Efficient Computation of Co-occurrence Based Word Relatedness

Prior work on computing semantic relatedness of words focused on representing their meaning in isolation, effectively disregarding inter-word affinities. We propose a large-scale data mining approach to learning word-word relatedness, where known pairs ...

Word sense disambiguation (WSD) is a difficult problem in natural language processing. In this paper, a sememe co-occurrence frequency based WSD method was introduced. In this method, Hownet was used as our information source, and a co-occurrence ...

We address the question of how Bag-of-Words BoW models of text relatedness can be improved by using important words in the text-pair instead of all the words. To find important words in a text, we use a new approach based on word relatedness. We use two ...