A Survey on Data Analytics for Personification using Machine Learning - P. Gawade, Prema (International Journal of Computer Sciences and Engineering, 2019)
With proliferation of the internet based media application; like SMS, video messaging, has resulted in a surge of data sharing. Applications like WhatsApp, Facebook, attracted large number of users because of easy chat conversations. WhatsApp is also used in small-scale industries for business purpose where user can write message is any language, in short form and understanding the context in chat is very important. There is no standard text which can be conventional machine understandable. Categorization can form personification; but there is lack of support to interpretation the content in the text messages with direct and indirect meaning. Map reduce framework can be used for transliteration process with frequent term visualization. Also messages can be with intuitive background where safety features are required to focus. Hence in this paper a survey for personification of embedded media data through the confluence of embedded media data analytic and machine learning techniques is proposed.