日本データベース学会の皆様、 以下、特別企画「Cyver Physical Systems」と題して、 米国の先端研究者からホットトピック情報を語っていただく 講演会が6月9日(木)・東大生研にて行われます。 ふるってご参加ください。 　　　　　　　　　　　　　　　　　東京大学生研 　　　　　　　　　　　　　　　　　中野美由紀 　☆☆☆　6月9日　特別企画「ＣＰＳ」講演会のご案内　　　☆☆☆ 共催　電子情報通信学会データ工学研究専門委員会 　　　最先端研究開発支援プログラム（FIRST）: 「超巨大データベース時代に 　　　向けた最高速データベースエンジンの開発と当該エンジンを核とする 　　　戦略的社会サービスの実証・評価」 日本データベース学会 　　　ACM SIGMOD日本支部 日時　6月9日（木）　午後1時半〜5時 場所　東京大学生産技術研究所　An棟　3階　大会議室（An 301,302） http://www.iis.u-tokyo.ac.jp/map/index.html 特別企画　Cyber Physical Systems 講演会 13:30-14:30 Social Influence Models in Information Network Analysis Prof. Ling Liu (Georgia Institute of Technology) 14:45-15:45 Participatory Urban Data Collection: Planning and Optimization 　　　　Prof. Cyrus Shahabi (USC) 16:00-17:00 A World of Opportunities: CPS, IOT, and Beyond Prof. Calton Pu (Georgia Institute of Technology) 参加費　無料 皆様のご参加をお待ちしております。 　　　　　　　　　　　　電子情報通信学会データ工学研究会　委員長 　　　　　　　　　　　　　　　　　　　　　　　　　　　　 中野　美由紀 　　　　　　　　　　　　最先端(FIRST)プログラム　 「超巨大ＤＢ＆戦略的社会サービス」 　　　　　　　　　　　　　　　　　　　研究代表者　　　　　喜連川　優 　　　　　　　　　　　　　　　　　　　　　　 連絡(問合せ)先　cps_lecture@tkl.iis.u-tokyo.ac.jp ----------------------------------------------------------------- To: cps_lecture@tkl.iis.u-tokyo.ac.jp 　講演会　参加申し込み 6月9日（木）の講演会に参加 ・お名前　　　 ・ご所属 ------------------------------------------------------------------ プログラム詳細 13:30-14:30 Social Influence Models in Social Network Analysis Ling Liu (Georgia Institute of Technology) Social influence, the phenomenon that the actions of a user induce similar behaviors among his/her friends via social ties, exists prevailingly in socially networked systems. Social influence models define the processes by which ideas and influence propagate through a social network. The effects of “word of mouth” in the promotion of new products represent one example application of the science of social influence. In this talk, I will first give an overview of some representative social influence models, focusing on the algorithmic problem for social influence processes in social networks: Can we convince a subset of individuals to adopt a new product, a new idea or an innovation, such that a large cascade of further adoptions can be triggered? and if so, which set of individuals should we target? Existing studies mostly focus on studying flow of communication across groups at macro-level (e.g., diffusion models). We argue that it is equally important to understand and model flows within dyads or small groups (micro level). Social influence at microscopic scale (i.e., at the granularity of individual users, actions and time-stamps) may significantly enhance our understanding of two important questions: (1) how word of mouth interaction in dyads or small groups aggregates to form large-scale patterns in the diffusion of information and influence concerning innovations, fashions, fads, rumors and formation of consumer attitudes, and (2) which interpersonal ties are more likely to be activated for the flow of information and are more influential. In the second part of the talk, I will give a brief overview of our recent work in social influence across multiple networks. Concretely, I will discuss how to model users’ actions as interactions between social network (formed by users) and object network (formed by targets of actions), how an occurred interaction may trigger another, when and where a new interaction may be observed? I will also illustrate the use of our cross-network social influence analysis to answer the above two fundamental questions of social influence. While macroscopic social influence models may be amenable to stochastic analysis over large populations of users and objects, microscopic analysis introduces new computational challenges. We will end the talk with a set of research challenges in influence driven social network analysis. Short Bio: Ling Liu is a full Professor in the School of Computer Science at Georgia Institute of Technology. There she directs the research programs in Distributed Data Intensive Systems Lab (DiSL), examining various aspects of data intensive systems with the focus on performance, availability, security, privacy, and energy efficiency. Prof. Liu and her students have released a number of open source software tools, including WebCQ, XWRAPElite, PeerCrawl, GTMobiSim. Prof. Liu has published over 250 International journal and conference articles in the areas of databases, distributed systems, and Internet Computing. She is a recipient of the best paper award of ICDCS 2003, WWW 2004, the 2005 Pat Goldberg Memorial Best Paper Award, and 2008 Int. conf. on Software Engineering and Data Engineering. Prof. Liu has served as general chair and PC chairs of numerous IEEE and ACM conferences in data engineering, distributed computing, service computing and cloud computing fields and is a co-editor-in-chief of the 5 volume Encyclopedia of Database Systems (Springer). She is currently on the editorial board of several international journals, such as Distributed and Parallel Databases (DAPD, Springer), Journal of Parallel and Distributed Computing (JPDC), ACM Transactions on Web, IEEE Transactions on Service Computing (TSC), and Wireless Network (WINET, Springer). Dr. Liu’s current research is primarily sponsored by NSF, IBM, and Intel. 