held in conjunction with

Invited Speakers

Dr Minoru Etoh (NTT DoCoMo)

Cellular Phones as Information Hubs

Abstract
This is a survey how cell-phones are interacting with a real world with I/O devices in information retrieval. Many cell-phones are now being equipped with many I/O devices including GPS, microphones, CCD/CMOS cameras, and motion-sensors. Thus content delivery, interaction with contents, and e-commerce are going to be associated with real environments which will bring us context-aware(real-world aware) capability. Here we see the clear distinction between cell-phones and mobile laptop PCs in that context. Interaction is the key when considering mobile information retrieval. Having 3G broadband and low-latency technologies, “always-on” mobile infrastructure has brought an on-demand and real-time information retrieval capability in conjunction with a popular communication culture, which we call “the third generation of cell-phone culture”, which was never seen before. That is in next two decades, billions of cell-phones are now being connected to server cloud. We may have a different level of real-word aware computing which has not emerged yet.

Bio
Minoru Etoh is Deputy Managing Director of Research Laboratories at NTT DoCoMo, Japan. In 90's, he was leading an image communication research team in Matsushita Electric and participated in MPEG-4 standardization.  He joined Multimedia Laboratories of NTT DoCoMo in 2000, where he contributed to launching DoCoMo’s 3G mobile multimedia services including video phones and audio-visual content download applications. He was also appointed at Managing Director of DoCoMo USA Labs in 2002 and Multimedia Labs in 2005 respectively. He served as visiting professor of Nara Institute of Science and Technology in 2003-2006, and is still teaching mobile communication technologies in Osaka University. His expertise a wide range of mobile multimedia: network architecture, terminal software, coding technologies, media transport, and data mining. He received his B.E. and M.S.E.E. from Hiroshima University, Ph.D. degree from Osaka University, in 1983, 1985 and 1993 respectively.

Prof Dik Lun Lee (Hong Kong University of Science and Technology)

To Find or To be Found, That is the Question in Mobile Information Retrieval

Abstract
Web search engines today require users to specify their interests using keywords. By and large, they are successful because the web is so large and so diversify that any reasonable keywords can return some useful documents, whether or not the most relevant or most complete results are returned is a different question. Information filtering aims at matching dynamic information sources against a relatively static user profile to pick up documents that are of interest to the users. It has been studied in the information retrieval community, albeit with less intensity compared to search.

In the mobile scenario, letting interesting information find you is often more important than finding the interesting information when it is needed. The proactive and context-aware nature of information push will manifest itself into all levels and all aspects of mobile information retrieval, turning the mobile device from a place where user commands are issued to a place where information is automatically collected for the user. This talk discusses user profiling methods for monitoring user actions to extract content-based and location-based user profiles, wireless data dissemination architectures that cater for ad hoc location-based information publishing, and applications on mobile advertisements.

Bio
Dik Lun Lee is currently a professor in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology. Prior to this, he was an associate professor in the Department of Computer Science and Engineering at the Ohio State University, USA. He received the MS and PhD degrees in computer science from the University of Toronto, Canada, and B.Sc. degree in Electronics from the Chinese University of Hong Kong. He was the founding conference chair for the International Conference on Mobile Data Management and served as the chairman of the ACM Hong Kong Chapter in 1997. His research interests include information retrieval, search engines, mobile computing, and pervasive computing.

Prof Kim-Hui Yap (Nanyang Technological University)

Mobile Media Annotation and Sharing: Current Challenges and Future Trends

Abstract
With the increasing popularity and usage of camera-equipped mobile devices, large amounts of mobile media content (images and videos) have been generated and are growing rapidly in recent years. This has led to proliferation of mobile media applications. A new trend in mobile media applications centered on mobile media annotation and sharing has emerged and begun to gain popularity and importance recently. This paper will present an overview on mobile media annotation and sharing. Issues and challenges encountered in current media annotation and sharing systems will be discussed. The main characteristics of media annotation and sharing in a mobile environment will be outlined. Finally, future trends in mobile media annotation and sharing will be presented.

Bio
Kim-Hui Yap (S'99-M'03) received the B.Eng. and Ph.D. degrees in electrical engineering from the University of Sydney, Sydney, Australia, in 1998 and 2002, respectively. Currently, he is a faculty member at Nanyang Technological University, Singapore. He has worked on projects for image processing and computer vision, including image restoration, segmentation, super-resolution, and reconstruction. He is also the Group Leader of Content-Based Analysis for the Center for Signal Processing, Nanyang Technological University. His works cover image/video content analysis and understanding, media processing, image/video indexing, retrieval, and summarization. He has numerous publications in various international journals, book chapters, and conference proceedings. He is also the Editor of the book Intelligent Multimedia Processing with Soft Computing (Springer-Verlag, 2005). His main research interests include image/video processing, media content analysis, computer vision, and computational intelligence.