By Enrique Machuca, Lawrence Mandow, Lucie Galand (auth.), Concha Bielza, Antonio Salmerón, Amparo Alonso-Betanzos, J. Ignacio Hidalgo, Luis Martínez, Alicia Troncoso, Emilio Corchado, Juan M. Corchado (eds.)
This ebook constitutes the refereed complaints of the fifteenth convention of the Spanish organization for man made Intelligence, CAEPIA 20013, held in Madrid, Spain, in September 2013. The 27 revised complete papers awarded have been rigorously chosen from sixty six submissions. The papers are prepared in topical sections on Constraints, seek and making plans, clever net and knowledge retrieval, fuzzy platforms, wisdom illustration, reasoning and common sense, computing device studying, multiagent structures, multidisciplinary issues and functions, metaheuristics, uncertainty in synthetic intelligence.
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Extra resources for Advances in Artificial Intelligence: 15th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2013, Madrid, Spain, September 17-20, 2013. Proceedings
An on-demand video service) in a given moment, is thus an interesting challenge for the recommender systems research community. Previous work has shown that methods based on the analysis of temporal patterns of users are highly accurate in the above task when they use randomly sampled test data. However, such evaluation methodology may not properly deal with the evolution of the users’ preferences and behavior through time. In this paper we evaluate several methods’ performance using time-aware evaluation methodologies.
This kind of problems, and scalability related ones, will be more pronounced according to the reported growth in multimedia production and semantic metadata describing these new contents in the web of data. 3 Header-Dictionary-Triples (HDT) The HDT binary format  addresses the current needs of large RDF datasets for scalable publishing and exchanging in the Web of Data5 . HDT describes a binary serialization format for RDF that keeps large datasets compressed while maintaining search and browse operations.
Global top values in each column are in bold, and best values for each method are underlined. 9759 Conclusions and Future Work In this paper we have presented an empirical comparison of methods for active household member identification, evaluated under different methodologies previously applied on recommender systems evaluation. Given that the methods are based on exploiting temporal patterns, we included some time-aware evaluation methodologies in order to test the reliability of previously reported results.