We introduce a new task-independent framework to model top-down overt visual attention based on graphical models for probabilistic inference and reasoning. We describe a Dynamic B...
Pseudo-relevance feedback is an effective technique for improving retrieval results. Traditional feedback algorithms use a whole feedback document as a unit to extract words for ...
Phoneme segmentation is a fundamental problem in many speech recognition and synthesis studies. Unsupervised phoneme segmentation assumes no knowledge on linguistic contents and a...
As the Web has evolved into a data-rich repository, with the standard “page view,” current search engines are becoming increasingly inadequate for a wide range of query tasks....
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...