SmartCityZen database

Citation Author(s):
Onsa
Lazzez
REGIM-Lab.: REsearch Groups in Intelligent Machines, ENIS, University of Sfax, Tunisia
Wael
Ouarda
REGIM-Lab.: REsearch Groups in Intelligent Machines, ENIS, University of Sfax, Tunisia
Adel M.
Alimi
REGIM-Lab.: REsearch Groups in Intelligent Machines, ENIS, University of Sfax, Tunisia
Submitted by:
Adel Alimi
Last updated:
Thu, 01/07/2021 - 11:19
DOI:
10.21227/9xt8-1f82
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Abstract 

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 SmartCityZen 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).

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