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数据分析与知识发现  2017, Vol. 1 Issue (9): 28-39     https://doi.org/10.11925/infotech.2096-3467.2017.09.03
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
基于标签的商品推荐模型研究*
涂海丽1(), 唐晓波2
1东华理工大学经济与管理学院 南昌 330013
2武汉大学信息管理学院 武汉 430072
Building Product Recommendation Model Based on Tags
Tu Haili1(), Tang Xiaobo2
1School of Economics and Management, East China University of Technology, Nanchang 330013, China
2School of Information Management, Wuhan University, Wuhan 430072, China
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摘要 

目的】构建社会化电子商务环境下基于标签的个性化商品推荐模型。【方法】综合考虑用户使用标签的频率和时间因素计算用户的兴趣偏好; 基于标签层次特征和电子商务网站中关于商品特征的检索条件, 构建某一主题商务社区中商品本体; 利用本体规范化用户标签语义, 并对商品进行分类; 寻找含有用户偏好的类簇, 计算该类簇中商品与用户偏好商品的相似度, 将用户未标注过的商品与用户偏好相似度高的商品推荐给用户。【结果】从翻东西网站上随机选取200个活跃用户关于热门商品的标注信息进行分析, 验证该模型的有效性。【局限】在计算用户兴趣偏好时, 只考虑用户使用标签的频率和时间因素, 未考虑其他因素。【结论】该模型相对于利用标签进行协同过滤推荐方法具有较优的效果, 计算时间和空间复杂度更小。

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涂海丽
唐晓波
关键词 用户标签商品本体用户偏好推荐模型    
Abstract

[Objective] This paper proposes a personalized product recommendation model based on tags in the social e-commerce environment. [Methods] First, we calculated users’ interests and preferences with the help of tagging frequency and time. Then, we constructed a product ontology of the commercial community based on the tag features and searching conditions of the e-commerce website. Third, we used the ontology to standardize tag semantics, and to classify goods. Fourth, we found clusters containing user preferences, and calculated the similarity between their tags of goods and user preference in the cluster. Finally, we identified the goods which were not tagged but preferred by a specific user. [Results] We examined the model with information of 200 randomly selected active users of popular items from the website of FanDongXi. [Limitations] Only used the frequency and time factor of the users’ tags to calculate their interests and preferences. [Conclusions] The proposed method has better performance than the collaborative filtering recommendation based methods.

Key wordsUser Tag    Product Ontology    User Preference    Recommendation Model
收稿日期: 2016-12-07      出版日期: 2017-10-18
ZTFLH:  G35  
基金资助:*本文系国家自然科学基金项目“社会化媒体集成检索与语义分析方法研究”(项目编号: 71273194)、抚州市社科规划项目“基于KANO模型的抚州旅游市场需求分析”(项目编号: 15sk23)和东华理工大学地质资源经济与管理研究中心开放基金项目“基于KANO模型的旅游用户潜在需求挖掘研究”(项目编号: 14GL05)的研究成果之一
引用本文:   
涂海丽, 唐晓波. 基于标签的商品推荐模型研究*[J]. 数据分析与知识发现, 2017, 1(9): 28-39.
Tu Haili,Tang Xiaobo. Building Product Recommendation Model Based on Tags. Data Analysis and Knowledge Discovery, 2017, 1(9): 28-39.
链接本文:  
https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467.2017.09.03      或      https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2017/V1/I9/28
  基于标签的商品推荐模型
  社会化电子商务中的用户-标签-商品关系示例
  标签层次及对应结构
  基于标签的本体构建
  用户标签权重计算结果(部分)
  不同K值下的Precision值比较
  不同K值下的Recall值比较
  不同K值下的F-Measure
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