Abstract. In this paper we propose a supervised method for the segmentation of masses in mammographic images. The algorithm starts with a selected pixel inside the mass, which has ...
In this paper we have introduced a methodology to rank the available products in the Internet market. These rankings are based on the customers’ own preferences and also on the ...
In this paper we propose algorithms for combining and ranking answers from distributed heterogeneous data sources in the context of a multi-ontology Question Answering task. Our pr...
Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...
Nima Asadi, Donald Metzler, Tamer Elsayed, Jimmy L...
We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...