Ontology-Based Terrorism Event Extraction

Uraiwan Inyaem, Phayung Meesad, Choochart Haruechaiyasak, Dat Tran

    Research output: A Conference proceeding or a Chapter in BookConference contribution

    1 Citation (Scopus)

    Abstract

    The proliferations of terrorism news articles from thousands of different sources are now available on the Web. Summarization of such information is becoming increasingly important. The aim of this paper is to study and compare the linguistic feature methods that are appropriate for use in terrorism event extraction systems. The event extraction has a main function to named entity recognition and segments the terrorism events from news articles to display to the users. The research methodology in the paper compares many linguistic features techniques including the terrorism gazetteer, the terrorism ontology and terrorism grammar rule. The annotated entities are summarized into the three desired template events. The terrorism events are classified by using similarity measure based on Term Frequency-Inverse Document Frequency called TF-IDF-based event segmentation. Additionally, we use a finite state algorithm to learn these feature weights and also studied to emphasize the performance of the event extraction algorithms. The experimental results show that the terrorism ontology linguistic feature selection yielded the best performance with 85.15% for both precision and recall.
    Original languageEnglish
    Title of host publication2009 First IEEE International Conference on Information Science and Engineering
    EditorsFeng Jiao
    Place of PublicationLos Alamitos, CA, USA
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages912-915
    Number of pages4
    Volume1
    ISBN (Print)9780769538877
    DOIs
    Publication statusPublished - 2009
    Event2009 First IEEE International Conference on Information Science and Engineering - Nanjing, China
    Duration: 18 Dec 200920 Dec 2009

    Conference

    Conference2009 First IEEE International Conference on Information Science and Engineering
    CountryChina
    CityNanjing
    Period18/12/0920/12/09

    Fingerprint

    Terrorism
    Ontology
    Linguistics
    Feature extraction

    Cite this

    Inyaem, U., Meesad, P., Haruechaiyasak, C., & Tran, D. (2009). Ontology-Based Terrorism Event Extraction. In F. Jiao (Ed.), 2009 First IEEE International Conference on Information Science and Engineering (Vol. 1, pp. 912-915). Los Alamitos, CA, USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICISE.2009.804
    Inyaem, Uraiwan ; Meesad, Phayung ; Haruechaiyasak, Choochart ; Tran, Dat. / Ontology-Based Terrorism Event Extraction. 2009 First IEEE International Conference on Information Science and Engineering. editor / Feng Jiao. Vol. 1 Los Alamitos, CA, USA : IEEE, Institute of Electrical and Electronics Engineers, 2009. pp. 912-915
    @inproceedings{2fe79cf6331b4981afc81e50b91bc8bc,
    title = "Ontology-Based Terrorism Event Extraction",
    abstract = "The proliferations of terrorism news articles from thousands of different sources are now available on the Web. Summarization of such information is becoming increasingly important. The aim of this paper is to study and compare the linguistic feature methods that are appropriate for use in terrorism event extraction systems. The event extraction has a main function to named entity recognition and segments the terrorism events from news articles to display to the users. The research methodology in the paper compares many linguistic features techniques including the terrorism gazetteer, the terrorism ontology and terrorism grammar rule. The annotated entities are summarized into the three desired template events. The terrorism events are classified by using similarity measure based on Term Frequency-Inverse Document Frequency called TF-IDF-based event segmentation. Additionally, we use a finite state algorithm to learn these feature weights and also studied to emphasize the performance of the event extraction algorithms. The experimental results show that the terrorism ontology linguistic feature selection yielded the best performance with 85.15{\%} for both precision and recall.",
    author = "Uraiwan Inyaem and Phayung Meesad and Choochart Haruechaiyasak and Dat Tran",
    year = "2009",
    doi = "10.1109/ICISE.2009.804",
    language = "English",
    isbn = "9780769538877",
    volume = "1",
    pages = "912--915",
    editor = "Feng Jiao",
    booktitle = "2009 First IEEE International Conference on Information Science and Engineering",
    publisher = "IEEE, Institute of Electrical and Electronics Engineers",
    address = "United States",

