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In this paper, we have developed a probabilistic approach using PLSA for the discovery and analysis of contextual keyword relevance based on the distribution of keywords across a training text corpus. We have shown experimentally, the flexibility of this approach in classifying keywords into different domains based on their context. We have developed a prototype system that allows us to project keyword...
In this paper, we show that the efficiency of LSA is significantly controlled by the choice of weighting algorithm applied. These weighting algorithms allocate relative importance to the document attributes (e.g. keywords) based on their occurrences in the corpus. Effects of different weighting algorithms are the central point of this paper. We experimented with various weighting algorithms to evaluate...
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