Paper Title
Query Based Document Ranking for Enhanced Information Retrieval

To improve the retrieval of documents, number of techniques have been proposed but most of them do not deal with contextual meaning of terms present in user’s query which can result in low precision and recall. Through this paper, the ranking of documents is improved using a hybrid technique in which user’s query is first reformulated by performing spell check using n-grams. Then the contextual meaning of the ambiguous terms (polysemy words) is identified using Word Net and the relevant terms are added to original user’s query. The similarity score is assigned to the extended query and KNN technique is applied to find the most relevant documents along-with their ranking. The experiments, conducted on data sets of ambiguous queries show that proposed approach outperforms other ranking methodologies by enhancing precision and recall.