By Peter Stone (auth.), Longbing Cao, Ana L. C. Bazzan, Andreas L. Symeonidis, Vladimir I. Gorodetsky, Gerhard Weiss, Philip S. Yu (eds.)
This booklet constitutes the completely refereed post-workshop complaints of the seventh foreign Workshop on brokers and knowledge Mining interplay, ADMI 2011, held in Taipei, Taiwan, in may possibly 2011 together with AAMAS 2011, the tenth foreign Joint convention on self reliant brokers and Multiagent structures.
The eleven revised complete papers provided have been conscientiously reviewed and chosen from 24 submissions. The papers are prepared in topical sections on brokers for info mining; information mining for brokers; and agent mining applications.
Read or Download Agents and Data Mining Interaction: 7th International Workshop on Agents and Data Mining Interation, ADMI 2011, Taipei, Taiwan, May 2-6, 2011, Revised Selected Papers PDF
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Extra info for Agents and Data Mining Interaction: 7th International Workshop on Agents and Data Mining Interation, ADMI 2011, Taipei, Taiwan, May 2-6, 2011, Revised Selected Papers
3–43. Springer, Heidelberg (2002) 17. : PMADE – A Platform for mobile agent Distribution & Execution. In: The Proceedings of 5th World MultiConference on Systemics, Cybernetics and Informatics (SCI 2001) and 7th International Conference on Information System Analysis and Synthesis (ISAS 2001), Orlando, Florida, USA, July 22-25, vol. IV, pp. 287–293 (2001) 18. : A flexible security framework for mobile agents. Intl. Journal of Control & Intelligent systems’ 33(3), 175–183 (2005) 19. S. K. B. Patel 20.
The overall cluster conﬁguration is then sent to the user agent (inform cluster configuration), after which moves are made for agents to exit the dialogue (leave dialogue) and subsequently end it (close dialogue). The way in which the reconﬁguration of clusters happens is dependant upon the clustering algorithm used, as will be described in the next section. 5 Operation The operation of the proposed MADM clustering mechanism is described in this section. We have elected to describe the operation in a procedural manner as we believe this will facilitates understanding (although readers should be clear that the operation is anything but procedural).
Management of Data, WA, pp. 207–216 (May 1993) 11. : Fast algorithms for mining association rules. In: Proc. 1994 Int. Conf. Very Large Data Bases, Santiago, Chile, pp. 487–499 (September 1994) 12. : Parallel Algorithm for Mining Frequent Itemsets. In: Proc. of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, August 18-21 (2005) 13. : Parallel and Distributed Association Mining: A Survey, Department of Computer Science. Rensselaer Polytechnic Institute, Troy 14.