Measuring semantic relatedness with vector space models and random walks

Graph-based Methods for Natural Language Processing(2009)

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摘要
Both vector space models and graph random walk models can be used to determine similarity between concepts. Noting that vectors can be regarded as local views of a graph, we directly compare vector space models and graph random walk models on standard tasks of predicting human similarity ratings, concept categorization, and semantic priming, varying the size of the dataset from which vector space and graph are extracted.
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关键词
graph random walk model,human similarity rating,concept categorization,vector space model,vector space,standard task,semantic relatedness,semantic priming,local view
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