摘要
受经济利益驱使,大量恶意用户发布包含不实内容的虚假评论以影响用户的购买决策,从而提高自身商品的销售业绩并打压竞争对手,严重扰乱电子商务运营秩序。为此,介绍虚假评论识别的研究成果,包括虚假评论内容、发布者及虚假评论者群组的识别,对识别过程所使用的特征及检测方法进行对比分析,并给出虚假评论识别效果的评价方式和指标。在此基础上,对未来虚假评论识别研究工作进行探讨和展望。
Driven by economic interests,a large number of malicious users publish false comments containing untrue content to influence users’purchasing decisions,thereby promoting the sale of their own products or suppressing competitors,seriously disrupting the order of e-commerce operations.Therefore,the paper introduces fake commodity reviews research result,including the identification of false reviews,publishers,and groups of fake reviewers,analyzes and compares the features and detection methods used,and gives the evaluation method and indicators of false comment recognition effect.On this basis,the future research on false comment recognition is discussed and prospected.
作者
张璐
ZHANG Lu(College of Information Engineering,Nanjing University of Finance and Economics,Nanjing 210046,China)
出处
《计算机工程》
CAS
CSCD
北大核心
2019年第10期293-300,共8页
Computer Engineering
基金
国家重点研发计划(2018YFD0401404)
国家自然科学基金(71801123,91646204)
关键词
虚假评论
恶意用户
群组检测
机器学习
评价指标
fake review
malicious users
group detection
machine learning
evaluation indicator
