Online offerings such as web search, news portals, and e-commerce applications face the challenge of providing high-quality service to a large, heterogeneous user base. Recent eff...
Abstract We present a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, which has been shown to be empiricall...
Qiang Wu, Christopher J. C. Burges, Krysta Marie S...
Contextual information provides an important basis for identifying and understanding users' information needs. Our previous work in traditional information retrieval systems ...
State-of-the-art Web search engines are inherently limited in their abilities to search information in Deep Web beyond portals. This paper discusses how Web services and Semantic-...
The current state of web search is most successful at directing users to appropriate web sites. Once at the site, the user has a choice of following hyperlinks or using site searc...
We describe a parser for robust and flexible interpretation of user utterances in a multi-modal system for web search in newspaper databases. Users can speak or type, and they can...
As the search engine arms-race continues, search engines are constantly looking for ways to improve the manner in which they respond to user queries. Given the vagueness of Web sea...
Jill Freyne, Barry Smyth, Maurice Coyle, Evelyn Ba...
Algorithms for clustering web search results have to be efficient and robust. Furthermore they must be able to cluster a dataset without using any kind of a priori information, s...
Steven Schockaert, Martine De Cock, Chris Cornelis...
We introduce a statistical model for abbreviation disambiguation in Web search, based on analysis of Web data resources, including anchor text, click log and query log. By combini...