Implicit relevance feedback (IRF) is the process by which a search system unobtrusively gathers evidence on searcher interests from their interaction with the system. IRF is a new...
We formulate and study search algorithms that consider a user’s prior interactions with a wide variety of content to personalize that user’s current Web search. Rather than re...
The paper presents a study on large-scale automatic extraction of acronyms and associated expansions from Web data and from the user interactions with this data through Web search...
Understanding how people interact with search engines is important in improving search quality. Web search engines typically analyze queries and clicked results, but these actions...
Traditional information systems return answers after a user submits a complete query. Users often feel "left in the dark" when they have limited knowledge about the unde...