iosr-JCE   Volume-19 ~ Issue-4 ~ July-August 2017

Abstract:As technology has made an unprecedented change in world economy and professional preparation, India is rapidly advancing in the technological space. With the growing population and increasing Smartphone penetration, it is going mobile and digital. Smartphone and internet is not just for the rich and wealthy but more users are becoming informed by getting access of mobile internet. e-Governance is trying its level best to provide e-government services to citizens. But still there is need to reach these services to individual at their doorstep. So the looking at the current mobile age there is need for transforming e-governance services to m-Governance, which promises to bring the "anywhere-anytime-anybody" e-government service vision one step closer. It is in this way that this research intends to address variables that would facilitate the migration to m-governance model in a Higher Education Institution experiencing a very high growth and adoption of mobile communication technology............

Keyword: e-Governance; m-Governance, enabler and communication service. .

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Abstract: SentiT is an opinion analysis application for Twitter. Based on the keyword searched, SentiT collects tweets having to do with it , separates and labels them into the different polarity classes neutral, negative and positive , simultaneously we also categorize them into emotions which are anger, disgust, fear, joy, sadness, surprise .Our main objective is to prepare a system that takes real time data from the twitter and come to a conclusion about the opinion on particular product/keyword.

Keywords: Public opinion mining, Social media, Analysis Introduction

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Abstract: Recommender system is a growing proliferation in today online applications contributed to the problems of Information overloading. In a day to day life enormous amount of data is generated and collected leads to a problem of information overloading. This paper focuses on how to deal with the problem of information overloading and how to recommend an additional product to the end user using collaborative filtering (CF) recommendation algorithms. The personalized recommendation algorithm with their benefits and limitations are described. A pitfall occurs in CF recommendation system is described. An outline framework is proposed for the initial stage of recommendation...............

Keywords: Web Mining, Collaborative filtering, CF Algorithms, CF Framework, E-Commerce

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