• SHREEYA YASHWANT UNDALE
• DR. SANDEEP B. VANJALE

online social networks provide relevant information on users' opinions and posts on various topics. So Applications, such as monitoring and detection systems can collect and analyse this data. This paper study an information based system, which includes an emotional health monitoring system to detect users with possible psychological disorders specially depression and stress. Symptoms Of this psychological disorder are usually observed passively. In this situation, author argues that online social behaviour extraction offers an opportunity to actively identify psychological disorder at an early stage. It is hard to recognize the confusion in light of the fact that the mental components considered in standard symptomatic criteria survey can't be seen by the registers of online social exercises. Our methodology, New and creative for the act of psychological disorders. Location, it does so don't confide in the self-revelation of those mental factors through the surveys. Rather, propose an AI strategy that is recognition of psychological disorders. In informal organizations which misuses the highlights removed from interpersonal organization information for relate to exactness potential instances of confusion discovery. We perform an analysis of the characteristics and we also apply machine learning in large-scale data sets and analyse features of the two types of psychological disorders.

Sentiment analysis, knowledge personalization and customization, detection system, social networks, machine learning.

"Survey on Knowledge-Based Recommendation System Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 4, page no.122-124, April-2020, Available :http://www.jetir.org/papers/JETIR2004218.pdf

"Survey on Knowledge-Based Recommendation System Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 4, page no. pp122-124, April-2020, Available at : http://www.jetir.org/papers/JETIR2004218.pdf