Automated Document Ranking Evaluation in Digital Libraries

The construction of Automated Digital Libraries has grabbed widespread popularity over recent years, rendering the value added services that suit to the tailored user requirements. In this context, carrying out traditional searches over text material by querying upon a given metadata or a set of domain keywords is predominantly observe, not to retrieve the relevant documents, although these end up in huge list of results containing query terms. In the present communication, the search is deviated from explicitly borrowed Metadata search to the context oriented search triggered from implicitly available Ontologies of the considered subject domain. The proposal is hereby analyzed to be most fruitful for Relevant Information Retrieval by User Communities, i.e. by those group of people who share common interests and benefit by their own accessed information. It is further emphasized that the search terms contributing to the background knowledge, can be implicitly made available from the collection of documents, which only need to be selectively defined, studying the User profiles of the search communities. The authors visualize this work as a tool to precisely rank the prescribed courseware material for Academic Digital Libraries.