Search result diversification using data envelopment analysis

How to resolve query ambiguity and how to avoid redundancies in a search result? The redundancy in returned results( e.g., near duplicates) has a negative effect on retrieval effectiveness(i.e., user satisfaction) and there is less benefit in representing relevant yet redundant results to the user repeatedly. So the ambiguity of query needs to be reflected in the returned results to account for the uncertainty on the user's information need. In a diversity context, the user is usually interested in retrieving various types of relevant documents (the number of information needs) more than the ones which are at the top of the result list. In this paper, we present a new document re-ranking method for information retrieval using Data Envelopment Analysis (DEA) and Diversity Retrieval Measure (DRM). The goal of the proposed re-ranking system is to diversify the documents results from the original ranking list. The experimentation is performed on hundreds of random Decision Making Units (DMUs) and the consequence achieved is compared with the existing system. The result demonstrates that the new method satisfies the unspecified individuals when the query is ambiguous. It also shows that the diversifying method is effective to satisfy the user who wants to get many types of information.