NLPCC 2018 Shared Task User Profiling and Recommendation Method Summary by DUTIR_9148

摘要：

　　User profiling and personalized recommendation plays an important role in many business applications such as precision marketing and targeting advertisement.Since user data is heterogeneous,leveraging the heterogeneous information for user profiling and personalized recommendation is still a challenge.In this paper,we propose effective methods to solve two subtasks working in user profiling and recommendation.Subtask one is to predict users tags,we treat this subtask as a binary classification task,we combine users profile vector and social Large-scale Information Network Embedding(LINE)vector as user features,and use tag information as tag features,then apply a deep learning approach to predict which tags are related to a user.Subtask two is to predict the users a user would like to follow in the future.We adopt social-based collaborative filtering(CF)to solve this task.Our results achieve second place in both subtasks.

关键词： User tags prediction User following recommendation User modeling Collaborative filtering Deep learning

作者: Xiaoyu Chen Jian Wang Yuqi Ren Tong Liu Hongfei Lin

作者单位: Dalian University of Technology,Dalian Liaoning 116023,China

会议类型: 国际会议

会议名称: 2018自然语言处理与中文计算国际会议(NLPCC2018)

会议地点: 呼和浩特

会议语种:英文

页码: 420-428

在线出版日期: 2018-08-26（万方平台首次上网日期，不代表论文的发表时间）