    }

    Inyaem, U, Meesad, P, Haruechaiyasak, C & Tran, D 2009, Ontology-Based Terrorism Event Extraction. in F Jiao (ed.), 2009 First IEEE International Conference on Information Science and Engineering. vol. 1, IEEE, Institute of Electrical and Electronics Engineers, Los Alamitos, CA, USA, pp. 912-915, 2009 First IEEE International Conference on Information Science and Engineering, Nanjing, China, 18/12/09. https://doi.org/10.1109/ICISE.2009.804

    Ontology-Based Terrorism Event Extraction. / Inyaem, Uraiwan; Meesad, Phayung; Haruechaiyasak, Choochart; Tran, Dat.

    2009 First IEEE International Conference on Information Science and Engineering. ed. / Feng Jiao. Vol. 1 Los Alamitos, CA, USA : IEEE, Institute of Electrical and Electronics Engineers, 2009. p. 912-915.

    Research output: A Conference proceeding or a Chapter in BookConference contribution

    TY - GEN

    T1 - Ontology-Based Terrorism Event Extraction

    AU - Inyaem, Uraiwan

    AU - Meesad, Phayung

    AU - Haruechaiyasak, Choochart

    AU - Tran, Dat

    PY - 2009

    Y1 - 2009

    N2 - The proliferations of terrorism news articles from thousands of different sources are now available on the Web. Summarization of such information is becoming increasingly important. The aim of this paper is to study and compare the linguistic feature methods that are appropriate for use in terrorism event extraction systems. The event extraction has a main function to named entity recognition and segments the terrorism events from news articles to display to the users. The research methodology in the paper compares many linguistic features techniques including the terrorism gazetteer, the terrorism ontology and terrorism grammar rule. The annotated entities are summarized into the three desired template events. The terrorism events are classified by using similarity measure based on Term Frequency-Inverse Document Frequency called TF-IDF-based event segmentation. Additionally, we use a finite state algorithm to learn these feature weights and also studied to emphasize the performance of the event extraction algorithms. The experimental results show that the terrorism ontology linguistic feature selection yielded the best performance with 85.15% for both precision and recall.

    AB - The proliferations of terrorism news articles from thousands of different sources are now available on the Web. Summarization of such information is becoming increasingly important. The aim of this paper is to study and compare the linguistic feature methods that are appropriate for use in terrorism event extraction systems. The event extraction has a main function to named entity recognition and segments the terrorism events from news articles to display to the users. The research methodology in the paper compares many linguistic features techniques including the terrorism gazetteer, the terrorism ontology and terrorism grammar rule. The annotated entities are summarized into the three desired template events. The terrorism events are classified by using similarity measure based on Term Frequency-Inverse Document Frequency called TF-IDF-based event segmentation. Additionally, we use a finite state algorithm to learn these feature weights and also studied to emphasize the performance of the event extraction algorithms. The experimental results show that the terrorism ontology linguistic feature selection yielded the best performance with 85.15% for both precision and recall.

    U2 - 10.1109/ICISE.2009.804

    DO - 10.1109/ICISE.2009.804

    M3 - Conference contribution

    SN - 9780769538877

    VL - 1

    SP - 912

    EP - 915

    BT - 2009 First IEEE International Conference on Information Science and Engineering

    A2 - Jiao, Feng

    PB - IEEE, Institute of Electrical and Electronics Engineers

    CY - Los Alamitos, CA, USA

    ER -

    Inyaem U, Meesad P, Haruechaiyasak C, Tran D. Ontology-Based Terrorism Event Extraction. In Jiao F, editor, 2009 First IEEE International Conference on Information Science and Engineering. Vol. 1. Los Alamitos, CA, USA: IEEE, Institute of Electrical and Electronics Engineers. 2009. p. 912-915 https://doi.org/10.1109/ICISE.2009.804