Most up-to-date well-behaved topic-based summarization systems are built upon the extractive framework. They score the sentences based on the associated features by manually assig...
In recent years, many algorithms for the Web have been developed that work with information units distinct from individual web pages. These include segments of web pages or aggreg...
Semantic Web data exhibits very skewed frequency distributions among terms. Efficient large-scale distributed reasoning methods should maintain load-balance in the face of such hi...
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Automatically extracting semantic content from audio streams can be helpful in many multimedia applications. Motivated by the known limitations of traditional supervised approache...