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基于情感词汇的在线评论产品个性化推荐方法研究
引用本文:那日萨,钟佳丰,童强. 基于情感词汇的在线评论产品个性化推荐方法研究[J]. 郑州大学学报(理学版), 2011, 43(2): 48-51
作者姓名:那日萨  钟佳丰  童强
作者单位:大连理工大学,系统工程研究所,辽宁,大连,116024
基金项目:国家自然科学基金面上资助项目,编号61072128
摘    要:针对网络在线产品评论,利用Apriori算法从在线产品评论中挖掘出产品的热门属性,提取情感词汇并确定词汇和属性的搭配关系;对情感词汇进行模糊化表示,通过构建产品属性与推荐度的模糊推理规则,实现个性化产品推荐计算.以京东商城网站手机产品评论为例进行了实际计算,结果表明,该方法较传统的按销量排序方法更具个性化和针对性.

关 键 词:在线评论  产品推荐  情感计算  模糊推理

Research on Product Recommendation Based on Sentiment Words of Online Reviews
NA Ri-sa , ZHONG Ta-feng , TONG Qiang. Research on Product Recommendation Based on Sentiment Words of Online Reviews[J]. Journal of Zhengzhou University(Natrual Science Edition), 2011, 43(2): 48-51
Authors:NA Ri-sa    ZHONG Ta-feng    TONG Qiang
Affiliation:NA Ri-sa,ZHONG Jia-feng,TONG Qiang(Institute of Systems Engineering,Dalian University of Technology,Dalian 116024,China)
Abstract:A number of products attributes were exited from the online customer reviews about the products.These attributes could be extracted from the reviews using the Apriori algorithm.Through establishing fuzzy rules of the product attributes,the value of the personalized product recommendations could be calculated.Using the reviews of Jingdong online shop,the calculation result showed that our method was more personalized than traditional method.
Keywords:online review  product recommendation  sentiment calculation  fuzzy inference  
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