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Information Retrieval Techniques based on Ontology for High Effectiveness
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 118 - Number 6 |
| Year of Publication: 2015 |
| Authors: Komal Shivaji Mule, Arti Waghmare |
10.5120/20748-3138
|
Komal Shivaji Mule, Arti Waghmare . Information Retrieval Techniques based on Ontology for High Effectiveness. International Journal of Computer Applications. 118, 6 ( May 2015), 8-11. DOI=10.5120/20748-3138
Abstract
Information Retrieving is task of recuperating information with high relevance, precision and recall. Basic methods for information retrieval include Boolean Retrieval, Fuzzy retrieval, Vector Space model. Searching depends on matching keywords between user-query and document. Ontology can be used in information retrieval. In software engineering and information science, ontology is a formal naming and meaning of the types, properties, and interrelationships of the elements that truly or in a broad sense exist for a specific domain of discourse. Ontology provides us with vocabulary of terms. New terms and relations could be found out using the existing relations. Many Information retrieval techniques exist amongst which many depend on keywords. Relations between keywords are considered here so as to get higher precision and recall.
References
- Rajeswari Mukesh, Sathish Kumar Penchala, and Anupama K. Ingale. Ontology Based Zone Indexing Using Information Retrieval Systems. S. Unnikrishnan, S. Surve, and D. Bhoir (Eds. ): ICAC3 2013, CCIS 361, pp. 181–186, 2013.
- TroelsAndreasen, HenrikBulskov. Conceptual querying through ontologies. 2009 Elsevier.
- Eduard Dragut, Fang Fang, Prasad Sistla, Clement Yu. Stop Word and Related Problems in Web Interface Integration. August 24-28, 2009.
- Saruladha, K. , Aghila, G. , Penchala, S. K. , "Design of New Indexing Techniques Based on Ontology for Information Retrieval Systems", In: Das, V. V. , Vijaykumar, R. (eds. ) ICT 2010. CCIS, vol. 101, pp. 287291. Springer, Heidelberg (2010)
- Fatima Ashraf, Tansel Ozyer, And Reda Alhajj,Associate Member, IEEE,"Employing Clustering Techniques For Automatic Information Extraction From Html Documents",IEEE Transactions On Systems, Man, And Cybernetics—Part C: Applications And Reviews, Vol. 38, No. 5, September 2008
- Yiyao Lu, Hai He, Hongkun Zhao, Weiyi Meng, Member, IEEE, and Clement Yu, Senior Member, IEEE,"Annotating Search Results from Web Databases", IEEE Transactions On Knowledge And Data Engineering, Vol. 25, No. 3, March 2013
- Jingtian Jiang, Xinying Song, Nenghai Yu, Member, IEEE, and Chin-Yew Lin, Member, IEEE, "FoCUS: Learning to Crawl Web Forums", IEEE Transactions On Knowledge And Data Engineering, Vol. 25, No. 6, June 2013
- Hai Dong, Member, IEEE, and Farookh Khadeer Hussain, "Self-Adaptive Semantic Focused Crawler for Mining Services Information Discovery", IEEE Transactions On Industrial Informatics, Vol. 10, No. 2, May 2014
- Dnyanesh G. Rajpathak, Member, IEEE and Satnam Singh, Senior Member, IEEE, "An Ontology-Based Text Mining Method to Develop D-Matrix from Unstructured Text", IEEE Transactions On Systems, Man, And Cybernetics: Systems, Vol. 44, No. 7, July 2014
- Jan Paralic, Ivan Kostial, "A Document Retrieval Method Based On Ontology Associations", Original Scientific Paper
- O. Dridi, RIADI Laboratory, National School of Computer Sciences, Tunisia, "Ontology-Based Information Retrieval :Overview and New Proposition"
- Jinwoo Kim, Dennis McLeod, "A 3-Tuple Information Retrieval Query Interface with Ontology Based Ranking", IEEE IRI 2012
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