We study a new task, proactive information retrieval by combining implicit relevance feedback and collaborative filtering. We have constructed a controlled experimental setting, ...
In contrast to traditional document retrieval, a web page as a whole is not a good information unit to search because it often contains multiple topics and a lot of irrelevant inf...
We consider the problem of learning to rank relevant and novel documents so as to directly maximize a performance metric called Expected Global Utility (EGU), which has several de...
Pseudo-relevance feedback (PRF) improves search quality by expanding the query using terms from high-ranking documents from an initial retrieval. Although PRF can often result in ...
Marc-Allen Cartright, James Allan, Victor Lavrenko...
We introduce GaZIR, a gaze-based interface for browsing and searching for images. The system computes on-line predictions of relevance of images based on implicit feedback, and wh...