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Ontology-Based Profiling by Hierarchical Cluster Analysis for Forecasting on Patterns of Significant Events

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Proceedings of the International Conference on Intelligent Computing, Communication and Information Security (ICICCIS 2022)

Part of the book series: Algorithms for Intelligent Systems ((AIS))

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Abstract

Catastrophic events such as pandemics, terrorist attacks, and natural calamities impact our society drastically. The forecast of such significant events to reduce the potential damage is an imminent research challenge. However, most of the existing computational methods are limited to only addressing the forecasting needs of specific domains. A strong reason for this limitation is the rigid management of events data in different heterogeneous formats restricted only to a set of utilities. To overcome this restriction, efficient storage, as well as suitable preprocessing of events data, is critical for proficient forecasts. We initiate by proposing an event ontology for categorization of event features and assembling of events retrieved in divergent formats from various sources under a single comprehensive structure. We also generate profiles of events related to terrorist attacks, floods, and airplane crashes to validate the adaptability and inclusiveness of our approach. Utilization of these event profiles results into a forecast performance of 67–75% in outputs.

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Acknowledgements

The authors thank the editors and the anonymous reviewers for their helpful comments and suggestions. This work has been supported by the Science and Engineering Research Board (SERB) under Department of Science and Technology, Government of India, under the project 'Forecasting Significant Social Events by Predictive Analytics Over Streaming Open Source Data' (Project File Number: EEQ/2019/000697).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Malaviya National Institute of Technology, Jaipur, Jaipur, India

    Saurabh Ranjan Srivastava, Yogesh Kumar Meena & Girdhari Singh

Authors
  1. Saurabh Ranjan Srivastava
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  2. Yogesh Kumar Meena
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  3. Girdhari Singh
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Corresponding author

Correspondence to Saurabh Ranjan Srivastava .

Editor information

Editors and Affiliations

  1. Serbian Academy of Sciences and Arts, Belgrade, Serbia

    Vladan Devedzic

  2. Department of Computer Science and Engineering, Central University of Rajasthan, Ajmer, Rajasthan, India

    Basant Agarwal

  3. Department of Computer Science and Engineering, Swami Keshvanand Institute of Technology Management and Gramothan, Jaipur, Rajasthan, India

    Mukesh Kumar Gupta

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Srivastava, S.R., Meena, Y.K., Singh, G. (2023). Ontology-Based Profiling by Hierarchical Cluster Analysis for Forecasting on Patterns of Significant Events. In: Devedzic, V., Agarwal, B., Gupta, M.K. (eds) Proceedings of the International Conference on Intelligent Computing, Communication and Information Security. ICICCIS 2022. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-1373-2_5

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