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Modeling Decisions for Artificial Intelligence : 14th International Conference, MDAI 2017, Kitakyushu, Japan, October 18-20, 2017, Proceedings

معرفی کتاب «Modeling Decisions for Artificial Intelligence : 14th International Conference, MDAI 2017, Kitakyushu, Japan, October 18-20, 2017, Proceedings» نوشتهٔ Vicenç Torra,Yasuo Narukawa,Aoi Honda,Sozo Inoue (eds.)، منتشرشده توسط نشر Honda در سال 1057. این کتاب در فرمت pdf، زبان انگلیسی ارائه شده است.

This book constitutes the proceedings of the 14th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2017, held in Kitakyushu, Japan, in October 2017. The 18 revised full papers presented together with one invited paper and three abstracts of invited talks were carefully reviewed and selected from 30 submissions. Providing a forum for researchers to discuss models for decision and information fusion (aggregation operators) and their applications to AI, the papers are organized in topical sections on aggregation operators, fuzzy measures and integrals; clustering and classication; data privacy and security; data mining and applications. Front Matter ....Pages I-XVIII Front Matter ....Pages 1-1 Provenance and Privacy (Vicenç Torra, Guillermo Navarro-Arribas, David Sanchez-Charles, Victor Muntés-Mulero)....Pages 3-11 Front Matter ....Pages 13-13 Comparison of Risk Averse Utility Functions on Two-Dimensional Regions (Yuji Yoshida)....Pages 15-25 Symmetrization Methods for Aggregation Functions (Radko Mesiar, Andrea Stupňanová)....Pages 26-32 Event-Based Transformations of Capacities (Surajit Borkotokey, Radko Mesiar, Jun Li)....Pages 33-39 Pan-Integrals Based on Optimal Measures (Jun Li, Yao Ouyang, Minhao Yu)....Pages 40-50 Orness and Cardinality Indices for Averaging Inclusion-Exclusion Integrals (Aoi Honda, Simon James, Sutharshan Rajasegarar)....Pages 51-62 \(L_1\)-space for Sugeno Integral (Aoi Honda, Yoshiaki Okazaki)....Pages 63-73 Front Matter ....Pages 75-75 An Adaptation of the ML-kNN Algorithm to Predict the Number of Classes in Hierarchical Multi-label Classification (Thissiany Beatriz Almeida, Helyane Bronoski Borges)....Pages 77-88 On Fuzzy Clustering for Categorical Multivariate Data Induced by Polya Mixture Models (Yuchi Kanzawa)....Pages 89-102 Comparison of Fuzzy Co-clustering Methods in Collaborative Filtering-Based Recommender System (Tadafumi Kondo, Yuchi Kanzawa)....Pages 103-116 Front Matter ....Pages 117-117 Differentially Private Data Sets Based on Microaggregation and Record Perturbation (Jordi Soria-Comas, Josep Domingo-Ferrer)....Pages 119-131 A Methodology to Compare Anonymization Methods Regarding Their Risk-Utility Trade-off (Josep Domingo-Ferrer, Sara Ricci, Jordi Soria-Comas)....Pages 132-143 Session-Based Network Intrusion Detection Using a Deep Learning Architecture (Yang Yu, Jun Long, Zhiping Cai)....Pages 144-155 Front Matter ....Pages 157-157 A Hybrid Model of ARIMA and ANN with Discrete Wavelet Transform for Time Series Forecasting (Warut Pannakkong, Van-Nam Huynh)....Pages 159-169 A Novel Hybrid Model for Activity Recognition (Hela Sfar, Amel Bouzeghoub, Nathan Ramoly, Jérôme Boudy)....Pages 170-182 Constructing Document Vectors Using Kernel Density Estimates (Michael Mayo, Sean Goltz)....Pages 183-194 On Cell Detection System with User Interaction (Yoshitaka Maeda, Yasunori Endo, Sho Sanami)....Pages 195-206 A Fuzzy Colour Model Sensitive to the Context: Study Cases Using PRAGR and Logics (Zoe Falomir, Luis Gonzalez-Abril)....Pages 207-219 Joint Subjective Opinions (Magdalena Ivanovska, Audun Jøsang, Jie Zhang, Shuo Chen)....Pages 220-233 Back Matter ....Pages 235-235 This book constitutes the refereed proceedings of the 9th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2012, held in Girona, Catalonia, Spain, in November 2012. The 32 revised full papers were carefully reviewed and selected from 49 submissions and are presented with 4 plenary talks. The papers are organized in topical sections on aggregation operators, integrals, data privacy and security, reasoning, applications, and clustering and similarity.
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