计算机工程 ›› 2018, Vol. 44 ›› Issue (9): 159-163,170.doi: 10.19678/j.issn.1000-3428.0048993

• 人工智能及识别技术 • 上一篇    下一篇

基于隐空间代价敏感学习的微博水军识别方法

王磊,任航,王之怡   

  1. 西南财经大学 经济信息工程学院,成都 610074
  • 收稿日期:2017-10-17 出版日期:2018-09-15 发布日期:2018-09-15
  • 作者简介:王磊(1978—),男,副教授、博士,主研方向为机器学习、数据挖掘;任航,硕士研究生;王之怡,副教授、博士。
  • 基金项目:

    中央高校基本科研业务费重大理论基础研究项目(JBK151127);中央高校基本科研业务费创新团队项目(JBK130503,JBK150503);教育部人文社会科学研究西部和边疆地区项目(16XJAZH002)。

Microblog Spammer Identification Method Based on Cost-sensitive Learning in Latent Space

WANG Lei,REN Hang,WANG Zhiyi   

  1. School of Economic Information Engineering,Southwestern University of Finance and Economics,Chengdu 610074,China
  • Received:2017-10-17 Online:2018-09-15 Published:2018-09-15

摘要:

根据微博水军活动的特点,提出一种基于隐空间代价敏感学习的半监督水军识别方法。从内容、行为、社交关系3个视角选取微博账户的22个特征,结合矩阵隐空间分解、代价敏感学习和社交关系正则技术,构造代价敏感的半监督最大间隔分类模型,并利用随机梯度 下降算法求解模型的线性复杂度。实验结果表明,该方法在准确率、召回率和F1指标上均优于SMFSR和L2-SVMs方法,并且具有接近线性的学习速度。

关键词: 水军识别, 矩阵分解, 代价敏感学习, 社交关系正则, 隐空间

Abstract:

According to the characteristics of microblog spammers,this paper proposes a semi-supervised spammer identification method based on cost-sensitive learning in latent space.Firstly,it selects twenty-two features of microblog account from perspectives of contents,activities and social relations.Then,it obtains latent account vectors using matrix factorization method and constructs a novel cost-sensitive semi-supervised classification model with the maximum margin theory in latent space.In addition,a social relation regularization from following behaviors is formulated on the model.Finally,it develops a linear-complexity algorithm for solving the model with the stochastic gradient descent method.Experimental results show that the proposed method outperforms existing methods significantly,such as SMFSR and L2-SVMS,in terms of the evaluation measures of accuracy,recall and F1 score.It also obtains nearly linear training speeds.

Key words: spammer identification, matrix factorization, cost-sensitive learning, social relation regularization, latent space

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