Titlebook: Intelligent Data Engineering and Automated Learning - IDEAL 2002; Third International Hujun Yin,Nigel Allinson,Simon Hubbard Conference pr

悄悄移动

艰苦地移动

Discovering Temporal Rules from Temporally Ordered Dataoftware. By performing appropriate preprocessing and postprocessing, RFCT extends C4.5’s domain of applicability to the unsupervised discovery of temporal relations among temporally ordered nominal data.

glisten

Automated Personalisation of Internet Users Using Self-Organising Mapslick stream data were used to calculate the probabilities of user behaviour on the Web site. Thus, the map can be used for personalisation of users and to calculate the probabilities of each neuron in predicting where the user will next move on the Web site. The results indicate that SOM analysis can successfully process Web information.

高调

explicit

mitten

nurture

天文台

0302-9743 lications, agent technology, autonomous mining, financial engineering, bioinformatics, learning systems, and pattern recognition.978-3-540-44025-3978-3-540-45675-9Series ISSN 0302-9743 Series E-ISSN 1611-3349

Ischemia

Co-evolutionary Data Mining to Discover Rules for Fuzzy Resource Managementng of the data base as required. The game allows easy evaluation of the information mined in the second step. The criterion for re-optimization is discussed. The mined information is extremely valuable as indicated by demanding scenarios.

duplicate

Data Abstractions for Numerical Attributes in Data Miningwe can reduce the number of extracted rules, still preserving almost the same quality of the rules extracted without abstractions. The usefulness of our abstraction method is shown by preliminary experimental results.