By Sandip Sen (auth.), Longbing Cao, Ana L. C. Bazzan, Vladimir Gorodetsky, Pericles A. Mitkas, Gerhard Weiss, Philip S. Yu (eds.)
This ebook constitutes the refereed lawsuits of the sixth overseas Workshop on brokers and information Mining interplay, ADMI 2010, held in Toronto, Canada, in could 2010. The 15 revised complete papers offered have been conscientiously reviewed and chosen from 37 submissions. The papers are geared up in topical sections on brokers for information mining; information mining for brokers; facts mining in brokers; and agent mining functions.
Read Online or Download Agents and Data Mining Interaction: 6th International Workshop on Agents and Data Mining Interaction, ADMI 2010, Toronto, ON, Canada, May 11, 2010, Revised Selected Papers PDF
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Extra info for Agents and Data Mining Interaction: 6th International Workshop on Agents and Data Mining Interaction, ADMI 2010, Toronto, ON, Canada, May 11, 2010, Revised Selected Papers
1st Touchstone edn. : Complex Adaptive Systems. : Modeling Complex Systems. : Complex Adaptive Systems: Exploring the Known, the Unknown and the Unknowable. : Agent-based Models. : A Computer Simulation Laboratory for Social Theories. : NetLogo. Center for Connected Learning and Computer-Based Modeling. edu/netlogo/ 26 T. Carmichael, M. Hadzikadic, and O. : An Agent-based Model of Solid Tumor Progression. : Towards a General Tool for Studying Threshold Effects Across Diverse Domains. , Ribarsky, W.
It should be noted that the results of this pilot simulation can be replicated with other statistical techniques and traditional methods of data mining. g. INC that one of the authors is very familiar with , can use complete agent descriptions and a predefined similarity function to drive the formation of clusters, which are subsequently used for prediction of category membership for the remaining, previously unseen cases. However, CAS studies allow the project designer to let many aspects of the underlying phenomenon emerge, instead of being specified ahead of time.
A QA decides autonomously within its decision scope whether to create a query plan or a further decomposition and delegation is needed. If the QA is able to process a query sequence completely, it returns the intermediate result to the QMA. Information Retrieval Agents Information retrieval agents control the relevant data sources. They are responsible for maintaining a data connection with their corresponding data sources. In addition to the realisation of the technical access to the different data sources, a uniform description of the data source content is needed which translates the ontology-based representation into the target technology.
Agents and Data Mining Interaction: 6th International Workshop on Agents and Data Mining Interaction, ADMI 2010, Toronto, ON, Canada, May 11, 2010, Revised Selected Papers by Sandip Sen (auth.), Longbing Cao, Ana L. C. Bazzan, Vladimir Gorodetsky, Pericles A. Mitkas, Gerhard Weiss, Philip S. Yu (eds.)