Accident prevention system based on semantic network

Jian Xiong Yang, Junzo Watada

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    As humans handle huge and dynamic information in their daily life, such information is structurally complex and ever growing. Nowadays, the most typical information should be the World Wide Web. It is a fertile knowledge sea which humans encounter in their life individually as well as in business. Therefore, Web mining is one of most important techniques. A new generation of web mining techniques is developed to analyze Web information by means of searching, recommending, surfing and visualizing the Web. A semantic network is one of new ways for web content mining which takes advantage for both of a fuzzy logical search and semantic analysis. The objective of this paper is to build an accident prevention system by means of the semantic network. The system is built from a number of ranking algorithms based on generality and novelty measures extracted from an accident database.

    Original languageEnglish
    Title of host publicationProceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
    Pages3738-3743
    Number of pages6
    Volume7
    DOIs
    Publication statusPublished - 2008
    Event7th International Conference on Machine Learning and Cybernetics, ICMLC - Kunming
    Duration: 2008 Jul 122008 Jul 15

    Other

    Other7th International Conference on Machine Learning and Cybernetics, ICMLC
    CityKunming
    Period08/7/1208/7/15

    Keywords

    • Semantic network
    • Web content mining
    • Web mining
    • Web search
    • Web structure mining
    • Web usage mining

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Human-Computer Interaction
    • Control and Systems Engineering

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  • Cite this

    Yang, J. X., & Watada, J. (2008). Accident prevention system based on semantic network. In Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC (Vol. 7, pp. 3738-3743). [4621055] https://doi.org/10.1109/ICMLC.2008.4621055