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Effective E-Learning Recommender System Using Query Expansion Technique in Information Retrieval

Anitha.V, Ravichandran. M

In an information retrieval system users cannot accurately give their queries for retrieving a particular context. So the term mismatch problem occurs (i.e.) a user query for Information Retrieval applications do not contain the appropriate terms as actually intended by the user. The fundamental issue in the Information Retrieval System is term mismatch or word mismatch problem, as we already know that the effective way to handle the problem is query expansion technique. Query expansion adds related term to original query, which provides more information about the user needs. This paper implements a well-known Global Query Expansion tool namely WORDNET for expanding the query in any given Information Retrieval systems. Global Query Expansion comprises of Similarity thesaurus and Statistical thesaurus. This paper includes similarity thesaurus. Global similarity thesaurus has to be computed only once and can be updated incrementally. Also this paper incorporates a representation model named bag-of-words which makes this technique effective, simple and convenient. This paper calculates the similarity values, so that the result will be improved in its accuracy and performance. The result shows flexible and simple execution by reducing the run-time computational overhead.