Zhiyong Zhang, Constantinos Patsakis, Athanasios Zigomitros, Achilleas Papageorgiou, Agusti Solanas, Hui Zhu, Cheng Huang, Hui Li, Hong Zhu, Shengli Tian, Kevin Lü, WeiTao Song, Bin Hu, Bin Yang, Xingming Sun, Xianyi Chen, Jianjun Zhang, Xu Li, Ayesha Kanwal, Rahat Masood, Muhammad Awais Shibli, Rafia Mumtaz, Qingqi Pei, Dingyu Yan, Lichuan Ma, Zi Li, Yang Liao, Zhen Yang, Kaiming Gao, Kefeng Fan, Yingxu Lai, Hui Lin, Jia Hu, Jianfeng Ma, Li Xu, Li Yang, Kanliang Wang

Artificial Intelligence Research and Development 131 (41),

Description: Page 1. CONTENTS SPECIAL FOCUS ON SECURITY, TRUST AND RISK IN MULTIMEDIA SOCIAL NETWORKS 515 Security, Trust and Risk in Multimedia Social Networks Zhiyong Zhang 518 Privacy and Security for Multimedia Content shared on OSNs: Issues and Countermeasures Constantinos Patsakis, Athanasios Zigomitros, Achilleas Papageorgiou and Agusti Solanas 536 Information Diffusion Model Based on Privacy Setting in Online Social Networking Services Hui Zhu, Cheng Huang and Hui Li 549 Privacy-Preserving Data Publication with Features of Independent ?-Diversity Hong Zhu, Shengli Tian and Kevin Lü 572 Approach to Detecting Type-Flaw Attacks Based on Extended Strand Spaces WeiTao Song and Bin Hu 588 Exposing Photographic Splicing by Detecting the Inconsistencies in Shadows Bin Yang, Xingming Sun, Xianyi Chen, Jianjun Zhang and Xu Li

Agusti Solanas, Enrique Romero, Sergio Gómez, Josep M Sopena, Rene Alquézar, Josep Domingo-Ferrer

Artificial Intelligence Research and Development 131 (41),

Description: This paper presents a new feature selection method and an outliers detection algorithm. The presented method is based on using a genetic algorithm combined with a problem-specific-designed neural network. The dimensional reduction and the outliers detection makes the resulting dataset more suitable for training neural networks. A comparative analysis between different kind of proposed criteria to select the features is reported. A number of experimental results have been carried out to demonstrate the usefulness of the presented technique.

Josep Maria Mateo Sanz, Agusti Solanas, Josep Domingo

Artificial Intelligence Research and Development 131 (41),

Description: Se propone un método de posprocesado sobre la microagregación de un conjunto multivariable de microdatos con la particularidad de que los grupos resultantes pueden tener cardinalidades diferentes según la suma de cuadrados entre grupos que provoque la agrupación de los registros. El método se basa en la reasignación de los registros que provocan una suma de cuadrados alta.

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