Web Information Extraction on Multiple Ontologies Based on Concept Relationships upon Training the User Profiles

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 325)

Abstract

There is a need of personalized Web information extraction. Mining vast information across the Web is not an easy task. We need to undergo various reduction techniques to remove unwanted data and to grab the useful information from the Web resources. Ontology is the best way for representing the useful information. In this paper, we have planned to develop a model based on multiple ontologies. From the constructed ontologies based on the mutual information among the concepts the taxonomy is constructed, then the relationship among the concepts is calculated. Thereby, the useful information is extracted. An algorithm is proposed for the same. The results show that the computation time for data extraction is reduced as the size of the database increases. This shows a healthy improvement for quick access of useful data from a huge information resource like the Internet.

Keywords

Information extraction Ontologies User profiles Concept similarity Ontological relationship Training the ontology 

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Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSathyabama UniversityChennaiIndia
  2. 2.Perunthalaivar Kamarajar Institute of Engineering and TechnologyKaraikalIndia

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