Abstract A large amount of research results show that events objectively exist in a lot of texts, having essential inherent connections between them and different event has different importance. The matrix of event influence factor is constructed to depict the associative strengths between events of text collection. Based on the matrix of event influence factor, a method of identifying important events from text collection is elaborated by using event influence relations. This method utilizes the special timed transition relations between events and synthetically considers both hubs and authorities of events to compute event importance, abbreviated to HARank (Hubs-Authorities Rank). The experimental results show that the proposed algorithm can achieve significantly better ranking results for events over the classical PageRank and Reverse PageRank algorithms.
ZHONG Zhao-Man,LIU Zong-Tian. A Method of Identifying Important Events from Text Collection Using Event Influence Relationship[J]. , 2010, 23(3): 307-313.
[1] Li Wenjie, Xu Mingli, Lu Qin, et al. Extractive Summarization Using Inter-and Intra-Event Relevance // Proc of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics. Sydney, Australia, 2006: 369-376 [2] vander Wende L, Banko M, Menezes A. Event-Centric Summary Generation // Proc of the Human Language Technology and North American Association for Computational Linguistics Conference. Edmonton, Canada, 2003: 127-132 [3] Chang J. Event Structure and Argument Linking in Chinese. Language and Linguistics, 2003, 4(2): 317-351 [4] Li Zhiwei, Wang Bin, Li Mingjing, et al. A Probabilistic Model for Retrospective News Event Detection // Proc of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Salvador, Brazil, 2005: 106-113 [5] Yang Hui, Chua T S, Wang Shuguang, et al. Structured Use of External Knowledge for Event-Based Open Domain Question Answering // Proc of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Toronto, Canada, 2003: 33-40 [6] Yu Manquan, Luo Weihua, Xu Hongbo, et al. Research on Hierarchical Topic Detection in Topic Detection and Tracking. Journal of Computer Research and Development, 2006, 43(3): 489-495 (in Chinese) (于满泉,骆卫华,许洪波,等.话题识别与跟踪中的层次化话题识别技术研究.计算机研究与发展, 2006, 43(3): 489-495) [7] Wu Pingbo, Chen Qunxiu, Ma Liang. Study on Intelligent Retrieval of Event Relevant Documents Based on Event Frame. Journal of Chinese Information Processing. 2003, 17(6): 25-30 (in Chinese) (吴平博,陈群秀,马 亮.基于事件框架的事件相关文档的智能检索研究.中文信息学报, 2003, 17(6): 25-30) [8] Filatova E, Hatzivassiloglou V. Domain-Independent Detection, Extraction, and Labeling of Atomic Events // Proc of the 4th International Conference on Recent Advances in Nature Language Processing. Borovetz, Bulgaria, 2003: 145-152
[9] Zhou Wen, Liu Zongtian. Event-Based Knowledge Acquisition for Ontology Learning // Proc of the 6th IEEE International Conference on Cognitive Information. Lake Tahoe, USA, 2007: 498-501 [10] Gan Honghua, Pan Yunhe. A New Analysis of the Structure of Event Causation. Pattern Recognition and Artificial Intelligence, 2003, 16(1): 56-62 (in Chinese) (干红华,潘云鹤.一种基于事件的因果关系的结构分析方法.模式识别与人工智能, 2003, 16(1): 56-62) [11] Zhong Zhaoman, Liu Zongtian, Zhou Wen, et al. The Model of Event Relation Representation. Journal of Chinese Information Processing, 2009, 23(6): 56-60 (in Chinese) (仲兆满,刘宗田,周 文,等.事件关系表示模型.中文信息学报, 2009, 23(6): 56-60) [12] Liu Zongtian, Huang Meili, Zhou Wen, et al. Research on Event-Oriented Ontology Model. Computer Science, 2009, 36(11): 189-192 (in Chinese) (刘宗田,黄美丽,周 文,等.面向事件的本体研究.计算机科学, 2009, 36(11): 189-192) [13] Nie Zaiqing, Zhang Yuanzhi, Wen Jirong, et al. Object-Level Ranking: Bringing Order to Web Objects // Proc of the 14th International Conference on World Wide Web. Chiba, Japan, 2005: 567-574 [14] Ding Li, Pan Rang, Finin T, et al. Finding and Ranking Knowledge on the Semantic Web // Proc of the International Semantic Web Conference. Galway, Ireland, 2005: 156-170 [15] Fogaras D. Where to Start Browsing the Web // Proc of the International Workshop on Innovative Internet Community Systems. Leipzig, Germany, 2003: 65-79 [16] Wu Gang, Zhang Kuo, Li Juanzi, et al. Ranking by Mutually Reinforcing Concepts and Relations in Ontology. Chinese Journal of Computers, 2007, 30(9): 1490-1499 (in Chinese) (吴 刚,张 阔,李涓子,等.利用相互增强关系迭代计算本体中概念与关系的重要性.计算机学报, 2007, 30(9): 1490-1499) [17] Kleinberg J M. Authoritative Sources in a Hyperlinked Environment. Journal of ACM, 1999, 46(5): 604-632 [18] Zhi Huilai, Liu Zongtian. Event Importance Analysis Based on Directed Graph // Proc of the International Symposium on Intelligent Information Technology Application Workshops. Shanghai, China, 2008: 451-454 [19] Chen X. Why Did John Herschel Fail to Understand Polarization? The Differences between Object and Event Concepts. Studies in History and Philosophy of Science: Part A, 2003, 34(3): 491-513 [20] Pan Yunhe, Geng Weidong, He Zhimin. An Introduction to Intelligent-Computing Oriented Memory Theory. Journal of Computer Research and Development, 1994, 31(12): 37-42 (in Chinese) (潘云鹤,耿卫东,何志明.面向智能计算的记忆结构理论综述.计算机研究与发展, 1994, 31(12): 37-42)
2010, Vol. 23 
