New PDF release: Agents and Data Mining Interaction: 10th International

By Longbing Cao

ISBN-10: 3319202294

ISBN-13: 9783319202297

ISBN-10: 3319202308

ISBN-13: 9783319202303

This ebook constitutes the completely refereed and revised chosen papers from the tenth foreign Workshop on brokers and information Mining Interactions, ADMI 2014, held in Paris, France, in might 2014 as satellite tv for pc workshop of AAMAS 2014, the thirteenth overseas convention on self sufficient brokers and Multiagent Systems.

The eleven papers offered have been rigorously reviewed and chosen from various submissions for inclusion during this quantity. They current present examine and engineering effects, in addition to power demanding situations and clients encountered within the respective groups and the coupling among brokers and knowledge mining.

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Additional info for Agents and Data Mining Interaction: 10th International Workshop, ADMI 2014, Paris, France, May 5-9, 2014, Revised Selected Papers

Example text

Small but slow world: how network topology and burstiness slow down spreading. Phys. Rev. E. 83(2), 025102 (2011) 15. : Time-critical influence maximization in social networks with time-delayed diffusion process. In: Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, pp. 592–598 (2012) 16. : Scalable influence estimation in continuous-time diffusion networks. In: Advances in Neural Information Processing Systems, pp. 3147–3155 (2013) 17. : Multiplexity-facilitated cascades in networks.

We then continue to frame 2 and 3 and repeat process and so on. On each iteration we record the identified blob locations (as described in Sect. 4). Periodically it may be the case that a blob is lost, in which case we will stop recording locations, but continue the frame comparison process until the blobs are rediscovered. 42 4 M. Tufail et al. Learning Framework This section presents the proposed learning framework. 2 m2 floor area for the scenarios considered, the “playing area” in terms of the mouse behaviour MABS described in [2,3], was conceived of as a grid across which rats could be tracked.

Int. J. Comput. Inf. Syst. Ind. Manage. Appl. 5, 499–508 (2013) 9. : On combining classifiers. IEEE Trans. Pattern Anal. Mach. Intell. 20(3), 226–239 (1998) 10. : Ontological user profiling in recommender systems. ACM Trans. Inf. Syst. 22(1), 54–88 (2004) 11. : The AKT Manifesto (2001). doc 12. : Collective knowledge ontology user profiling for twitter - automatic user profiling. In: Proceedings of IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) 13. 5 Programs for Machine Learning.

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Agents and Data Mining Interaction: 10th International Workshop, ADMI 2014, Paris, France, May 5-9, 2014, Revised Selected Papers by Longbing Cao

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