Survey on Self Adaptive Semantic Focused Crawling Using Ontology Learning

  S.Bhargavi

The Internet today has become a vast storehouse for a scintillating amount of knowledge. It is an excellent source of information catering to the needs of people of varied interests. But this process of information retrieval does have its shortcomings too viz. heterogeneity, ubiquity and ambiguity. Thus a self-adaptive semantic focused crawler - SASF crawler that addresses these issues and optimises the process of information discovery and indexing of the searched information is proposed. This framework encompasses the concepts of semantic focused crawling and ontology learning that helps to maintain the performance of the crawler in spite of the variety in the Web environment. The innovation here is the unsupervised vocabulary-based ontology learning and a hybrid matching algorithm that matches semantically relevant concepts and metadata. Finally the performance of the crawler is evaluated based on various parameters.

Keywords- Ontology learning, Semantic focused crawling, Hybrid matching algorithm, SASF crawler, Information retrieval

Unique Identification Number - IJEDR1502141
Page Number(s) - 786-790
Pubished in - Volume 3 | Issue 2 | May 2015
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  S.Bhargavi,   "Survey on Self Adaptive Semantic Focused Crawling Using Ontology Learning", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.3, Issue 2, pp.786-790, May 2015, Available at :http://www.ijedr.org/papers/IJEDR1502141.pdf