LSSVM-based social spam detection model

DOI

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of the 2nd International Conference On Systems Engineering and Modeling (ICSEM 2013)
PB  - Atlantis Press
SP  - 7
EP  - 12
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.2
DO  - 10.2991/icsem.2013.2
ID  - Yang2013/04
ER  -