Yu Hong

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Email: tianxianer@gmail.com

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PublicationsProjectsLifeDemo


2017

94.
Kai Wang, Yu Hong, Yingying Qiu, Jian Wang, Jianmin Yao, Guodong Zhou. Study on boundary detection of user's query intents . Journal of Shandong University( Natural Science ). 2016. Accepted
93.
Hao Liu, Yu Hong, Liang Yao, Le Liu, Jianmin Yao, Guodong Zhou. HITS-Based Optimization Method for Bilingual Corpus Mining. Journal of Chinese Information . 2016. Accepted
92.
Jian Tang, Yu Hong, Mengyi Liu, Jiashuo Zhang, Jianmin Yao Optimizing topic distributions of descriptions for image description translation. NLPCC. 2016. Accepted
92.
Jian Tang, Yu Hong, Mengyi Liu, Jiashuo Zhang, Jianmin Yao Optimizing topic distributions of descriptions for image description translation. NLPCC. 2016. Accepted
91.
Yang Xu, Huibin Ruan, Yu Hong. Stacked Learning for Implicit Discourse Relation Recognition. China Conference on Information Retrieval. 2016. Accepted
90.
Fenhong Zhu, Xiaozheng Dong, Rui Song, Yu Hong, Qiaoming Zhu. A Multiple Learning Model based Voting System for News Headline Classification. NLPCC. 2016. Accepted
89.
Wenxuan Zhou, Zengzhuang Xu, Yu Hong, Guodong Zhou. Researching on A Method of Topic Detection Based on Word Correlation Graph. Journal of Shanxi University. 2016. Accepted
88.
Mengyi Liu, Liang Yao, Yu Hong, Hao Liu, Jianmin Yao. Domain Adaptation of Reordering Model via Topic Information :Word Order in Translated Text across Domains Journal of Chinese Information. 2016. Accepted
87.
Mengyi Liu, Jian Tang, Yu Hong, Jianmin Yao. Terminlology Translation Error Identification and Correction. Chinese National Conference on Social Media Processing. 2016. Accepted
86.
Zengzhuang Xu, Rui Song, Bowei Zou, Yu Hong. Unsupervised Slot Filler Renement via Entity CommunityConstruction. NLPCC. 2016. Accepted
2016

85.
Liang Yao, Yu Hong, Hao Liu, Le Liu, Jianmin Yao. Translation model adaptation based on semantic distribution similarity. Journal of Shandong University( Natural Science ). 2016. Accepted
84.
Liang Yao, Yu Hong, Hao Liu, Le Liu, Jianmin Yao. Combining Translation and Language Models for Bilingual Data Selection . Journal of Chinese Information . 2016. Accepted
83.
Liang Yao, Mengyi Liu, Yu Hong, Hao Liu, Jianmin Yao. Topic Model Based Adaptation Data Selection for Domain-Specific Machine Translation. Chinese National Conference on Social Media Processing. 2016. Accepted
82.
Yu Hong, Liang Yao, Mengyi Liu, Tongtao Zhang, Wenxuan Zhou, Jianmin Yao, Heng Ji. 图像 - Image-Image Search for Comparable Corpora Construction. coling. 2016. Accepted
81.
Shanshan Zhu, Yu Hong, Siyuan Ding, Weirong Yan, Jianmin Yao, Qiaoming Zhu. Implicit Discourse Relation Classification Method Based on the Training Data Expansion. Journal of Chinese Information. 2016. Accepted
80.
Siyuan Ding, Yu Hong, Shanshan Zhu, Jianmin Yao, Qiaoming Zhu. Combining Event-Level and Cross-Event Semantic Information for Event-Oriented Relation Classification by SCNN. International Symposium on Natural Language Processing Based on Naturally Annotated Big Data China National Conference on Computational Linguistics. 2016. Accepted
79.
Weirong Yan, Yang Xu, Shanshan Zhu, Yu Hong, Jianming Yao, Qiaoming Zhu. A Survey to Discourse Relation Analyzing. Journal of Chinese Information . 2016. Accepted
78.
Kai Wang, Yingying Qiu, Yu Hong, Yu Hong, Yadong Chen, Jianming Yao, Qiaoming Zhu, Guodong Zhou. A Case Study on Active Learning for Event Extraction. Chinese National Conference on Social Media Processing. 2016. Accepted
77.
Yadong Chen, Yu Hong, Xiaobin Wang, Xuerong Yang, Jianmin Yao, Qiaoming Zhu. Combining Multiple Models and High-Confidence Dictionary for Event Nugget Detection. Acta Scientiarum Naturalium Universitatis Pekinensis. 2016. Accepted
76.
Liang Yao, Yu Hong, Hao Liu, Le Liu, Jianmin Yao. Translation model adaptation based on semantic distribution similarity. Journal of Shandong University( Natural Science ). 2016. Accepted
75.
Yu Hong, Tongtao Zhang,Tim O'Gorman, Sharone Horowit-Hendler, Heng Ji, Martha Palmer. Building a Cross-document Event-Event Relation Corpus. ACL. 2015. Accepted
2015

