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Itemset Mining Based Episode Profiling of Terrorist Attacks Using Weighted Ontology

  • Saurabh Ranjan SrivastavaEmail author
  • Yogesh Kumar Meena
  • Girdhari Singh
Conference paper
  • 61 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1141)

Abstract

体育赛事投注记录itemset mining is a prominent research problem of data mining domain. it is extensively utilized for knowledge discovery in domains dealing with multi-component records or itemsets. terrorism is a similar domain where every terrorist attack carries attack attributes such as location, target and attack type as components. treatment of terrorist attack episodes as itemsets can facilitate effective pattern analysis and forecast of future attack episodes. this paper introduces a novel approach of mapping three major attributes of terrorist attacks taken place in a region in a single weighted ontology. the weighted ontology is later employed to discover and forecast useful information about possible attack episodes in the future.

Keywords

Itemset mining Episode Ontology Weighted ontology Terrorism Terrorist attack 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  • Saurabh Ranjan Srivastava
    • 1
    Email author
  • Yogesh Kumar Meena
    • 1
  • Girdhari Singh
    • 1
  1. 1.Department of Computer Science & EngineeringMalviya National Institute of TechnologyJaipurIndia

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