The problem of combining the ranked preferences of many experts is an old and surprisingly deep problem that has gained renewed importance in many machine learning, data mining, a...
We study the problem of aggregating partial rankings. This problem is motivated by applications such as meta-searching and information retrieval, search engine spam fighting, e-c...
In this paper, we propose a new methodology based on directed weighted graphs and the TextRank algorithm to automatically induce general-specific noun relations from web corpora f...
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...
A crucial issue for Machine Learning and Data Mining is Feature Selection, selecting the relevant features in order to focus the learning search. A relaxed setting for Feature Sele...