Queries describe the users' search intent and therefore they play an essential role in the context of ranking for information retrieval and Web search. However, most of exist...
In this paper, we propose a semi-supervised learning approach for classifying program (bot) generated web search traffic from that of genuine human users. The work is motivated by...
Hongwen Kang, Kuansan Wang, David Soukal, Fritz Be...
Abstract. This paper presents an architecture that enables the recognizer to learn incrementally and, thereby adapt to document image collections for performance improvement. We ar...
This Chapter presents the PASCAL1 Evaluating Predictive Uncertainty Challenge, introduces the contributed Chapters by the participants who obtained outstanding results, and provide...
Machine Learned Ranking approaches have shown successes in web search engines. With the increasing demands on developing effective ranking functions for different search domains, ...
Keke Chen, Rongqing Lu, C. K. Wong, Gordon Sun, La...