The purpose of extractive document summarization is to automatically select a number of indicative sentences, passages, or paragraphs from the original document according to a tar...
Shih-Hsiang Lin, Yi-Ting Chen, Hsin-Min Wang, Bin ...
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 ...
We present a passage relevance model for integrating syntactic and semantic evidence of biomedical concepts and topics using a probabilistic graphical model. Component models of t...
The complexity of software systems makes design reuse a necessary task in the software development process. CASE tools can provide cognitive assistance in this task, helping the so...
We propose a new method for handwritten word-spotting which does not require prior training or gathering examples for querying. More precisely, a model is trained "on the fly...