Abstract. Too much information kills information. This common statement applies to huge databases, where state of the art search engines may retrieve hundreds of very similar docum...
Yann Landrin-Schweitzer, Pierre Collet, Evelyne Lu...
In this paper, we propose a Bayesian learning approach to promoting diversity for information retrieval in biomedicine and a re-ranking model to improve retrieval performance in t...
In the interest of establishing robust benchmarks for search efficiency, we conducted a series of tests on symbolic databases of musical incipits and themes taken from several di...
Craig Stuart Sapp, Yi-Wen Liu, Eleanor Selfridge-F...
Search Engines today often return a large volume of results with possibly a few relevant results. The notion of relevance is subjective and depends on the user and the context of ...
Organizing Web search results into a hierarchy of topics and subtopics facilitates browsing the collection and locating results of interest. In this paper, we propose a new hierar...