Authors: Junhui Yang; Zongtian Liu; Wei Liu
Addresses: School of Computer Engineering and Science, Shanghai University, Shanghai, 200072, China; School of Information Engineering, Jiangxi University of Science and Technology, Jiangxi, Ganzhou, 341000, China ' School of Computer Engineering and Science, Shanghai University, Shanghai, 200072, China ' School of Computer Engineering and Science, Shanghai University, Shanghai, 200072, China
Abstract: Aiming at the problem that the traditional event relation identification cannot be considered semantic relation of event structural characteristics; this paper proposes a method of semantic relation based on dependency and co-occurrences. Dividing the text into event representation, using the distribution characteristics of the event elements, the phenomenon of the co-occurrences elements and the dependence relation between the text events excavate clues of semantic relevant events. Then, clustering the event set with the related thread by the improved AP algorithm. Experiments show that the semantic role of the event (six elements) can be more accurate to calculate the degree of dependence and the co-occurrences overlap ratio of event elements between the candidate relation events which is helpful to the more abundant candidate related event set, so as to improve the recognition ability of the matter.
Keywords: event; event relation; event element; dependency; co-occurrence; AP algorithm.
International Journal of Intelligent Information and Database Systems, 2019 Vol.12 No.4, pp.335 - 349
Received: 24 Dec 2018
Accepted: 09 Apr 2019
Published online: 15 Jan 2020 *