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• W2337948133 abstract "Since its introduction into the NLP community, pointwise mutual information has proven to be a useful association measure in numerous natural language processing applications such as collocation extraction and word space models. In its original form, it is restricted to the analysis of two-way co-occurrences. NLP problems, however, need not be restricted to two-way co-occurrences; often, a particular problem can be more naturally tackled when formulated as a multi-way problem. In this paper, we explore two multivariate generalizations of pointwise mutual information, and explore their usefulness and nature in the extraction of subject verb object triples." @default.
• W2337948133 created "2016-06-24" @default.
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• W2337948133 date "2011-06-24" @default.
• W2337948133 modified "2023-09-23" @default.
• W2337948133 title "Two multivariate generalizations of pointwise mutual information" @default.
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