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刘寰哲.jpg

刘寰哲

北京大学

个人简介

哲,博士,北京大学信息科学技术学院副教授,主要研究方向包括软件工程、移动计算系统、服务计算等。近年来在 TSE、TMC、TOIS、TOIT、TSC、WWW、ICSE、OOPSLA、UbiComp等国际期刊和会议上发表学术论文 30 余篇,其中CCF A类论文10余篇;获3次国际会议最佳论文奖和2次最佳论文奖提名;博士学位论文《基于社区的服务组装技术研究》获 2011 年全国优秀博士学位论文提名奖、2010 年中国计算机学会优秀博士论文奖(同行评审排名第一);作为主要完成人获得教育部科技进步一等奖(排名第3);研制的关键技术以通过专利转化方式应用于央企、政府、互联网等多个领域,取得良好社会经济效益。担任WWW、KDD、ICSE、CIKM、ICDCS、ICSOC、ICWS等国际会议程序委员会成员;Journal of Computer Science and Technology特邀编辑(Guest Editor);CCF学术工作委员会秘书、委员;CCF服务计算专委会委员;中国电子学会青年科学家俱乐部云计算大数据专委会秘书长。


演讲题目

Learning from the Large-Scale User-Behavior Data of Appstore


议题简介

The prevalence of smart mobile devices has promoted the popularity of mobile applications (a.k.a. apps) and appstores such as Apple Appstore, Google Play, and numerous third-party appstores. The appstore has significantly changed the development and delivery model of software, and even established a new ecosystem. Understanding user behaviors over the appstores can help improve app development, deployment, delivery, revenue, etc. This talk presents our recent study of deriving various insightful knowledge by learning behavioral profiles collected from millions of users, including app management activities (i.e., downloading, updating, and uninstalling apps) and app network usage. Based on the findings as well as derived knowledge, we suggest some practical machine-learning based solutions to address challenges raised by the appstore-centric ecosystem.


中关村智联软件服务业质量创新联盟

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