We propose a framework for “probabilistic functional testing.” The success of a test data set generated according to our method guarantees a certain level of confidence into ...
Understanding the impact of individual and task differences on search result page examination strategies is important in developing improved search engines. Characterizing these e...
Georg Buscher, Ryen W. White, Susan T. Dumais, Jef...
We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms u...
David Sontag, Kevyn Collins-Thompson, Paul N. Benn...
How can a search engine automatically provide the best and most appropriate title for a result URL (link-title) so that users will be persuaded to click on the URL? We consider th...
We study the problem of answering ambiguous web queries in a setting where there exists a taxonomy of information, and that both queries and documents may belong to more than one ...
Rakesh Agrawal, Sreenivas Gollapudi, Alan Halverso...