Keynotes

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Abstract

Geo-textual web content is content accessible on the web that has a text component as well as a geo-location, in addition to possibly other attributes such as a timestamp or a rating. Increasing volumes of suchobjects are available on the web, including web pages, business directory entries, and microblog posts.

Geo-textual web content is not only relevant but also important to many human activities. Thus, studies suggest that each week, several billion keyword-based queries are issued that have some form of local intent and target geo-textual web content. Such queries aim to find relevant content in an implied geographical region.

This state of affairs gives prominence to the capability of efficiently computing queries that retrieve useful content from large collections of geo-textual web content. A standard keyword-based query takes a user location and user-supplied keywords as arguments, and it returns content that is geographically and textually relevant to these arguments. Due perhaps to the rich semantics of geographical space and its importance to our daily lives, many different kinds of useful geo-textual web query functionality may be envisioned. For example, some queries aim to find a few near-by points of interest that each satisfy a user’s needs as indicated by query keywords, other queries aim to find a set of points of interest that collectively satisfy a user’s needs, and yet other queries aim to find densely populated regions that enable a user to conveniently explore different relevant points of interest.

Based on recent and ongoing work by the speaker and his colleagues, the talk presents key functionality, concepts, and techniques relating to the querying of geo-textual web content; it covers functionality that addresses different kinds of user intent; and it offers directions for the future development of keyword-based geo-textual web querying.

Bio

Christian S. Jensen is Obel Professor of Computer Science at Aalborg University, Denmark, and he was previously with Aarhus University for three years and spent a one-year sabbatical at Google Inc., Mountain View. His research concerns data management and data-intensive systems, and its focus is on temporal and spatio-temporal data management. Christian is an ACM and an IEEE Fellow, and he is a member of Academia Europaea, the Royal Danish Academy of Sciences and Letters, and the Danish Academy of Technical Sciences. He has received several national and international awards for his research. He is Editor in Chief of ACM Transactions on Database Systems.

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Bio

Professor Daniel P. Siewiorek is the Buhl University Professor of Electrical and Computer Engineering and Computer Science at Carnegie Mellon University. He has designed or been involved with the design of nine multiprocessor systems and has been a key contributor to the dependability design of over two dozen commercial computing systems. Dr. Siewiorek leads an interdisciplinary team that has designed and constructed over 20 generations of mobile computing systems. He has written nine textbooks in addition to over 480 papers. He is Director of the Quality of Life Technology NSF Engineering Research Center and previously served as Department Head of the Human Computer Interaction Institute. He has been the recipient of the AAEE Terman Award, the IEEE/ACM Eckert-Mauchly Award, and the ACM SIGMOBILE Outstanding Contributions Award. He is a Fellow of IEEE, ACM, and AAAS and is a member of the National Academy of Engineering. Professor Siewiorek received the B.S. degree in Electrical Engineering from the University of Michigan, and the M.S. and Ph.D. degrees in Electrical Engineering (minor in Computer Science) from Stanford University.

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Bio

Simonas Saltenis is an associate professor at the Department of Computer Science, Aalborg University, Denmark. He is affiliated with the Center for Data-Intensive Systems (DAISY) at Aalborg University. His research concerns spatial and spatiotemporal data management with a focus on the management of mobile objects, multidimensional access methods, multithreaded algorithms and data structures. During the last decade, Simonas has been serving on the program committees of major data management conferences. Simonas has a bachelors degree from Vilnius University, Lithuania, as well as a Masters degree and a Ph.D. in Computer Science, both from Aalborg University, Denmark. During his doctoral studies he was a visiting researcher at Denver University, Colorado.

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Abstract

Cloud computing provides a rich set of applications to more resource-limited mobile devices. The traditional cloud data center has its limitations, however, in terms of the connectivity, latency, bandwidth, and agility provided to mobile devices. Cloud-type resources (agile computation and storage) are needed at the edge of the network, where the people live---in access points, in cars, in homes, in coffee shops, etc. Moreover, the most interesting, timely data are generated at the edge, by the billions of mobile devices and soon hundreds of billions of smart sensors in the Internet of Things. Thus, data management tasks---query processing, analytics, indexing, caching, storage, privacy protection---should be increasingly done at the edge in a distributed, streaming fashion. This talk presents our ongoing work in this area at the Intel Science & Technology Center for Cloud Computing, and important future directions.

Bio

Phillip B. Gibbons is a Principal Research Scientist at Intel Labs and a Principal Investigator for the Intel Science and Technology Center for Cloud Computing homed at Carnegie Mellon University. His publications span systems and theory, and have been cited 13,800+ times with an h-index of 60. He is Editor-in-Chief for the recently launched ACM Transactions on Parallel Computing, an Associate Editor for the Journal of the ACM, and has served as program or area chair for a number of conferences in parallel/distributed computing, sensor networks, and databases. Gibbons is both an ACM and IEEE Fellow.