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- W2593636700 abstract "Event relation recognition, as one of natural language processing technologies, faces information stream of texts detecting event relation. By analyzing the influence of the words of different parts of speech on the relevance of events. And use the form of lexical chain to extract and store the relevant vocabulary between events, this paper propose an event relation recognization method based on lexical chain to detect latent semantic relation between events: whether events hold logical relation or not. Cornpared with the method based on dependency cue inference, the proposed method achieves 7. 68% improvement." @default.
- W2593636700 created "2017-03-16" @default.
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- W2593636700 date "2017-01-01" @default.
- W2593636700 modified "2023-10-04" @default.
- W2593636700 title "Event Relation Recognition by Multi Part of Speech Association Distribution Characteristics" @default.
- W2593636700 cites W1965605789 @default.
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- W2593636700 doi "https://doi.org/10.1051/matecconf/201710002059" @default.
- W2593636700 hasPublicationYear "2017" @default.
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