学术看板
科研动态
学院基金
成果展示
科研团队
相关政策
科研机构
学术看板
学术报告——Towards Explainable Recommendation via the Exploration of Multimodal Data
时间: 2018-03-26 15:36  来源: 计算机学院

 

报告题目:Towards Explainable Recommendation via the Exploration of Multimodal Data

报告人:程志勇(Postdoctoral Research Fellow, School of Computing, National University of Singapore, Singapore)

报告时间:201833014:00

报告地点:计算机学院(软件学院)报告厅(望江校区基础教学大楼B302

 

报告内容:

Latent factor models (e.g., matrix factorization) achieve good accuracy in rating prediction. However, they suffer from several problems including cold-start, non-transparency, and suboptimal recommendation for individual users.

In this talk, I will introduce our recent works on exploring multimodal data to alleviate these limitations. We employ user text reviews and item images together with the ratings to infer users’ preferences and items’ features on different aspects. To be specific, aspect-aware topic models are applied on text reviews and item images to capture user preferences and item features on different aspects with/without using well-defined aspect labels. The learned aspect preferences are integrated into a designed aspect-aware latent factor model to estimate aspect ratings for each user-item pair. To this end, our model captures a user’s preference on semantic aspects and estimates the importance and ratings of each aspect for an item. Therefore, our model could alleviate the data sparsity problem, gain good interpretability, and achieve more accurate prediction for local user-item pairs.

Comprehensive experimental studies have been conducted on 19 datasets from Amazon and Yelp 2017 Challenge dataset. Results show that our method achieves significant improvement compared with strong baseline methods, especially for users with only few ratings. Moreover, our model could provide reasonable explanation for recommendations.

 

报告人简介:

Zhiyong Cheng is currently a postdoctoral research fellow with the School of Computing at the National University of Singapore. His research interests include information retrieval, recommender systems, multimedia and machine learning. His works have appeared in several top-tier conferences and journals, such as SIGIR, WWW, IJCAI, TOIS, and TKDE. He has served as program committee member of international conferences such as ACM MM and ICDM.

 

欢迎广大师生踊跃参加!

 

 

外事科

                                            2018326






】 【打印本文】 【关闭窗口

 

 

地址:(望江校区)成都市一环路南一段24号基础教学楼B座三楼 邮编:610065 电话:86-028-85469688
   (江安校区)成都市双流县川大路第二基础教学楼B座五楼 邮编:610207 电话:86-028-85990972

四川大学计算机学院版权所有 © 2011

Produced By CMS 网站群内容管理系统 publishdate:2018/03/27 09:56:22