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...
Evaluating text fragments for positive and negative subjective expressions and their strength can be important in applications such as single- or multi- document summarization, do...
We address the task of learning rankings of documents from search engine logs of user behavior. Previous work on this problem has relied on passively collected clickthrough data. ...
Traditional boosting algorithms for the ranking problems usually employ the pairwise approach and convert the document rating preference into a binary-value label, like RankBoost....
Chenguang Zhu, Weizhu Chen, Zeyuan Allen Zhu, Gang...
The problem of measuring "similarity" of objects arises in many applications, and many domain-specific measures have been developed, e.g., matching text across documents...