74.
Yu Hong, Shanshan Zhu, Siyuan Ding, Jianmin Yao, Qiaoming Zhu, Guodong Zhou. Implicit Discourse Relation Inference Based on the External Relation. Journal of Computer Research and Development. 2015. Accepted
73.
Yu Hong, Jian Wang, Kai Wang, Yangyang Kang, Fang Kong, Jianmin Yao, Zhu Qiaoming, Guodong Zhou. Satisfaction Prediction Oriented Quantitative Mouse Movement Analysis. Chinese Journal of Computers. 2015. Accepted
72.
Yadong Chen, Yu Hong, Xuerong Yang, Xiaobin Wang, Jianmin Yao, Qiaoming Zhu. Automatic target identification in frame semantic parsing. Journal of Shandong University( Natural Science ). 2015. Accepted
71.
Xuerong Yang, Yu Hong, Yadong Chen, Jianmin Yao, Qiaoming Zhu. An Overview of Event Relation Detection System. Journal of Chinese Information . 2015. Accepted
70.
Weirong Yan, Shanshan Zhu, Yu Hong, Jianmin Yao, Qiaoming Zhu. Implicit Discourse Relation Inference Based on Frame Semantics. Journal of Chinese Information . 2015. Accepted
69.
Jian Wang, Yu Hong, Kai Wang, Jianmin Yao, Qiaoming Zhu. Correlation Aanlysis between Social Network Content and Query Intention. International Conference on Asian Language Processing. 2015. Accepted
68.
Hao Liu, Yu Hong, Le Liu, Xing Wang, Jianmin Yao, Qiaoming Zhu. Identifying Domain-specific Bilingual Websites through Global Retrieval and Local Classification. Journal of Shanxi University. 2015. Accepted
67.
Shanshan Zhu, Yu Hong, Siyuan Ding, Jianmin Yao, Qiaoming Zhu. Implicit Discourse Relation Recognition for Imbalanced Data Journal of Chinese Information. 2015. Accepted
66.
Siyuan Ding, Yu Hong, Shanshan Zhu, Jianmin Yao, Qiaoming Zhu. Research of Event Relation Classification based on Tri-Training. Computer Engineering & Science. 2015. Accepted
65.
Chen Yadong, Yu Hong, Xiaobin Wang, Xuerong Yang, Jianmin Yao, Qiaoming Zhu. Event Extraction Optimization via Frame Semantic Knowledge. Journal of Chinese Information. 2015. Accepted
64.
Yu Hong, Xiaobin Wang , Yadong Chen, Jian Wang. Biography-Dependent Collaborative Entity Archiving for Slot Filling. EMNLP. 2015. Accepted
63.
Xuerong Yang, Bin Ma, Yu Hong, Jianmin Yao, Qiaoming Zhu. A Novel Method to Optimize Training Data for Translation Model Adaptation. IALP. 2015. Accepted
2014

