Alternate Web Query Generation and Refined Search Results Using Query Expansion
Abstract
Abstract
The sole objective of an information retrieval (IR) task is to facilitate the user’s requests and filter the information which the user has actually intended. Therefore, the principle task of an IR system is to understand the user’s inability and act on behalf of the user’s point of view because most of the web users are novice, unaware of the topic pertaining in the selected domains etc. There has been a persistent gap elapsed between the user and the web data source. There are many primary assumptions underlying towards this shortcomings such as, (i) the relevance of a document is independent of the other documents in the accumulation, (ii) the usefulness of this document may depend on the number of relevant documents. But the large part of this problem is hanging in the kinds of information can the system make predictions. The prediction is entirely relying on the type of user information need and the available informative resources. Both these representations are problematic. The web information resources are diverse and heterogeneous (i.e., difference in terms of media, presence or absence of structure in the data, they can be aggregates or groups of informative resources). In this paper, we addressed the issue with expanding the user query through possible permutation combination and yield the suitable candidate query for fetching desired search results.
Keywords: Query expansion, semantic similarity, ontology, corpus, search engines
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