. 203–215, 2004.
- Shao Fen Liang, Paul Smart, Alistair Russell and Nigel Shadbolt, "Using Windmill Expansion for Document Retrieval", The Open Information Systems Journal, Vol. 3, pp. 1-8, 2009.
- Dolf Trieschnigg, Piotr Pezik, Vivian Lee, Franciska de Jong, Wessel Kraaij and Dietrich Rebholz-Schuhmann, "MeSH Up: Effective MeSH Text Classification for Improved Document Retrieval", Bioinformatics, vol. 25, no. 11, pp. 1412-1418, 2009.
- Rong Zhao and Grosky W. I, " Narrowing the semantic gap - improved text-based web document retrieval using visual features", IEEE Transactions on Multimedia, Vol. 4 , No. 2, pp. 189 – 200, 2002.
- Annekathrin Bartsch, Boyke Bunk, Isam Haddad, Johannes Klein, Richard Münch, Thorsten Johl , Uwe Kärst, Lothar Jänsch, Dieter Jahn and Ida Retter, "Gene-Reporter—sequence-based document retrieval and annotation", Bioinformatics, 2009.
- A. S. Siva Sathya and B. Philomina Simon, "A Document Retrieval System with Combination Terms Using Genetic Algorithm", IJCEE, Vol. 2, No. 1, pp. 1-6, 2010.
- Jayapal R and J. K. Mendiratt, "Document Image Retrieval: An Overview", International Journal of Computer Applications, Vol. 1, No. 7, pp. 114–119, 2010.
- V. A. Narayana, P. Premchand and A. Govardhan, "Effective Detection of Near Duplicate Web Documents in Web Crawling", International Journal of Computational Intelligence Research, Vol. 5, No. 1, pp. 83–96, 2009.
- Anton Karl Ingason, Sigrun Helgadottir, Hrafn Loftsson and Eirikur Rognvaldsson, "A Mixed Method Lemmatization Algorithm Using a Hierarchy of Linguistic Identities (HOLI)", Advances in Natural Language Processing-Lecture Notes in Computer Science, Vol. 5221, pp. 205-216, 2008.
- Lovins, J. B. "Development of a stemming algorithm". Mechanical Translation and Computational Linguistics, Vol. 11, pp. 22-31, 1968.
- Raymond Y. K. Lau, Dawei Song, Yuefeng Li, Terence C. H. Cheung, and Jin-Xing Hao, "Toward a Fuzzy Domain Ontology Extraction Method for Adaptive e-Learning", IEEE Transactions On Knowledge And Data Engineering, Vol. 21, No. 6, pp. 800-813, 2009
- Christos Faloutsos and Douglas W. Oard, "A survey of information retrieval and filtering methods", Technical Report on A survey of information retrieval and filtering methods, pp. 1-24, 1995.
- Analia Lourenço, Rafael Carreira, Daniel Glez-Pena, Jose R. Méndez, Sonia Carneiro, Luis M. Rocha, Fernando Diaz, Eugénio C. Ferreira, Isabel Rocha, Florentino Fdez-Riverola, Miguel Rocha, " BioDR: Semantic indexing networks for Biomedical Document Retrieval", Expert Systems with Applications, Vol 37, no. 4, pp: 3444-3453, 2010.
Index Terms
Keywords