LSSVM-based social spam detection model
Xiaolei Yang, Yidan Su, JinPing Mo
Available Online April 2013.
- https://doi.org/10.2991/icsem.2013.2How to use a DOI?
- social spam, social bookmark system, lssvm , detection model
- 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.
- 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 SP - 7 EP - 12 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 -