2nd International Conference On Systems Engineering and Modeling (ICSEM-13)

LSSVM-based social spam detection model

Authors
Xiaolei Yang, Yidan Su, JinPing Mo
Corresponding Author
Xiaolei Yang
Available Online April 2013.
DOI
https://doi.org/10.2991/icsem.2013.2How to use a DOI?
Keywords
social spam, social bookmark system, lssvm , detection model
Abstract
To Resolve the garbage tag issue in Folksonomy, Lssvm algorithm for social spam detection model (least Squares support vector machine classifiers) was proposed. The method of inequality change the constraints in the traditional support vector machine into equality constraints, and take the empirical function of the squared error loss function as the Experience function in training set. so that the quadratic programming problem convert QP into solving linear equations, it was improving solution the speed of solution and accuracy of convergence.The experimental results show that we have got higher classification accuracyand less predict time than traditional svm detection methods based on least squares support vector machine algorithm garbage tag detection model.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
2nd International Conference On Systems Engineering and Modeling (ICSEM-13)
Part of series
Advances in Intelligent Systems Research
Publication Date
April 2013
ISBN
978-94-91216-42-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/icsem.2013.2How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Xiaolei Yang
AU  - Yidan Su
AU  - JinPing Mo
PY  - 2013/04
DA  - 2013/04
TI  - LSSVM-based social spam detection model
BT  - 2nd International Conference On Systems Engineering and Modeling (ICSEM-13)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.2
DO  - https://doi.org/10.2991/icsem.2013.2
ID  - Yang2013/04
ER  -