Efficient Method of Retrieving Digital Library Search Results using Clustering and Time Based Ranking

摘要

Digital libraries are emerging as a significant source for serving the queries of researchers for relevant documents. With the growing digital content and the user's needs, the complexity of ranking mechanism utilized in digital libraries is increasing. Ranking plays an important role in digital libraries as it makes the user's search for scientific literature, research papers, or other academia based documents fruitful and avoids unnecessary navigation to find the desired content. Many ranking algorithms based on different parameters have already been proposed. The parameters like citations to a research paper, content of paper, impact factor of publication venue, age of the paper, bookmarks etc. are utilized for ranking the documents in the result list of the digital libraries. The existing ranking algorithms sometimes provide irrelevant results due to certain shortcomings, which indicate a scope for further improvement in ranking mechanism. In this paper an optimized ranking algorithm is proposed that carries out static as well as dynamic ranking to rank the documents in digital libraries. The proposed algorithm takes the link structure of the digital documents into consideration i.e. citations, bookmarks of the paper, paper age, user's feedback and clustering process for displaying efficient and relevant search result list. In this paper, an optimized approach is being proposed which provides sorted search result list in cluster foam against the user's query.