Abstract
Social networking is becoming necessity of the current generation due to its usefulness in searching the user’s interest related people around the world, gathering information on different topics, and for many more purposes. In social network, there is abundant information available on different domains by means of variety of users but it is difficult to find the user preference based information.Also it is very much possible that relevant information is available in different forms at the end of other users connected in the same network. In this paper, we are proposing a computationally efficient rough set based method for ranking of the documents. The proposed method first expands the user query using WordNet and domain Ontologies and then retrieves documents containing relevant information. The distinctive point of the proposed algorithm is to give more emphasis on the concept combination based on concept presence and its position instead of term frequencies to retrieve relevant information. We have experimented over a set of standard questions collected from TREC, Wordbook, WorldFactBook and retrieved documents using Google and our proposed method. We observed significant improvement in the ranking of retrieved documents.
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Ray, S.K., Singh, S. (2009). Rough Set Based Social Networking Framework to Retrieve User-Centric Information. In: Sakai, H., Chakraborty, M.K., Hassanien, A.E., Ślęzak, D., Zhu, W. (eds) Rough Sets, Fuzzy Sets, Data Mining and Granular Computing. RSFDGrC 2009. Lecture Notes in Computer Science(), vol 5908. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10646-0_22
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DOI: https://doi.org/10.1007/978-3-642-10646-0_22
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