Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective
暫譯: 社交媒體分析與用戶行為建模：任務異質性視角

近年來，社交媒體獲得了顯著的普及，並成為一種重要的溝通媒介。這種用戶生成的內容為應用挖掘任何信息的隱喻提供了絕佳的場景。轉移學習（Transfer learning）是機器學習中的一個研究問題，專注於利用在解決一個問題時獲得的知識，並將其應用於不同但相關的問題。

特點：
- 提供新穎的框架來研究用戶行為，並解決和解釋任務異質性
- 提供現有研究的詳細研究
- 提供框架的收斂性和複雜性分析
- 包含實現所提研究工作的算法
- 涵蓋廣泛的實證分析

《社交媒體分析與用戶行為建模：任務異質性視角》是一本針對異質環境中用戶行為建模的指南，對機器學習社群非常有用。

Arun Reddy Nelakurthi is a Senior Engineer in Machine Learning Research at Samsung Research America, Mountain View, California. He received his PhD in Machine Learning from Arizona State University in 2019. His research focuses on heterogeneous machine learning, transfer learning, user modeling and semi-supervised learning, with applications in social network analysis, social media analysis and healthcare informatics. He has served on the program committee for Conference on Information and Knowledge Management (CIKM) and The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD). He also worked as a reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE), Data Mining and Knowledge Discovery (DMKD) and IEEE Transactions on Neural Networks and Learning Systems (TNNLS) journals.

Jingrui He is an associate professor in the School of Information Sciences at the University of Illinois at Urbana-Champaign. She received her PhD in machine learning from Carnegie Mellon University in 2010. Her research focuses on heterogeneous machine learning, rare category analysis, active learning and semi-supervised learning, with applications in social network analysis, healthcare, and manufacturing processes. Dr. He is the recipient of the 2016 NSF CAREER Award and a threetime recipient of the IBM Faculty Award, in 2018, 2015 and 2014 respectively. She was selected for an IJCAI 2017 Early Career Spotlight, and was invited to the 24th CNSF Capitol Hill Science Exhibition. Dr. He has published more than 90 refereed articles, and is the author of the book, Analysis of Rare Categories (Springer- Verlag, 2011). Her papers have been selected as "Best of the Conference" by ICDM 2016, ICDM 2010, and SDM 2010. She has served on the senior program committee/ program committee for Knowledge Discovery and Data Mining (KDD), International Joint Conference on Artificial Intelligence (IJCAI), Association for the Advancement of Artificial Intelligence (AAAI), SIAM International Conference on Data Mining (SDM), and International Conference on Machine Learning (ICML).

阿倫·雷迪·內拉庫爾提是三星美國研究所（Samsung Research America）位於加州山景城的機器學習研究高級工程師。他於2019年在亞利桑那州立大學獲得機器學習博士學位。他的研究專注於異質機器學習、轉移學習、用戶建模和半監督學習，應用於社交網絡分析、社交媒體分析和醫療資訊學。他曾擔任資訊與知識管理會議（Conference on Information and Knowledge Management, CIKM）和亞太知識發現與數據挖掘會議（The Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD）的程序委員會成員。他也曾擔任《IEEE知識與數據工程期刊》（IEEE Transactions on Knowledge and Data Engineering, TKDE）、《數據挖掘與知識發現期刊》（Data Mining and Knowledge Discovery, DMKD）以及《IEEE神經網絡與學習系統期刊》（IEEE Transactions on Neural Networks and Learning Systems, TNNLS）的審稿人。

何靜瑞是伊利諾伊大學香檳分校（University of Illinois at Urbana-Champaign）資訊科學學院的副教授。她於2010年在卡內基梅隆大學獲得機器學習博士學位。她的研究專注於異質機器學習、稀有類別分析、主動學習和半監督學習，應用於社交網絡分析、醫療保健和製造過程。何博士是2016年國家科學基金會（NSF）CAREER獎的獲得者，並三度獲得IBM教職員獎，分別在2018年、2015年和2014年。她被選為2017年國際人工智慧聯合會議（IJCAI）早期職業亮點，並受邀參加第24屆國會山科學展覽（CNSF Capitol Hill Science Exhibition）。何博士已發表超過90篇經過審核的文章，並著有《稀有類別分析》（Analysis of Rare Categories, Springer-Verlag, 2011）一書。她的論文曾被ICDM 2016、ICDM 2010和SDM 2010評選為「會議最佳論文」。她曾擔任知識發現與數據挖掘會議（KDD）、國際人工智慧聯合會議（IJCAI）、人工智慧促進協會（AAAI）、SIAM國際數據挖掘會議（SDM）和國際機器學習會議（ICML）的高級程序委員會/程序委員會成員。