62.
Qi Li, Heng Ji, Yu Hong, Sujian Li. Constructing Information Networks Using One Single Model. EMNLP. 2014. Accepted
61.
Xuerong Yang, Bin Ma, Yu Hong, Jianmin Yao, Qiaoming Zhu. A Survey of Linguistics Resource,Evaluation and the Research in Event Relation DetectionInteligent Computer and Applications. 2014. Accepted
60.
Yu Hong, Weirong Yan, Tingting Che, Jianmin Yao, Qiaoming Zhu, Guodong Zhou. Parallel Reasoning Mechanism: An Implicit Textual Relation Detection MethodJournal of Software. 2014. Accepted
59.
Weirong Yan, Yu Hong, Shanshan Zhu, Tingting Che, Jianmin Yao, Qiaoming Zhu. Method of implicit discourse relation detecting based on semantic scenarioJournal of Shandong University. 2014. Accepted
58.
Shanshan Zhu, Yu Hong, Siyuan Ding, Weirong Yan, Jianmin Yao, Qiaoming Zhu. Implicit Discourse Relation Classification Method Based on the Training Data ExpansionJournal of Chinese Information. 2014. Accepted
57.
Hao Liu, Yu Hong, Le Liu, Xing Wang, Jianmin Yao, Qiaoming Zhu. Identifying Domain-specific Bilingual Websites through Global Retrieval and Local ClassificationJournal of Shanxi University 2014. Accepted
56.
Xuerong Yang, Yu Hong, Yadong Chen, Xiaobin Wang, Jianmin Yao,Qiaoming Zhu. Detecting EVent Relation through Cross—Scenario InferenceJournal of Chinese Information. 2014. Accepted
55.
Yu Hong, Shanshan Zhu, Weirong Yan, Jianmin Yao, Qiaoming Zhu,Guodong Zhou. ExpandingNativeTrainingDataForCCIS. 2014. Accepted
54.
Le Liu, Yu Hong, Hao Liu, Xin Wang, Jianmin Yao. An Iterative Link-based Method for Parallel Web Page MiningEMNLP. 2014. Accepted
2013