14:45-15:45 Participatory Urban Data Collection: Planning and Optimization Abstract In recent years, we have been witnessing the rapid advances of two technological trends. The first is the earth visualization systems (e.g., Google Earth, Microsoft Virtual Earth) that are becoming more and more realistic, allowing users to visualize almost every major urban area at detailed street and building levels. However, these systems face a major challenge in updating their data frequently due to the high cost of data collection. The second trend involves the advances of mobile devices equipped with sophisticated sensors, enabling people to collect and transmit audio, video, image, and text information tagged with location and time. Hence, there is an opportunity here to incentivize the public to participate in opportunistic data collection campaigns in order to transform the static environment of earth visualization systems to a dynamic one covering ever-changing, up-to-the-minute information about our urban environments and their events. The applications of su ch a dynamic information-rich geospatial environment are plenty, from tracking a contagious disease to the latest coverage of breaking news. One of the main research challenges in enabling participatory urban data collection is to find optimal plans for the participants such that they can collectively acquire as much of data as possible without violating their constraints. In this talk, I will present one specific example of the abovementioned vision, a participatory texture documentation (PTD) system, in which a group of users (dedicated individuals and/or general public) with camera-equipped mobile devices participate in collaborative collection of dynamic urban texture information. PTD enables inexpensive, scalable and high resolution urban texture documentation. We focus on the optimal planning challenges of PTD that consists of two phases: viewpoint selection and viewpoint assignment. First, during the viewpoint selection phase, a minimum number of points in an urban environment are selected from which the visible texture of the entire urban environment can be collected/captured. Next, during the viewpoint assignment phase, the selected viewpoints are assigned to the participating users such that given a limited number of users with various constraints; the users can collectively capture the maximum amount of texture information within a limited time interval 16:00 - 17:00 Title: A World of Opportunities: CPS, IOT, and Beyond Speaker: Prof. Calton Pu, Georgia Institute of Technology Abstract: The continuous evolution of computing and networking technologies (e.g., Moore’s Law) is creating a new world populated by many sensors on physical and social environments. This emerging new world goes much further than the original visions of ubiquitous computing and World Wide Web. Aspects of this new world have received various names such as Cyber Physical Systems (CPS) and Internet of Things (IOT). CPS links many physical sensor data to detailed simulation models running on large data centers. IOT brings together many appliances, making much more environmental data available and supporting control of these appliances. CPS/IOT applications are many, including personalized healthcare, intelligent transportation, smart grid, sustainable environment, and disaster recovery as representative examples. These CPS/IOT applications are motivated and strongly pushed by significant new social, economic, and human benefits. At the same time, these applications are also mission-critical with serious quality of service requirements such as real-time performance, continuous availability, high security and privacy. We will argue that the traditional process-oriented programming languages and software architectures should be augmented by distributed event-based facilities and abstractions (e.g., Continual Query) for the construction of large scale distributed CPS/IOT applications. In addition to the focus on performance, we anticipate that other quality of service dimensions such as availability, reliability, security, and privacy will become important concerns. We will discuss research opportunities and challenges that bring systems concepts and techniques such as streams, events, and code generation to CPS/IOT applications, with real world application scenarios such as the collection and management of a large amount and variety of radiation sensor data and metadata. ---------------------------------------- Bio Sketch: Calton Pu was born in Taiwan and grew up in Brazil. He received his PhD from University of Washington in 1986 and served on the faculty of Columbia University and Oregon Graduate Institute. Currently, he is holding the position of Professor and John P. Imlay, Jr. Chair in Software in the College of Computing, Georgia Institute of Technology. He has worked on several projects in systems and database research. His contributions to systems research include program specialization and software feedback. His contributions to database research include extended transaction models and their implementation. His recent research has focused on automated system management in clouds (Elba project) and document quality, including spam processing. He has collaborated extensively with scientists and industry researchers. He has published more than 70 journal papers and book chapters, 200 conference and refereed workshop papers. He served on more than 120 program committees, including the co-PC chairs of SRDS'95, ICDE’99, COOPIS’02, SRDS’03, DOA’07, DEBS’09, ICWS’10, CollaborateCom'11, and cogeneral chair of ICDE'97, CIKM'01, ICDE’06, DEPSA’07, CEAS’07, SCC’08, CollaborateCom’08, and World Service Congress’11. -- ----------------------------------------------------------------------- 中野　美由紀 東京大学　生産技術研究所　戦略情報融合国際研究センタ Miyuki NAKANO Institute of Industrial Science, Univ. of Tokyo 　　　　　　　　Center for Information Fusion miyuki@tkl.iis.u-tokyo.ac.jp