Information needs are rarely satisfied directly on search engine result pages. Searchers usually need to click through to search results (landing pages) and follow search trails b...
The advent of Cloud computing platforms, and the growing pervasiveness of Multicore processor architectures have revealed the inadequateness of traditional programming models base...
This paper presents a user recommendation system that recommends to a user new friends having similar interests. We automatically discover users’ interests using Latent Dirichle...
In social bookmarking systems, existing methods in tag prediction have shown that the performance of prediction can be significantly improved by modeling users’ preferences. Ho...
This paper presents a system for enabling offline web use to satisfy the information needs of disconnected communities. We describe the design, implementation, evaluation, and pil...
Jay Chen, Russell Power, Lakshminarayanan Subraman...
We develop an approach for measuring the effectiveness of online display advertising at the campaign level. We present a Kalman filtering approach to deseasonalize and estimate ...
Joel Barajas, Ram Akella, Marius Holtan, Jaimie Kw...
We consider the problem of automatically extracting general lists from the web. Existing approaches are mostly dependent upon either the underlying HTML markup or the visual struc...
Fabio Fumarola, Tim Weninger, Rick Barber, Donato ...
Web provides rich information about a variety of objects. Trustability is a major concern on the web. Truth establishment is an important task so as to provide the right informati...
We describe a new method for query completion for Bollywood song search without using query logs. Since song titles in nonEnglish languages (Hindi in our case) are mostly present ...
We propose a method to adapt an existing relation extraction system to extract new relation types with minimum supervision. Our proposed method comprises two stages: learning a lo...