53.
Yu Hong, Yangyang Kang, Jianmin Yao, Guodong Zhou, Qiaoming Zhu. Discovery and Illustration of Novel Optimal Retrieval ResultJournal of Computer. 2013. Accepted
52.
Xiaopei Zhou, Yu Hong, Tingting Che, Jianmin Yao, Qiaoming Zhu An Unsuper Approach to Inferring Implicit Discourse Relation Journal of Chinese Information. 2013. Accepted
51.
Xing Wang, Zhaopeng Tu, Jun Xie, Yajuan Lu, Jianmin Yao. Selection of Parallel Corpus Based on Classification Journal of Chinese Information. 2013. Accepted
50.
Bin Ma,Yu Hong,Xuerong Yang, Jianmin Yao, Qiaoming Zhu.. Using Event Dependency Cue Inference to Recognize Event Relation Acta Scientiarum Naturalium Universitatis Pekinensis (ASNUP) 2013. Accepted
49.
Bin Ma, Yu Hong, Jianfeng Zhang, Jianmin Yao, Qiaoming Zhu. A Thread-based Twostage Clustering Method of Microblog Topic Detection Journal of Chinese Information. 2013. Accepted
48.
Bin Ma, Yu Hong, Xuerong Yang, Jianmin Yao, Qiaoming Zhu. Event Relation Recognition by Event Term and Entity Inference Acta Scientiarum Naturalium Universitatis Pekinensis (ASNUP) 2013. Accepted
47.
Xuerong Yang,Yu Hong,Bin Ma, Jianmin Yao, Qiaoming Zhu. Event Relation Recognition by Event Term and Entity Inference . Journal of Chinese Information. 2013. Accepted
46.
Tingting Che,Yu Hong, Xiaopei Zhou,Weirong Yan, Jianmin Yao, Qiaoming Zhu. Predicting Implicit Discourse Relation Based on Functional Connective Journal of Chinese Information. 2013. Accepted
45.
Xing Wang,Zhaopeng Tu, Jun Xie, Yajuan Lu, Jianmin Yao. Selection of Parallel Corpus Based on Classification Journal of Chinese Information. 2013. Accepted
44.
Le liu,Jun LangYu Hong ,Jianmin Yao Le Liu, Jun Lang, Yu Hong, Jun Lu, Jianmin Yao. An Iterative Link-based Method for Parallel Web Pages Minging.International Conference on Pattern Recognition (ICPR). 2014. 已投出
43.
Yan Weirong, Hong Yu, Zhu Shanshan, Yao Jianmin, Zhu Qiaoming.Implicit Discourse Relation Inference Based on Frame Semantics. Chinese Journal of Computers, 2013, Accepted.
42.
洪宇, 车婷婷, 严为绒, 梁颖红, 姚建民, 朱巧明, 周国栋.基于平行推理机制的隐式篇章关系检测方法研究. 软件学报. 2013. 已录用
41.
Yang Xuerong, Hong Yu, Ma Bin, Yao Jianmin, Zhu Qiaoming.Using Event Term and Entity Inference to Recognize Event Relation. Journal of Chinese Information, 2013, Accepted.
40.
Yang Xuerong, Hong Yu, Chen Yadong, Hui Fang, Yao Jianmin,Zhu Qiaoming.An Overview of Event Relation Detection. Journal of Chinese Information, 2013, Accepted.
39.
Ma Bin,Hong Yu,Yang Xuerong, Yao Jianmin, Zhu Qiaoming.Using Cross-Entity Inference to Improve Event Extraction. Journal of Chinese Information, 2013, Accepted.
38.
Che Tingting,Hong Yu,Zhou Xiaopei,Yan Weirong,Yao Jianmin, Zhu Qiaoming. Predicting Implicit Discourse Relation Based on Functional Connective.Journal of Chinese Information. 2013, Accepted.
37.
Ma Bin, Hong Yu, Yang Xuerong, Yao Jianmin, Zhu Qiaoming.Using Inference Cues to Recognize Event Relation. Acta Scientiarum Naturalium Universitatis Pekinensis (ASNUP), 2013, Accepted.
36.
Zhou Xiaopei,Hong Yu, Che Tingting, Yao Jianmin,Zhu Qiaoming. An Unsupervised Approach to Inferring Implicit Discourse Relation. ,Journal of Chinese Information, 2013, 27(2),p17-25.
35.
Ma Bin, Hong Yu, Zhang Jianfeng, Yao Jianmin,Zhu Qiaoming. A Thread-based Two-stage Clustering Method of Microblog Topic Detection. Journal of Chinese Information, 2013,26(6), p121-128
34.
Wei Tang, Yu Hong, Yan-hui Feng, Jian-min Yao, Qiao-ming Zhu.A Novel Method for Parallel Resources Acquisition from Bilingual Web Page.Journal of Computational Information Systems, 2013, 9(6). p2175-2182.
33.
Ma Bin ,Hong Yu,Yang Xuerong,Yao Jianmin, Zhu Qiaoming.Using Event Dependency Cue Inference to Recognize Event Relation. Acta Scientiarum Naturalium Universitatis Pekinensis (ASNUP), 2013, 49(1):109-116.
32.
Hong Yu, Kang Yangyang, Yao Jianmin,Zhou Guodong Zhu Qiaoming.2011.Discovery and Illustration of Novel Optimal Retrieval Result. CCIR 2011 Meeting Paper. Chinese Journal of Computers. 2013,36(3),643-653.
2012

