By Sushil Jajodia (auth.), Guozhu Dong, Changjie Tang, Wei Wang (eds.)
With advances within the web and applied sciences round the World-Wide net, learn on layout, implementation, and administration of net- and W- dependent details structures has turn into more and more very important. As progressively more details of various style turns into on hand on the net and net, question and retrieval in addition to the administration of knowledge over the net develop into extra complicated and intensely di?cult. Novel methods to increase and deal with web and net info platforms are in excessive call for. Following the profitable meetings in 2000, 2001 and 2002, WAIM 2003 persisted to supply a discussion board for researchers, execs, and commercial practitioners from worldwide to proportion their speedily evolving wisdom and to file on new advances in Web-based details structures. WAIM 2003 acquired an overpowering 258 submissions from Australia, Canada, China, Denmark, France, Germany, Greece, Hong Kong, Japan, South Korea, Pakistan, Singapore, Sweden, Switzerland, Taiwan, Thailand, united kingdom, united states, and Vietnam. via cautious evaluate through this system committee, 30 papers have been chosen as common papers, and sixteen papers as brief papers. As indicated by means of those numbers, WAIM 2003 is intensely selective: eleven and 17 parts, respectively, together with textual content administration, info mining, details ?ltering, relocating gadgets, perspectives, bioinformatics, net and XML, multimedia, peer-to-peer platforms, provider networks, time-series streams, and ontologies. invited talks by way of Sushil Ja- dia (George Mason college, united states) and Beng Chin Ooi (National collage of Singapore) have been on entry keep an eye on versions and peer-to-peer systems.
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Extra resources for Advances in Web-Age Information Management: 4th International Conference, WAIM 2003, Chengdu, China, August 17-19, 2003. Proceedings
Algorithm 3. Building prediction model from users’ access patterns (training process) Input: Structure representing prediction model of order m constructed so far, user’s training log data Output: Updated prediction model Current context  = root node of structure For every request in user’s training log data: For length m down to 0: If request not appearing as child node of current context [length] in structure: Add child node for request to current context [length] request occurrence = 1 current context [length+1] = node of request if request appearing as child node of current context [length] in structure: request occurrence ++ current context [length+1] = node of request current context  = root node of structure Efficient Reduction of Web Latency through Predictive Prefetching on a WAN 29 Algorithm 4.
X. Chen, X. Zhang, “Popularity-Based PPM: An Effective Web Prefetching Technique for High Accuracy and Low Storage”, in Proc. , Canada, 2002, pp. 296–304. E. Cohen and H. Kaplan, “Prefetching the means for document transfer: A new approach for reducing Web latency”, in Proc. of IEEE INFOCOM, Tel Aviv, Israel, 2000, pp. 854– 863. B. D. Davison, "Assertion: Prefetching with GET is Not Good" in Proc. of The Sixth International Workshop Web Caching and Content Distribution, Elsevier, Boston, 2001, pp.
It is always useful to be able to foresee a request in such systems, in order to be able to service it before it is actually placed, since this would boost system performance. Prefetching systems always run the risk of misusing or even abusing system resources in order to execute their functions. The ultimate goal of Web prefetching is to reduce what is called User Perceived Latency(UPL) on the Web [1, 2, 7, 8, 12]. UPL is the delay that an end user (client) actually experiences when requesting a Web resource.
Advances in Web-Age Information Management: 4th International Conference, WAIM 2003, Chengdu, China, August 17-19, 2003. Proceedings by Sushil Jajodia (auth.), Guozhu Dong, Changjie Tang, Wei Wang (eds.)