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Roth, Dan Wang, Ruichen 2016-03-02T19:45:16Z 2016-03-02T19:45:16Z 2015-12-10 2015-12 Event Coreference is an important module in the event extraction task, which has been shown to be difficult to solve. The goal is to link mentions talking about the same event together so that the information could be aggregated. This task could further be split into two slightly different subtasks: Within-Doc Event Coreference and Cross-Doc Event Coreference. Most of the related publications tried to solve the problem of Event Coreference in a two-step manner: Train or design a similarity metric for event mention pairs, then apply some clustering algorithm to the event mention space using the similarity metric as distance. In this work, we identify two major problems people have neglected: One is that coreference does not imply full event mention similarity due to the fact that event mentions tend to contain partial and even complementary information. The other problem is that the order to compare event mentions pair could be important, because instead of comparing event mentions pairs that have incomplete and trustless information, comparing those who have complete and trustworthy information first could prune the error rate. We propose Core Similarity, a new argument-based similarity metric, to solve the first problem, and two information-based clustering algorithms for the second problem - Informative-First Clustering (IFC) for within-doc situation and Topic-Side Event Clustering (TSEC) for cross-doc situation. These clustering algorithms are based on the idea of Event Information which is defined in this work. Finally, the EVCO system is delivered with all of these details implemented. Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-03-02 without embargo terms The student, Ruichen Wang, accepted the attached license on 2015-12-10 at 15:50. The student, Ruichen Wang, submitted this Thesis for approval on 2015-12-10 at 16:00. This Thesis was approved for publication on 2015-12-10 at 16:12. DSpace SAF Submission Ingestion Package generated from Vireo submission #9004 on 2016-03-02 at 12:53:12 Made available in DSpace on 2016-03-02T19:45:16Z (GMT). No. of bitstreams: 2 WANG-THESIS-2015.pdf: 857321 bytes, checksum: 3c92619b30274fdfd33d159820ee9308 (MD5) LICENSE.txt: 4209 bytes, checksum: cf30a54678037ca2177da9baaa4482be (MD5) Previous issue date: 2015-12-10 application/pdf http://hdl.handle.net/2142/89094 en Copyright 2015 by Ruichen Wang Event Coreference Easy-First Clustering Event Argument Information-based Event Coreference text text Computer Science Computer Science University of Illinois at Urbana-Champaign Thesis M.S.