基于社会标注复杂网络的电子商务推荐方法研究

项目名称： 基于社会标注复杂网络的电子商务推荐方法研究

项目编号： No.71202168

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 工商管理

项目作者： 庞秀丽

作者单位： 黑龙江大学

项目金额： 17万元

中文摘要： 电子商务推荐可帮助用户快速找到满意商品，改善电子商务的服务质量，提高产品的销售量，它是电子商务和客户关系管理中的一个重要研究内容。近年来，社会标注网络可描述文本类内容，还可描述图像、声音、视频等传统方法不易说明其特征的产品，目前已在一些电子商务企业中成功采用，并带来可观的效益。本课题研究基于社会标注复杂网络的电子商务推荐方法，主要包含三项工作：一、借鉴复杂网络理论对标签网络的结构进行分析，发现用户之间隐含的联系，帮助用户组织自己喜好的资源，形成自己的网络社团，并为用户兴趣协同扩展提供依据；二、研究标签网络中的广义语义信息提高推荐系统的概念敏感型，改善推荐系统的深层次推理能力；三、研究引入标签的组合推荐方法并进一步研究其增量式学习机制，赋予推荐系统动态学习能力，以解决现有电子商务中因新产品的增加、用户兴趣的转移等引起的推荐环境变化，体现推荐系统的智能化。

中文关键词： 电子商务推荐；复杂网络；社会结构分析；推荐系统；

英文摘要： E-Commerce recommender helps users to find the commodities easily. And it not only improves quality of E-Commerce service, but also increases purchase of commodities. E-Commerce recommendation is an important research task in E-Commerce and customer relationship management. Recent years, as a kind of new application forms, social tagging network can describe the text based products, and it also describes the image, sound, video, etc, which is difficultly described by traditional content based method. The tagging based recommendation has been successfully applied in some notable E-commerce corporation, and bring promising benefit. This research is focused on E-Commerce recommendation based on social tagging network. It has three parts work. First, it analyzes community structure of social tagging network in use of complex network theory to find the latent relationship of users, and form their community structure to help users to constructor their favorite resource. Furthermore it provides support for extended collaborative filtering. Secondly, the semantic relations among concepts are calculated by reference the theory of Complex Network, and these semantic relations are fused into the E-Commercial Recommendation, so as to improve the infer ability. Thirdly, the tagging based recommendation is combined with ma

英文关键词： E-Commerce Recommender；Complex networks；Community；Recommendation system；