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