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Full Description
WAIM 2004, Dalian (China), 15-17 July, was hosted by Northeastern Univ- sity, China and Dalian University of Technology, China in cooperation with the Database Society of CCF. It was the International Conference on Web-Age Information Management. WAIM 2004 brought together participants from u- versities,industry, and governmentto present,discuss, and address both current issues and novel approaches in the practice, deployment, theory, and meth- ology of information management in the context of the World Wide Web. The conference provided an international forum for the sharing of original research results and practical development experiences among researchers and appli- tion developers from the many Web-related areas. The previous WAIM conf- ences wereheld in Shanghai(WAIM 2000),Xi'an (WAIM 2001),Beijing (WAIM 2002), and Chengdu, China (WAIM 2003). These conferences turned out to be very successful and each attracted more than 100 participants from all over the world.
The WAIM 2004 conference included technical sessions organized around important subtopics such as data streamprocessing,time series data processing, mobilecomputing,cachemanagement,security,XML,Web services,Web search engines, query evaluation, and data mining, etc. Following careful review of the 291 submissionsby membersof the internationalprogramcommittee, 57 regular papers and 23 short/industrial papers were accepted for presentation at the conference and for publication in this volume. The submissions came from a total of 22 countries and regions, and the accepted ones were from 13 countries andregions,including Australia,Canada,Chile,China,HongKongSAR,Korea, Norway, Singapore, Spain, Taiwan, UAE, UK, and USA. The conference also consisted of a poster and demonstration track, the publication of which was done in CD-ROM form.
Contents
Invited Talks.- Data Stream Processing.- Time Series Data Processing.- Security.- Mobile Computing.- Cache Management.- Query Evaluation.- Web Search Engine.- XML.- Web Services.- Classiffication.- Data Mining.- Industrial/Short Papers.
