Computational Collective Intelligence. Technologies and by Andrea Omicini, Pierluigi Contucci (auth.), Costin Bǎdicǎ,

By Andrea Omicini, Pierluigi Contucci (auth.), Costin Bǎdicǎ, Ngoc Thanh Nguyen, Marius Brezovan (eds.)

This ebook constitutes the completely refereed convention lawsuits of the fifth overseas convention on Computational Collective Intelligence, ICCCI 2013, held in Craiova, Romania, in September 2013. The seventy two revised complete papers provided have been conscientiously chosen from a variety of submissions. convention papers are equipped in sixteen technical periods, protecting the next themes: clever e-learning, category and clustering tools, internet intelligence and interplay, brokers and multi-agent structures, social networks, clever wisdom administration, language processing structures, modeling and optimization concepts, evolutionary computation, clever and workforce determination making, swarm intelligence, facts mining strategies and purposes, cooperative challenge fixing, collective intelligence for textual content mining and innovation, collective intelligence for social figuring out and mining, and delicate tools in collective intelligence.

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Extra resources for Computational Collective Intelligence. Technologies and Applications: 5th International Conference, ICCCI 2013, Craiova, Romania, September 11-13, 2013, Proceedings

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4 Experiments and Evaluation In order to evaluate the performance of the TBRSS (our proposed method) in collaboration recommendation, we used the accuracy of link prediction in coauthor network. Our experiments were done with a co-author network extract and built from the DBLP. 1 Dataset We use the DBLP dataset downloaded in Oct. 2012 to build co-author network and study the performance of different measures in terms of their ability to predict link. Specifically, we use 11 years of dataset, from 2001 to 2011.

A Hybrid Web Recommender System Based on Cellular Learning Automata. In: Proceedings of IEEE International Conference on Granular Computing, pp. 453–458 (2010) 28. : Social Network Analysis. Cambridge University Press, New York (1994) 29. : Social network analysis: Methods and applications. Cambridge University Press, New York (1994) 30. : A New Kind of Science. Wolfram Media, Champaign (2002) 31. : Theory and Applications of Cellular Automata. pl Abstract. Modelling the diffusion of information is one of the key areas related to activity within social networks.

That said that prediction for near future is easier than far future prediction (figure 2). 5 Conclusion and Future Work The objective of this research is to implement and evaluate a new method based on combining probability theory and graph theory, in addiction with the relation trend factor for analysing co-author networks, to recommend collaboration for computer science researchers. Our proposed method was empirically tested using a dataset of publications extracted from the DBLP in 11 years (from 20012011).

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