Building text-based temporally linked event network for scientific big data analytics

被引：12
|
作者：
Zhang, Junsheng [1 ]
Yao, Changqing [1 ]
Sun, Yunchuan [2 ]
Fang, Zengquan [3 ]
机构：
[1] Inst Sci & Tech Informat China, Beijing 100038, Peoples R China
[2] Beijing Normal Univ, Sch Business, Beijing 100875, Peoples R China
[3] Beijing Normal Univ, Coll Journalism & Commun, Beijing 100875, Peoples R China
来源：
PERSONAL AND UBIQUITOUS COMPUTING | 2016年 / 20卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Event; Information analytics; Temporal information; Temporal relation reasoning; Big data; INFORMATION EXTRACTION; INTERNET;
D O I：
10.1007/s00779-016-0940-x
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Events formulate the world of the human being and could be regarded as the semantic units in different granularities for information organization. Extracting events and temporal information from texts plays an important role for information analytics in big data because of the wide use of multilingual texts. This paper surveys existing research work on text-based event temporal resolution and reasoning including identification of events, temporal information resolutions of events in English and Chinese texts, the rule-based temporal relation reasoning between events and relevant temporal representations. For the scientific big data analytics, we point out the shortcomings of existing research work and give the argument about the future research work for advancing identification of events, establishment of temporal relations and reasoning of temporal relations.
引用
收藏
页码：743 / 755
页数：13
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