Due to the significant growth of social networking and human activities through the web in recent years, attention to analyzing big data using real-time crowdsourcing has increased. This data may appear in the form of streaming images, audio or videos. In this paper, we address the problem of deciding the appropriateness of streaming videos in public media with the help of crowdsourcing in real-time.
@article{arxiv.1708.09654,
title = {Identifying Unsafe Videos on Online Public Media using Real-time Crowdsourcing},
author = {Sankar Kumar Mridha and Braznev Sarkar and Sujoy Chatterjee and Malay Bhattacharyya},
journal= {arXiv preprint arXiv:1708.09654},
year = {2017}
}
Comments
Works-in-Progress, Fifth AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2017), Quebec City, Canada