IDEAS home Printed from https://ideas.repec.org/a/igg/jirr00/v5y2015i3p1-18.html
   My bibliography  Save this article

Extracting Entities of Emergent Events from Social Streams Based on a Data-Cluster Slicing Approach for Ontology Engineering

Author

Listed:
  • Chung-Hong Lee

    (Department of Electrical Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan)

  • Chih-Hung Wu

    (Department of Electrical Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan)

Abstract

In this paper, we describe our work on developing a model and method for extracting key entities from the online social messages regarding emergent events for enhancing ontology engineering, enabling a sensible solution for prevention of similar disasters. Our work started with the development of an event modelling system using a data-cluster slicing approach, which combines analytics of social data and event lifecycle algorithms, allowing for large-scale emerging novel events to be quickly and accurately analyzed. Subsequently, our system computes the energy of each collected event data sets, and then encapsulates ranked temporal, spatial and topical keywords into a structured node for event-entity extraction, in order to update event ontologies for fast response of emergent events. The preliminary experimental results demonstrate that our developed system is workable, allowing for prediction of possible evolution and early warning of critical incidents with a support of dynamic entity extraction.

Suggested Citation

  • Chung-Hong Lee & Chih-Hung Wu, 2015. "Extracting Entities of Emergent Events from Social Streams Based on a Data-Cluster Slicing Approach for Ontology Engineering," International Journal of Information Retrieval Research (IJIRR), IGI Global, vol. 5(3), pages 1-18, July.
    • Handle: RePEc:igg:jirr00:v:5:y:2015:i:3:p:1-18
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJIRR.2015070101
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jirr00:v:5:y:2015:i:3:p:1-18. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.