报告题目 | Rating online commodities by considering consumers’ purchasing networks | ||
报告人（单位） | 李永立 （哈尔滨工业大学） | ||
点评人（单位） | 杨东辉（东南大学） | 点评人（单位） | |
会议时间 | 2023年5月29日19:00 | ||
会议地点 | 会议时间：2023/05/29 19:00 (GMT+08:00) 中国标准时间 - 北京 点击链接入会，或添加至会议列表：https://meeting.tencent.com/dm/Txs2g9biXsRp #腾讯会议：980-535-940；会议密码：0529 | ||
报告人简介 | |||
李永立，哈尔滨工业大学经济与管理学院教授，博士生导师。主要研究方向为复杂网络分析、金融科技、金融风险管理、决策理论与方法和数据挖掘与数据分析。在以上研究方向，在包括Journal of Economic Behavior and Organization, Quantitative Finance, European Journal of Operational Research, Omega, Journal of the Operational Research Society, Journal of Informetrics, Journal of the Association for Information Science and Technology, Information Technology & People, IEEE Transactions on Systems, Man and Cybernetics: Systems, Scientometrics, Internet Research, Knowledge-based Systems等经济管理类国际知名期刊发表学术论文40余篇，以及在《管理科学学报》、《系统工程理论与实践》、《系统工程学报》等国家自然科学基金委管理学部推荐刊物发表论文近20篇。曾主持国家自然科学基金面上项目两项和青年项目一项，中国博士后科学基金特等资助和一等资助各一项，黑龙江省自然科学基金项目优秀青年基金项目获得者（黑龙江省优青）、黑龙江省教育科学专项省级重点课题等国家级和省部级科研项目。获得授权发明专利两项，专著两本，教材一本。 | |||
报告内容提要 | |||
Rating, as a common way of evaluation, is a significant exercise and plays a major role in managerial decision-making in general and in particular online purchasing. This work utilizes the theory of social network analysis (SNA) to make a comprehensive evaluation model for rating commodities, presents the new model’s properties and further illustrates the model’s applicability. Through the designed comparison analysis and the empirical analysis, the proposed method is validated to be better than the traditional ones such as averaging, analytic hierarchy process (AHP) and several mentioned dimension-reduction techniques (DRTs) in terms of consistency and its ability to deal with the missing data. In all, the proposed method enables to give comprehensive rating results which can preserve the rankings implied by all the customers’ ratings, adapt to the database with the missing data and cost a low algorithm time and space. | |||
