Content on the Internet is always changing. We explore the value of biasing search result snippets towards new webpage content. We present results from a user study comparing trad...
Krysta Marie Svore, Jaime Teevan, Susan T. Dumais,...
We develop a method for predicting query performance by computing the relative entropy between a query language model and the corresponding collection language model. The resultin...
We consider the task of suggesting related queries to users after they issue their initial query to a web search engine. We propose a machine learning approach to learn the probab...
In this paper, we address the problem of query formulation in the context of multi-domain integration of heterogeneous data on the Web. We argue that effectively tackling this pro...
A major cost in executing queries in a distributed database system is the data transfer cost incurred in transferring relations (fragments) accessed by a query from different sites...