Event cube – A conceptual framework for event modeling and analysis

Qing Li, Yun Ma, Zhenguo Yang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

The publicly available data such as the massive and dynamically updated news and social media data streams (a.k.a. big data) covers the various aspects of social activities, personal views and expressions, which points to the importance of understanding and discovering the knowledge patterns underlying the big data, and the need of developing methodologies and techniques to discover real-world events from such big data, to manage and to analyze the discovered events in an effective and elegant way. In this paper we present an event cube (EC) model which is devised to support various queries and analysis tasks of events; such events include those discovered by techniques of untargeted event detection (UED) and targeted event detection (TED) from multi-sourced data. Specifically, based on the essential event elements of 5W1H (i.e., When, Where, Who, What, Why, and How), the EC model is developed to organize the discovered events from multiple dimensions, to operate on the events at various levels of granularity, so as to facilitate analyzing and mining hidden/inherent relationships among the events effectively. Case studies are provided to illustrate the usages and show the benefits of EC facilities in on-line analytical processing of events and their relationships.

Original languageEnglish
Title of host publicationWeb Information Systems Engineering – WISE 2017 - 18th International Conference, Proceedings
EditorsLu Chen, Athman Bouguettaya, Andrey Klimenko, Fedor Dzerzhinskiy, Stanislav V. Klimenko, Xiangliang Zhang, Qing Li, Yunjun Gao, Weijia Jia
PublisherSpringer-Verlag
Pages499-515
Number of pages17
ISBN (Print)9783319687827
DOIs
Publication statusPublished - 1 Jan 2017
Externally publishedYes
Event18th International Conference on Web Information Systems Engineering, WISE 2017 - Puschino, Russian Federation
Duration: 7 Oct 201711 Oct 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10569 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Web Information Systems Engineering, WISE 2017
CountryRussian Federation
CityPuschino
Period7/10/1711/10/17

Keywords

  • Event cube
  • Event modeling
  • Event relationship analysis
  • On-line analytical processing

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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