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...
Users often try to accumulate information on a topic of interest from multiple information sources. In this case a user's informational need might be expressed in terms of an...
Web search engines are often presented with user queries that involve comparisons of real-world entities. Thus far, this interaction has typically been captured by users submittin...
In this paper we propose PARTfs which adopts a supervised machine learning algorithm, namely partial decision trees, as a method for feature subset selection. In particular, it is...
We present here a method for automatically projecting structural information across translations, including canonical citation structure (such as chapters and sections), speaker i...