By Ana L. C. Bazzan (auth.), Longbing Cao, Vladimir Gorodetsky, Jiming Liu, Gerhard Weiss, Philip S. Yu (eds.)
This ebook constitutes the completely refereed post-conference court cases of the 4th foreign Workshop on brokers and knowledge Mining interplay, ADMI 2009, held in Budapest, Hungary in may possibly 10-15, 2009 as an linked occasion of AAMAS 2009, the eighth foreign Joint convention on self sufficient brokers and Multiagent Systems.
The 12 revised papers and a pair of invited talks provided have been rigorously reviewed and chosen from quite a few submissions. equipped in topical sections on agent-driven facts mining, facts mining pushed brokers, and agent mining functions, the papers exhibit the exploiting of agent-driven facts mining and the resolving of severe info mining difficulties in conception and perform; the way to increase info mining-driven brokers, and the way information mining can improve agent intelligence in study and functional purposes. matters which are additionally addressed are exploring the combination of brokers and information mining in the direction of a super-intelligent details processing and structures, and picking demanding situations and instructions for destiny examine at the synergy among brokers and information mining.
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Extra resources for Agents and Data Mining Interaction: 4th International Workshop, ADMI 2009, Budapest, Hungary, May 10-15,2009, Revised Selected Papers
Zhang A typical understanding of the above mutual issues existing in agents and data mining is from the angle of ubiquitous intelligence. Ubiquitous intelligence surrounds a real-world agent mining problem can be identified and categorized into the following types. – – – – – – Data intelligence, Human intelligence, Domain intelligence, Network intelligence, Organizational intelligence, and Social intelligence. Furthermore, for agents, data mining and agent mining, it is necessary to not only involve an individual type of the above intelligence, but also consolidate the relevant ubiquitous intelligence into the modeling, evaluation, working process and systems.
Due to such limitations, it is possible to use the classical Kohonen map in the developed system only when q = 1 for each neural network . For to be able to maintain the system functionality while q > 1, it is necessary to apply some modifications to the classical Kohonen map. A heuristic, based on substituting the distance measure, is considered in this work. We propose a substitution of a Euclidean distance measure with a measure based on Dynamic Time Warping (DTW). Using DTW allows to process time series with different duration by one neural net.
A software agent definitions and features can be found in sources [4,11]. Application examples of software agents can be found in various fields of science, industry, environment monitoring and others [1,15]. A task of product life cycle phase transition point forecasting can serve as an example of such problem where both Data Mining and Decision Support technologies should be applied. From the viewpoint of the management it is important to know, in which particular phase the product is. One of applications of that knowledge is selection of the production planning policy for the particular phase .
Agents and Data Mining Interaction: 4th International Workshop, ADMI 2009, Budapest, Hungary, May 10-15,2009, Revised Selected Papers by Ana L. C. Bazzan (auth.), Longbing Cao, Vladimir Gorodetsky, Jiming Liu, Gerhard Weiss, Philip S. Yu (eds.)