31.
Hong Yu, Cang Yu, Yao Jianmin, Zhou Guodong, Zhu Qiaoming. 2012. Descending Kernel Track of Static and Dynamic Topic Models in Topic Tracking. Journal of Software. 23(5): 1100-1119. [EI]
30.
Hong Yu, Lu Jun, Yao Jianmin, Zhu Qiaoming. 2012. What Reviews are Satisfactory: Novel Features for Automatic Helpfulness Voting. Sigir2012.
29.
Yu Hong,Xiaopei Zhou,Tingting Che,Jianmin Yao,Qiaoming Zhu,Guodong Zhou: Cross-Argument Inference for Implicit Discourse Relation Recognition.In Proceedings of the 21st ACM International Conference on Information and Knowledge Management(CIKM 2012),p295-304
28.
Wei Tang, Yu Hong, Yan-hui Feng, Jian-min Yao, Qiao-ming Zhu Simultaneous Product Attribute Name and Value Extraction with Adaptively Learnt Templates.The 2nd International Conference on Computer Science and Service System (CSSS 2012), p2021-2025
27.
Zhou Xiaopei,Hong Yu, Che Tingting, Yao Jianmin,Zhu Qiaoming. Implicit Discourse Relation Inference Based Parallel Arguments. Computer Applications and Software, 2012, 29(9), p57-61.
26.
Lu Jun,Hong Yu,Yao Jianmin,Zhu Qiaoming.Automatic Reviews Quality Evaluation Based on Global User Intent. Journal of Chinese Information,2012,26(5),p79-87
25.
Yangyang Kang, Yu Hong, Li Yu, Jianmin Yao, Qiaoming Zhu. Divided pretreatment to targets and intentions for query recommendation. NLP&CC2012,Springer CCIS 333, 199-212
2011

24.
Lu Yuqing,Hong Yu, Lu Jun, Yao Jianmin, Zhu Qiaoming. 2011.Context Dependent Word Error Detection and Correction. Journal of Chinese Information Processing. 25(1):85-90.
23.
Sun Changlong,Hong Yu, Ge Yundong, Yao Jianmin, Zhu Qiaoming. 2011.The Translation Mining of the Out of Vocabulary Based on Wikipedia. Journal of Computer Research and Development. 48(6):1067-1076.
22.
Lu Jun,Hong Yu, Yao Jianmin, Zhu Qiaoming. 2011.Automatic Product Review Value Assessment Based on Global User Intent. CCIR2011(recommended to Journal of Chinese Information Processing).
21.
Ma Bin,Hong Yu, Zhang Jianfeng, Yao Jianmin, Zhu Qiaoming. 2011.A Thread-based Two -stage Clustering Method of Microblog Content Topic Detection. CCIR2011(recommended to Journal of Chinese Information Processing).
20.
Feng Yanhui,Hong Yu, Tang Wei, Yao Jianmin, Zhu Qiaoming. 2011.Using HTML Tags to Improve Parallel Resources Extraction. IALP(2011), November, Penang, Malaysia, p255 – 259.
19.
Zhang Jianfeng, Xia Yunqing, Ma Bin, Yao Jianmin, andHong Yu. 2011.Thread Cleaning and Merging for Microblog Topic Detection. In the Proceedings of the 5th International Joint Conference on Natural Language Processing (IJCNLP2011), November, Chiang Mai, Thailand, p589-597.
18.
Hong Yu, Zhang Jianfeng, Ma Bin, Yao Jianmin, Zhou Guodong, and Zhu Qiaoming. 2011. Using Cross-Entity Inference to Improve Event Extraction. In the Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-HLT 2011), June, Portland, USA, p1127-1136.
17.
Hong Yu, Lu Jun, Yao Jianmin, and Zhu Qiaoming. 2011. Factual or Satisfactory: What Search Results Are Better? In the Proceedings of the 25th Pacific Asia Conference on Language Information and Computing (PACLIC 2011), December, Singapore, p110-119.
2010

