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关于邹至庄

A Group-Specific Recommender System

主讲人: Peiyong Qu,University of Illinois at Urbana-Champaign
主讲人简介:

Homepage: http://www.stat.illinois.edu/people/faculty/qu.shtml

主持人: Wei Zhong
简介:

Abstract: In recent years, there has been a growing demand to develop efficient recommender systems which track users’ preferences and recommend potential items of interest to users. In this talk, we propose a group-specific method to utilize dependency information from users and items which share similar characteristics under the singular value decomposition framework. The new approach is effective for the “cold-start” problem, where, in the testing set, majority responses are obtained from new users or for new items, and their preference information is not available from the training set. One advantage of the proposed model is that we are able to incorporate information from the missing mechanism and group-specific features through clustering based on the numbers of ratings from each user and other variables associated with missing patterns.  Our simulation studies and MovieLens data analysis both indicate that the proposed group-specific method improves prediction accuracy significantly compared to existing competitive recommender system approaches. In addition, we also extend the recommender system for the tensor data with multiple arrays.

时间: 2017-07-06(Thursday)16:40-18:00
地点: N301,Econ Building
期数: 统计系独立讲座
主办单位: SOE&WISE
承办单位: 统计系
类型: 独立讲座