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Non-negative matrix factorization is an important method helpful in the analysis of high dimensional datasets. It has a number of applications including pattern recognition, data clustering, information retrieval or computer security. One its significant drawback lies in its computational complexity. In this paper, we introduce a new method allowing fast approximate transformation from input space...
The extraction of temporal information from text documents is becoming increasingly important in many applications such as natural language processing, information retrieval, question answering, etc. Indeed, the temporal dimension plays a key role on most of these systems, promoting better performance. Our goal is the definition of a temporal document representation, incorporating the time dimension...
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