16.
Hong Yu, Cai Qingqing, Hua Song, Yao Jianmin, and Zhu Qiaoming. 2010. Negative Feedback: The Forsaken Nature Available for Re-ranking. In the Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010), August, Beijing, China, p436-444.
15.
Yan Zhenxiang, Feng Yan-Hui,Hong Yu, Yao Jian-Min:Parallel Sentences Mining From The Web. 2010 JCIS, p1633-1641.
14.
Hua Song,Hong Yu, Zhang Jianfeng , Yao Jianmin, Zhu Qiaoming. 2010.Opposite Re-ranking Based on Relevant Subtopic dispelling. CCIR2010. p237-250
13.
Ge Yundong,Hong Yu, Yao Jianmin, and Zhu Qiaoming. 2010.Improving Web-Based OOV Translation Mining for Query Translation. In the Proceedings of the 6th Asia Information Retrieval Societies Conference (AIRS 2010), December, Taipei, Taiwan, p576–587.
12.
Feng Yanhui,Hong Yu, Yan Zhenxiang, Yao Jianmin, and Zhu Qiaoming. 2010.A Novel Method for Bilingual Web Page Acquisition from Search Engine Web Records. In the Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010), August, Beijing, China, p294-302.
11.
Zhang Jianfeng,Hong Yu, Yang Yuehui, Yao Jianmin, Zhu Qiaoming.A Grammar-based Unsupervised Method of Mining Volitive Words. IALP(2010).
10.
Zhang Jianfeng,Hong Yu, Ma Bin, Yao Jianmin, and Zhu Qiaoming. 2010.Chinese Volitive Words Mining. International Journal of Asian Language Processing (IJALP 2010), 20(4): 157-170.
2009

9.
Hong Yu, Zhang Yu, Liu Ting, Li Sheng. 2009. A Temporal Topic Model for New Event Detection. International Journal of Computer Processing of Languages (IJCPOL), 22(1): 1-32.
8.
Hong Yu, Zhang Yu, Liu Ting, Li Sheng. 2009. Incremental Novelty Learning in Adaptive Topic Tracking. International Journal on Asian Language Processing (IALP), 19(1): 13-32.
7.
Yan Zhenxiang, Feng Yan-Hui,Hong Yu, Yao Jian-Min:Parallel Resource Mining From Bilingual Web Pages,2009 CCIR, p513-524.
2008

6.
Hong Yu, Zhang Yu, Fan Jili, Liu Ting, Li Sheng. 2008. New Event Detection Based on Division Comparison of Subtopic. Chinese Journal of Computers. 31(4): 687-695. [EI]
5.
Hong Yu, Zhang Yu, Zheng Wei, Liu Ting, Li Sheng. 2008. Algorithm of Shielding Noises in Information Filtering Based on Distribution of Two-Dimension Similarity Relation. Journal of Software. 19(11): 2887-2898. [EI]
4.
Hong Yu, Zhang Yu, Fan Jili, Liu Ting, Li Sheng. 2008. Chinese Topic Link Detection Based on Semantic Domain Language Model. Journal of Software. 19(9): 2265-2275. [EI]
3.
Zheng Wei, Zhang Yu,Hong Yu, Fan Jili, Liu Ting.Topic Tracking Based on Keywords Dependency Profile. The 4th Asia Information Retrieval Symposium (AIRS). 2008: 129-140. [EI]
2007

2.
Hong Yu, Zhang Yu, Liu Ting, Li Sheng. 2007. Topic Detection and Tracking Review. Journal of Chinese Information Processing. 21(6): 71-87.
1.
Hong Yu, Zhang Yu, Liu Ting, Zheng Wei, Gong Cheng, Li Sheng. 2007. Learning Algorithm of Adaptive Information Filtering Based on Hierarchy Clustering. Journal of Chinese Information Processing. 21(3): 47-53.


