We examine the problem of retrieving the top-m ranked items from a large collection, randomly distributed across an n-node system. In order to retrieve the top m overall, we must ...
We have empirically compared two classes of technologies capable of locating potentially malevolent online content: 1) popular keyword searching, currently widely used by law enfo...
We propose a semantic passage segmentation method for a Question Answering (QA) system. We define a semantic passage as sentences grouped by semantic coherence, determined by the...
This work presents a general rank-learning framework for passage ranking within Question Answering (QA) systems using linguistic and semantic features. The framework enables query...
Matthew W. Bilotti, Jonathan L. Elsas, Jaime G. Ca...
This paper describes a Question Answering system which retrieves answers from structured data regarding cinemas and movies. The system represents the first prototype of a multilin...
Bogdan Sacaleanu, Constantin Orasan, Christian Spu...