By Wai-Ki Ching, Michael Kwok-Po Ng
Info mining and information modelling are lower than quickly improvement. due to their vast functions and learn contents, many practitioners and lecturers are interested in paintings in those parts. in an effort to selling conversation and collaboration one of the practitioners and researchers in Hong Kong, a workshop on facts mining and modelling was once held in June 2002. Prof Ngaiming Mok, Director of the Institute of Mathematical examine, The collage of Hong Kong, and Prof Tze Leung Lai (Stanford University), C.V. Starr Professor of the collage of Hong Kong, initiated the workshop. This paintings includes chosen papers awarded on the workshop. The papers fall into major different types: info mining and information modelling. information mining papers take care of trend discovery, clustering algorithms, type and sensible purposes within the inventory marketplace. info modelling papers deal with neural community types, time sequence types, statistical types and useful purposes.
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Extra resources for Advances in Data Mining and Modeling: Hong Kong 27 - 28 June 2002
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T ~ will ) be a good starting configuration for the Guttman’s updating algorithm (denoted by Gum) as well as the Pliner’s smoothing algorithm (denoted by PLm). The motivation of using this rank is as follows: if object k has the maximum total distance from other objects, object k should probably be the first or the last object in the UDS solution. The distances of other objects to object k, ( d k l , . ,d k n ) , should reflect how similar of these objects to object k. Therefore, the rank ( T I , .
A decreasing sequence of ~i= q ( N - i 1)/N for i = 2 , . . ,N is first constructed. 3). This solution is used as the initial configuration for the second stage with E = € 2 . The solution in the second stage is used as the initial configuration for the third stage and so on. This process continue up to the N t h stage. Pliner’s smoothing algorithm provides a better solution than Guttman’s updating algorithm but it also requires longer computational time as well. Therefore, a good starting configuration is very important to these algorithms.