1.
Grant: NSFC(Young Scientist), #61003152(Dr. Hong Yu)
Project Name: News topic detection on preference learning
Duration: 2011.01-2013.12
Research funding: 200K RMB
Abstract:   News topic detection, as an important subject in public opinion analysis, is of high value to the monitor, management and regulation of public opinion. Especially, news topic variant detection is of vital importance to the forecast of both abrupt and sensitive topics. At present, no previous work has done on the topic evolution detection and the study on topic evolution pattern using public opinion preference learning. The project will put emphasis on learning collaborative evolution pattern of news topic and preference, along with its machine learning strategy. It will also explore the real time detection of variant anchors, as well as the description rule for topic variant. The project can be divided into four aspects: topic modeling based on temporal event chain, opinion recognition based on volitive words, adaptive learning of collaborative evolution of topic, opinion and real-time topic variant detection. It focus on the structured modeling of dynamic topic integrating temporal attribute, preference evolution description using the strength levels of volitive words, as well as collaborative evolution modeling relying on strength of preference and abrupt event dependency. The project aims to implement the automatic monitor of collaborative evolution of preference and topic in public opinion, as well as effective recognition and forecast of topic variant.

2.
Grant: NSFC(Suzhou International Cooperation Projects), (Dr. Hong Yu)
Project Name: Research on event discourse relation detection in web public opinions
Duration: 2013.01-2016.12
Research funding: 800K RMB
Abstract:   Characters):As an important research task in the cross-field of information extraction and public opinion analysis, Event Discourse Relation Detection (abbr., EDRD) has high practical value in extracting logical relations for nature languages that specially represent events, and mining occurrence cues and development veins of public opinions by using relevant events. However, there are still few researches focusing on the event relation detection, and especially it is still a blank field to use discourse analysis to thoroughly explain and describe the event relation at the semantic level. For this, the project focuses on researching the linguistic regularities of event relation, and based on the discourse analysis, exploring the methods of machine learning and automatically detecting event discourse relation. The research content can be divided into the following four parts: the first is cross-entity inference based event extraction, the second is dynamic topic modeling for cross-discourse relevant event identification, the third is parallel theory based event discourse relation detection, and the last is hierarchical scope establishing for event discourse relation. Especially the project will research the method of identifying shallow event relation under the restriction of global topics, and the mathematical modeling method of detecting event logistical relation based on parallelization identification of event semantics, when given the general characteristics of languages in the process of parallel events forming discourse relations. On the basis, the project finally aims to automatically identify and detect kinds of event logical relations in public opinions, by which to support the prediction of event occurrence and evolution.

3.
Grant: NSFC, (Dr. Hong Yu)
Project Name: Fundamental Theories and Key Technologies on Pseudo Event Relation Detection
Duration: 2014.01-2017.12
Research funding: 800K RMB
Abstract:   Pseudo event relation is a kind of relation which diverges or even deviates from objective laws, generating in the knowledge architecture triggered by subjective thinking and spreading in the procedure of information description and transmission with language as carrier. It includes three characteristics: confusing, ambiguous and illogical relationship. Correspondingly, pseudo event relation detection is an important subject in the cross-domain of natural language understanding and social opinion analysis, having a high research value in resolving the semantics and pragmatics of language description for event relation as well as discerning truth on the relation within social opinion. Current research on the fundamental theories of pseudo event relation has not started yet and corresponding technologies for detecting such event relation has no presence. For this, we build a framework for pseudo event relation detection on the basis of discourse relation understanding with focus on the characteristics of such pseudo event relations, under which, we study various tasks such as relevant event identification, relation cue mining, confusing event relation detection, ambiguous relation detection and illogical relation detection. Especially, we focus on exploring the key techniques on multiple cues fusion based confusing event relation detection, argument-focus co-reference based ambiguous event relation detection, and illogical event relation detection under the restriction of global event network, by which to implement an automatic scheme of identifying and detecting pseudo event relation in social opinion.