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Exploring open information via event network†

Published online by Cambridge University Press:  26 October 2017

YANPING CHEN ,
QINGHUA ZHENG ,
FENG TIAN ,
HUAN LIU ,
YAZHOU HAO  and
NAZARAF SHAH
YANPING CHEN
Affiliation:
Guizhou Provincial Key Laboratory of Public Big Data, GuiZhou University, China e-mail: ypench@gmail.com Shaanxi Province Key Laboratory of Satellite and Terrestrial Network Technology, Xi’an Jiaotong University, China e-mail: qhzheng@mail.xjtu.edu.cn, hliuxjtu@gmail.com, yazhouhao@gmail.com
QINGHUA ZHENG
Affiliation:
Shaanxi Province Key Laboratory of Satellite and Terrestrial Network Technology, Xi’an Jiaotong University, China e-mail: qhzheng@mail.xjtu.edu.cn, hliuxjtu@gmail.com, yazhouhao@gmail.com
FENG TIAN
Affiliation:
National Engineering Lab of Big Data Analytics, Xi’an Jiaotong University, China e-mail: fengtian@mail.xjtu.edu.cn
HUAN LIU
Affiliation:
Shaanxi Province Key Laboratory of Satellite and Terrestrial Network Technology, Xi’an Jiaotong University, China e-mail: qhzheng@mail.xjtu.edu.cn, hliuxjtu@gmail.com, yazhouhao@gmail.com
YAZHOU HAO
Affiliation:
Shaanxi Province Key Laboratory of Satellite and Terrestrial Network Technology, Xi’an Jiaotong University, China e-mail: qhzheng@mail.xjtu.edu.cn, hliuxjtu@gmail.com, yazhouhao@gmail.com
NAZARAF SHAH
Affiliation:
The Faculty of Engineering and Computing, Coventry University, UK e-mail: aa0699@coventry.ac.uk
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Abstract

It is a challenging task to discover information from a large amount of data in an open domain.1 In this paper, an event network framework is proposed to address this challenge. It is in fact an empirical construct for exploring open information, composed of three steps: document event detection, event network construction and event network analysis. First, documents are clustered into document events for reducing the impact of noisy and heterogeneous resources. Secondly, linguistic units (e.g., named entities or entity relations) are extracted from each document event and combined into an event network, which enables content-oriented retrieval. Then, in the final step, techniques such as social network or complex network can be applied to analyze the event network for exploring open information. In the implementation section, we provide examples of exploring open information via event network.

Type
Articles
Information
Natural Language Engineering , Volume 24 , Issue 2 , March 2018 , pp. 199 - 220
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

†

This research is supported in part by the National Science Foundation of China under grant numbers 201721002, 61462011, 61540050 and 61472315; The Fundamental Theory and Applications of Big Data with Knowledge Engineering under the National Key Research and Development Program of China with grant number 2016YFB1000903, Project of China Knowledge Centre for Engineering Science and Technology, and the Ministry of Education Innovation Research Team no. IRT13035. The Open project no. 2017BDKFJJ018; the Major Applied Basic Research Program of Guizhou Province no. JZ20142001. Introduce Talents Science Projects of Guizhou University no. 201650.

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