Discovering concept-level event associations from a text stream

Tao Ge, Lei Cui, Heng Ji, Baobao Chang, Zhifang Sui

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

We study an open text mining problem – discovering concept-level event associations from a text stream. We investigate the importance and challenge of this task and propose a novel solution by using event sequential patterns. The proposed approach can discover important event associations implicitly expressed. The discovered event associations are general and useful as knowledge for applications such as event prediction.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer-Verlag Berlin Heidelberg
Pages413-424
Number of pages12
DOIs
StatePublished - Dec 1 2016
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10102
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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