ICTACT Journal on Soft Computing

S. K. Jayanthi ¹, S. Prema ²

Affiliations
1 Department of Computer Science, Vellalar College for Women, IN
2 Department of Computer Science, K.S.R College of Arts and Science, IN

Abstract

In the current scenario, web page result personalization is playing a vital role. Nearly 80 % of the users expect the best results in the first page itself without having any persistence to browse longer in URL mode. This research work focuses on two main themes: Semantic web search through online and Domain based search through offline. The first part is to find an effective method which allows grouping similar results together using BookShelf Data Structure and organizing the various clusters. The second one is focused on the academic domain based search through offline. This paper focuses on finding documents which are similar and how Vector space can be used to solve it. So more weightage is given for the principles and working methodology of similarity propagation. Cosine similarity measure is used for finding the relevancy among the documents.

Keywords

Semantic Web, BookShelf Data Structure, Similarity Propagation, Cosine Similarity measure, Vector Space Model.

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S. K. Jayanthi ¹, S. Prema ²

Affiliations
1 Department of Computer Science, Vellalar College for Women, IN
2 Department of Computer Science, K.S.R College of Arts and Science, IN

Abstract

Search engines are playing a vital role in retrieving relevant information for the web user. In this research work a user profile based web search is proposed. So the web user from different domain may receive different set of results. The main challenging work is to provide relevant results at the right level of reading difficulty. Estimating user expertise and re-ranking the results are the main aspects of this paper. The retrieved results are arranged in Bookshelf Data Structure for easy access. Better presentation of search results hence increases the usability of web search engines significantly in visual mode.

Keywords

Web Search Personalization, Bookshelf Data Structure, Agglomerative Hierarchical Clustering, Similarity Measure, Visualization.

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