Machine Learning Approach for User Accounts Identification with Unwanted Information and data

Main Article Content

Abhishek Kumar
TVM SAIRAM
https://orcid.org/0000-0003-2292-6210

Abstract

Machine Learning used for many real time issues in many organizations and for the purpose of social media analytics machine learning models is used most prominently and to identify the genuine accounts and the information in the social media we are her with a new pattern of identification. In this pattern of model we are proposing some words which are hidden to identify the accounts with fake data and the some of the steps we are proposing will be help to identify the fake and unwanted accounts in Facebook in an efficient manner. Clustering in machine learning will be used and in prior to that we are proposing an efficient architecture and the process flow which can identify the fake and suspicious accounts in the social media. This article will be on machine learning implementations and will be working on OSN (online social networks). Our work will be more on Facebook which is maintaining more amount of accounts and identifying which are over ruling the rules of privacy and protection of the user content. Machine learning supervised models will be used for text classification and the image classification is performed by CNN of unsupervised learning and the explanation will be given in the implementation phase

Article Details

How to Cite
Kumar, A., & SAIRAM, T. (2018). Machine Learning Approach for User Accounts Identification with Unwanted Information and data. International Journal of Machine Learning and Networked Collaborative Engineering, 2(03), 119-127. Retrieved from http://mlnce.net/index.php/Home/article/view/47
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