An Event Graph Model for Discovering Trends from Text Streams

Chengli Zhao; Xue Zhang; Dongyun Yi

6th International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems

Research Article

An Event Graph Model for Discovering Trends from Text Streams

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@INPROCEEDINGS{10.1007/978-3-642-32615-8_35,
    author={Chengli Zhao and Xue Zhang and Dongyun Yi},
    title={An Event Graph Model for Discovering Trends from Text Streams},
    proceedings={6th International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems},
    proceedings_a={BIOADCOM},
    year={2012},
    month={10},
    keywords={event graph trend text stream},
    doi={10.1007/978-3-642-32615-8_35}
}

Chengli Zhao
Xue Zhang
Dongyun Yi
Year: 2012
An Event Graph Model for Discovering Trends from Text Streams
BIOADCOM
Springer
DOI: 10.1007/978-3-642-32615-8_35

Chengli Zhao¹^,*, Xue Zhang¹^,*, Dongyun Yi¹^,*

1: National University of Defense Technology

*Contact email: chenglizhao@nudt.edu.cn, xuezhang@nudt.edu.cn, dongyunyi@nudt.edu.cn

Abstract

In this paper, we formally define and study the event graph model based on set theory and multi-relations theory, and discuss the methods of modeling event and event relations in detail. The event graph model is mainly designed to extract the potential events and the relationships between events from massive text streams, and further discover the trends embodied in the contents in text streams. We also study the connectivity of the event graph model, and give the equivalent conditions to determine the connectivity of event graph.

Keywords: event graph trend text stream

Published: 2012-10-18

: http://dx.doi.org/10.1007/978-3-642-32615-8_35

An Event Graph Model for Discovering Trends from Text Streams

Abstract

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