›› 2012, Vol. 27 ›› Issue (3): 591-598.doi: 10.1007/s11390-012-1246-8

• Special Issue on Social Network Mining • Previous Articles     Next Articles

Personalized Semantic Based Blog Retrieval

Godfrey Winster Sathianesan and Swamynathan Sankaranarayanan   

  1. Department of Information Science and Technology, College of Engineering Campus, Anna University Chennai 600 025, Tamil Nadu, India
  • Received:2011-09-01 Revised:2012-01-10 Online:2012-05-05 Published:2012-05-05
  • About author:Godfrey Winster Sathiane-san is currently a research scholar in Department of Information Scie-nce and Technology, College of En-gineering Campus, Anna University, Chennai, India. He received his B.E. degree in computer science and en-gineering from University of Madras in 2002 and Master's degree in com-puter science and engineering from Sathyabama University in 2006. His research interest in-cludes web mining, Semantic web and social networking.

Blog retrieval is a complex task because of the informal language usage. Blogs deviate from the language which is used in traditional corpora largely due to various reasons. Spelling errors, grammatical irregularity, over use of abbreviations and symbolic characters like emotions are a few reasons of irregular corpus blogs. To make the retrieval of blogs easier, the novel idea of personalized semantic based blog retrieval (PSBBR) system is discussed in this paper. The blogs are tagged with a relationship to one another with reference to ontology. The meanings of the blog content and key term are tagged as XML tags. The query term accesses the XML tags to retrieve entire blog content. The system is evaluated with a huge number of blogs extracted from various blog sources. Relevance score is calculated for every blog associated with keywords and content-based importance (CBI) gives the content similarity to the query word. The experimental result shows the system performs well for the blog retrieval process.

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