Mining feedback information from user click-through data is an important issue for modern Web retrieval systems in terms of architecture analysis, performance evaluation and algor...
Rongwei Cen, Yiqun Liu, Min Zhang, Bo Zhou, Liyun ...
Evaluating user preferences of web search results is crucial for search engine development, deployment, and maintenance. We present a real-world study of modeling the behavior of ...
Eugene Agichtein, Eric Brill, Susan T. Dumais, Rob...
We consider the problem of learning to rank relevant and novel documents so as to directly maximize a performance metric called Expected Global Utility (EGU), which has several de...
Relevance feedback has been proposed as an important technique to boost the retrieval performance in content-based image retrieval (CBIR). However, since there exists a semantic g...