Anti-fraud system on the basis of data mining technologies

M. U. Sapozhnikova, A. V. Nikonov, A. M. Vulfin, M. M. Gayanova, K. V. Mironov, D. V. Kurennov

Результат исследований: Глава в книге, отчете, сборнике статейМатериалы конференцииНаучно-исследовательскаярецензирование

1 цитирование (Scopus)
Язык оригиналаАнглийский
Название основной публикации2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017
ИздательInstitute of Electrical and Electronics Engineers Inc.
Страницы243-248
Число страниц6
ISBN (электронное издание)9781538646625
DOI
СостояниеОпубликовано - 18 июн 2018
Событие17th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017 - Bilbao, Испания
Продолжительность: 17 дек 201719 дек 2017

Конференция

Конференция17th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017
СтранаИспания
ГородBilbao
Период17/12/201719/12/2017

Отпечаток

Data mining
Classifiers
Monitoring
Cluster analysis
Multilayer neural networks
Neural networks

Ключевые слова

    Предметные области ASJC Scopus

    • Safety, Risk, Reliability and Quality
    • Energy Engineering and Power Technology
    • Computer Networks and Communications
    • Computer Vision and Pattern Recognition
    • Hardware and Architecture
    • Signal Processing

    Предметные области WoS

    • Технологии, Электро и электронные
    • Телекоммуникации

    Цитировать

    Sapozhnikova, M. U., Nikonov, A. V., Vulfin, A. M., Gayanova, M. M., Mironov, K. V., & Kurennov, D. V. (2018). Anti-fraud system on the basis of data mining technologies. В 2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017 (стр. 243-248). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISSPIT.2017.8388649
    Sapozhnikova, M. U. ; Nikonov, A. V. ; Vulfin, A. M. ; Gayanova, M. M. ; Mironov, K. V. ; Kurennov, D. V. / Anti-fraud system on the basis of data mining technologies. 2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017. Institute of Electrical and Electronics Engineers Inc., 2018. стр. 243-248
    @inproceedings{a0b8f215bd724ddabb688845909f6d13,
    title = "Anti-fraud system on the basis of data mining technologies",
    keywords = "anti-fraud system, cluster analysis, Kohonen self-organazed map, neural network, random forest comeetee, support vector machine, user environment",
    author = "Sapozhnikova, {M. U.} and Nikonov, {A. V.} and Vulfin, {A. M.} and Gayanova, {M. M.} and Mironov, {K. V.} and Kurennov, {D. V.}",
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    Sapozhnikova, MU, Nikonov, AV, Vulfin, AM, Gayanova, MM, Mironov, KV & Kurennov, DV 2018, Anti-fraud system on the basis of data mining technologies. в 2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017. Institute of Electrical and Electronics Engineers Inc., стр. 243-248, 17th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017, Bilbao, Испания, 17/12/2017. https://doi.org/10.1109/ISSPIT.2017.8388649

    Anti-fraud system on the basis of data mining technologies. / Sapozhnikova, M. U.; Nikonov, A. V.; Vulfin, A. M.; Gayanova, M. M.; Mironov, K. V.; Kurennov, D. V.

    2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017. Institute of Electrical and Electronics Engineers Inc., 2018. стр. 243-248.

    Результат исследований: Глава в книге, отчете, сборнике статейМатериалы конференцииНаучно-исследовательскаярецензирование

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    AU - Gayanova, M. M.

    AU - Mironov, K. V.

    AU - Kurennov, D. V.

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    KW - Kohonen self-organazed map

    KW - neural network

    KW - random forest comeetee

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    Sapozhnikova MU, Nikonov AV, Vulfin AM, Gayanova MM, Mironov KV, Kurennov DV. Anti-fraud system on the basis of data mining technologies. В 2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017. Institute of Electrical and Electronics Engineers Inc. 2018. стр. 243-248 https://doi.org/10.1109/ISSPIT.2017.8388649