A hybrid training mechanism for applying neural networks to web-based applications

Ko Kang Chu, Maiga Chang, Yen Teh Hsia

    Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

    3 Citations (Scopus)

    Abstract

    This paper proposes a hybrid training neural network and applying it to the Accuracy Counter (AC) developed previously. The neural network is used for detecting the cheating model for abnormal browsing behaviors performed by users in the conflicting environment. The most significant issue, training, should be taken into consideration while we are applying the neural network to web-based applications such like the Accuracy Counter. Therefore, we design a hybrid web-based training mechanism for neural networks to deal with this kind of training problem. Finally, we also find out that the AC's block rate for detecting the abnormal browsing behaviors is increasing from 61% (rule-based) to 76% (neural networks with hybrid training mechanism) in the efficient and acceptable training period.

    Original languageEnglish
    Title of host publication2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
    Pages3543-3547
    Number of pages5
    DOIs
    Publication statusPublished - 2004
    Event2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004 - The Hague, Netherlands
    Duration: 10 Oct. 200413 Oct. 2004

    Publication series

    NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
    Volume4
    ISSN (Print)1062-922X

    Conference

    Conference2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
    Country/TerritoryNetherlands
    CityThe Hague
    Period10/10/0413/10/04

    Keywords

    • Neural network
    • Online training
    • Web counter

    Fingerprint

    Dive into the research topics of 'A hybrid training mechanism for applying neural networks to web-based applications'. Together they form a unique fingerprint.

    Cite this