We study the problem of learning to rank images for image retrieval. For a noisy set of images indexed or tagged by the same keyword, we learn a ranking model from some training e...
We present a non-traditional retrieval problem we call subtopic retrieval. The subtopic retrieval problem is concerned with finding documents that cover many different subtopics ...
ChengXiang Zhai, William W. Cohen, John D. Laffert...
Abstract. We propose a novel active learning strategy based on the compression framework of [9] for label ranking functions which, given an input instance, predict a total order ov...
In view of the need to provide tools to facilitate the reuse of existing knowledge structures such as ontologies, we present in this paper a system, AKTiveRank, for the ranking of...
Since the publication of Brin and Page's paper on PageRank, many in the Web community have depended on PageRank for the static (query-independent) ordering of Web pages. We s...