Mapreduce in Social Networking with Smart Education System using Machine Learning

Abstract

One of the marvels of the today’s world which is
shaping the future, is the worldwide accessibility to the internet.
There are around 7.2 billion people in the world out of which
there are about 3.1 billion active internet users out of which 65%
of the users devote it towards social networking & majority of
them are students from the age group of 16-30 [1]. If this
developing thoughts are targeted specifically towards informative
& academic actions keeping the same social networking
environment in the background would create interest in students
for educational activities and also develop productive reports.
Using Big Data analytics, machine learning and recommender
system on the pupils data and activity would nurture them with
useful information and suggestions which would help them yield
knowledge and make them choose their future in right resolution.
This can be implemented by creating a social -cum-educational
portal with recommender systems, also data can be generated
and displayed on the same place after analysis through
recommenders. There is a humongous quantity of social,
educational data being generated at a great rate on the web
which can be examined and used for the betterment of the
students and also the analysed information can be delivered to
the students based on their interests. Particular information to
particular student can be provided. Use of such a system will
strengthen the educational activities amongst students that would
lead to maximize their success ratio! However, most of the
existing Social Recommender systems do not have good
extensibility which are unable to process huge volumes of data.
Aiming to this problem we can design a social recommender
system based on Hadoop and its parallel computing platform.