Adaptive Distribution of Sensitive Informatio...

Adaptive Distribution of Sensitive Information in Online Social Networks

Author Name : M. Saraswathi, K. Venkat Gowtham, L. V. Subba Reddy

ABSTRACT

The Growth of increasing rapidly of social networking is supplementing the progression of cyber-bullying activities. The bulk of the people concerned in these activities belong to the younger generations, particularly teenagers who are the worst state of affairs are at a lot of risk of self destructive attempts thus propose an useful predator and victim identification with linguistics increased marginalized denoising auto-encoder approach to observe cyber-bullying message from social media through the consideration theme. Thus we have a tendency to propose Semantic-Enhanced Marginalized Denoising Auto-Encoder is developed via linguistics extension of fashionable deep learning model stack denoising auto-encoder. The linguistic extension consists of linguistics dropout noise and spareness constraints, wherever the linguistics dropout noise is supposed supported domain data and thus the word embedding technique. The experiment show effective of our approach.

Keywords: Cyber bullying detection, Social Networking, Illustration learning, Stacked Denoising Auto encoders, Word Embedding