An Ontology-Based Learnable Focused Crawler using Hybrid Latent Semantic Indexing In Data Mining

Authors

  • Pravendra Kumar School of Information and Communication Technology, Gautam Buddha University, Greater Noida, India

DOI:

https://doi.org/10.37591/jowet.v2i2.430

Abstract

In this paper, we proposed an ontological model of an information system that provides precise definitions of fundamental concepts like Query, Sub-query, and Coupling. Queries are mapped to this space with documents being retrieved based on similarity model. In this Research, OLC (Ontological Semantic Indexing) Performance in document retrieval is investigated and compared with traditional term matching techniques with the help of LSI, LUD, CHOLSKEY Transform, Natural language processing to improve searching redundancy with stemming and start stopping words processing. After that, we have to apply for singular value decomposition; so as to gain the motivation for fetching records and information from document which would be same in the meaning and texture.

Keywords: Ontology Crawler, LSI, NLP, Cholskey Transform, SVM, LUD

Cite this Article

Kumar Pravendra and Solanki Arun. An Ontology-Based Learnable Focused Crawler Using Hybrid Latent Semantic Indexing in Data Mining. Journal of Web Engineering & Technology. 2015; 2(2): 11–17p.

References

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Published

2015-12-29

Issue

Vol. 2 No. 2 (2015)

Section

Research Articles

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