The week's pick
Random Articles
Reseach Article
Context based Indexing in Search Engines using Ontology
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 1 - Number 14 |
| Year of Publication: 2010 |
| Authors: Parul Gupta, A.K. Sharma |
10.5120/302-468
|
Parul Gupta, A.K. Sharma . Context based Indexing in Search Engines using Ontology. International Journal of Computer Applications. 1, 14 ( February 2010), 49-52. DOI=10.5120/302-468
Abstract
Indexing in search engines has been an active area of current researches. The main aim of search engines is to provide most relevant documents to the users in minimum possible time. So granting efficient and fast accesses to the index is a major issue for performances of Web Search Engines. Indexing is performed on the web pages after they have been gathered into a repository by the crawler. The existing architecture of search engine shows that the index is built on the basis of the terms of the document and consists of an array of the posting lists where each posting list is associated with a term and contains the term as well as the identifiers of the documents containing the term. The current information retrieval systems use terms to describe documents and search engines. This paper proposes an indexing structure in which index is built on the basis of context of the document rather than on the terms basis using ontology. The ontology-based collection selection method presented in this paper uses context to describe collections and search engines. The context of the documents being collected by the crawler in the repository is being extracted by the indexer using the context repository, thesaurus and ontology repository and then documents are indexed according to their respective context.
References
- Parul Gupta, Dr. A.K. Sharma, A framework for multilevel Indexing in Search Engines, accepted in International Journal of Applied Engineering Research..
- Fabrizio Silvestri, Raffaele Perego and Salvatore Orlando. Assigning Document Identifiers to Enhance Compressibility of Web Search Engines Indexes. In the proceedings of SAC, 2004.
- S.Brin and L.Page.The Anatomy of a Large-Scale Hypertextual Web Search Engine. In the 7th International WWW Conference, (WWW7), pp. 107-117, Brisbane, Australia.
- Van Rijsbergen C.J. Information Retrieval. Butterworth 1979.
- Soumen Chakrabarti. Mining the Web Discovering Knowledge from Hypertext Data. Morgan Kaufmann Publications, 2003.
- Oren Zamir and Oren Etzioni. Web Document Clustering: A feasibility demonstration. In the proceedings of SIGIR, 1998.
- A. Jain and R. Dubes. Algorithms for Clustering Data. Prentice Hall, 1988
- Berners-Lee, T., Hendler, J. and Lassila, O., “The Semantic Web,” Scientific American.284(5):35-43, 2001.
- O. Zamir, O. Etzioni, O. Madanim, and R.M. Karp, “Fast andIntuitive Clustering of Web Documents,” Proc. Third Int’l Conf. Knowledge Discovery and Data Mining, pp. 287-290, Aug. 1997.
- Wang Jicheng, Huang Yuan, Wu Gangshan and Zhang Fuyan, ‘Web Mining: Knowledge Discovery on the Web’ ,IEEE (1999).
- Frawley, W., Piatetsky-Shapiro, G., and Matheus, C., Knowledge Discovery in Databases: An Overview. Ai Magazine, Vol. 13 (1992), pp.57-70.
- Changshang Zhou, Wei Ding, Na Yang, Double Indexing Mechanism of Search Engine based on Campus Net, Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (APSCC'06)
- Quan, T. T., Hui, S. C., Fong, A. C. M., and Cao, T. H. (2004). Automatic generation of ontology for scholarly semantic Web. In: Lecture Notes in Computer Science. Vol. 3298. (pp. 726–740).
Index Terms
Keywords