MATEC Web Conf.
Volume 100, 201713th Global Congress on Manufacturing and Management (GCMM 2016)
|Number of page(s)||7|
|Section||Part 2: Internet +, Big data and Flexible manufacturing|
|Published online||08 March 2017|
Event Relation Recognition by Multi Part of Speech Association Distribution Characteristics
Key Laboratory of Intelligent Information Processing, Kunming University of Science and Technology, Kunming, Yunnan, China
* Corresponding author: firstname.lastname@example.org
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.
Key words: Multi part of speech distribution / lexical chain / event relation
© The Authors, published by EDP Sciences, 2017
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