SmartCityZen database

Social images analysis from social networks is considered as one of the most popular social technologies. Social images analysis is an active research topic in recent years and in order to promotes social images’s analysis research, the REGIM-Lab.: REsearch Groups in Intelligent Machines, ENIS, University of Sfax, Tunisia provides the Sm@rtCityZen social images database freely of charge to social images analysis researchers.The SmartCityZen database was developed to advance the research and development of Social visual data analysis for users interest discovery systems. The social visual data is from 240 Facebook accounts that contains male and female users, multiple ethnicity like Africans and European users in various locations and ages betweeen 15 and 60 years old. This database is composed of 24 files corresponding to the 24 topics of interest predefined by Facebook and each file contains 10 Facebook accounts. A pre-label assigned to each file consists of the topic of interest that the 10 users are interested in according to a voluntary filing of the big interest questionnaire (BI).All documents and papers that uses the REgim Sfax Tunisian hand database (REST database) will acknowledge the use of the database by including an appropriate citation to the following:[1] Onsa Lazzez, Wael Ouarda, and Adel M. Alimi. "Understand me if you can! Global soft biometrics recognition from social visual data." In International Conference on Hybrid Intelligent Systems, pp. 527-538. Springer, Cham, 2016.[2] Onsa Lazzez, Wael Ouarda, and Adel M. Alimi. "Age, gender, race and smile prediction based on social textual and visual data analyzing." In International Conference on Intelligent Systems Design and Applications, pp. 206-215. Springer, Cham, 2016.[3] Onsa Lazzez, Wael Ouarda, and Adel M. Alimi. "DeepVisInterests: CNN-Ontology Prediction of Users Interests from Social Images." arXiv preprint arXiv:1811.10920 (2018).

社交网络社交图像分析被视为最热门的社交技术之一。近年来，社交图像分析是一个活跃的研究课题。为推动该领域的研究发展，隶属于突尼斯斯法克斯大学ENIS学院的REGIM实验室（REGIM-Lab.，智能机器研究小组，REsearch Groups in Intelligent Machines），向社交图像分析研究者免费开放Sm@rtCityZen社交图像数据库（Sm@rtCityZen）。Sm@rtCityZen数据库旨在推动面向用户兴趣发现系统的社交视觉数据分析研究与开发。该社交视觉数据源自240个Facebook账号，涵盖男女用户，包含非洲、欧洲等多个族裔群体，用户分布于不同地区，年龄介于15至60岁之间。该数据库包含24个数据文件，对应Facebook预先定义的24个兴趣主题，每个文件包含10个Facebook账号。每个文件均被赋予预标注，该标注对应10名用户通过自愿填写大兴趣问卷（Big Interest Questionnaire，BI）所申报的兴趣主题。所有使用REGIM突尼斯斯法克斯手图像数据库（REST database）的文档与论文，均需通过引用以下文献以明确致谢该数据库的使用：[1] Onsa Lazzez、Wael Ouarda及Adel M. Alimi. "Understand me if you can! Global soft biometrics recognition from social visual data." 收录于《混合智能系统国际会议》，第527-538页，施普林格·沙姆，2016年。[2] Onsa Lazzez、Wael Ouarda及Adel M. Alimi. "Age, gender, race and smile prediction based on social textual and visual data analyzing." 收录于《智能系统设计与应用国际会议》，第206-215页，施普林格·沙姆，2016年。[3] Onsa Lazzez、Wael Ouarda及Adel M. Alimi. "DeepVisInterests: CNN-Ontology Prediction of Users Interests from Social Images." arXiv预印本，arXiv:1811.10920，2018年。