Enhanced Scalable Learning for Identifying and Ranking for Big Data Using Social Media Factors

Abstract

In this paper describe a valuable information from online sources has become a prominent research area in information technology in recent years. In recent period, social media services provide a vast amount of user-generated data, which have great potential to contain informative news-related content. For these resources to be useful, must find a way to filter noise and only capture the content that, based on its similarity to the news media is considered valuable. In addition, the project includes a new concept called sentiment analysis. Since many automated prediction methods exist for extracting patterns from sample cases, these patterns can be used to classify new cases. The proposed system contains the method to transform these cases into a standard model of features and classes. As a result, the behavior of individuals is collected through their posts in a forum and then they are classified as positive/negative posts. The cases are encoded in terms of features in some numerical form, requiring a transformation from text to numbers and assign the positive and negative values to each word to classify the word in the document.

Authors and Affiliations

Preethi L, Dr. Periyasamy S

Keywords

Related Articles

Simulation of Dynamic Load Balancing Algorithms 

Cloud computing is a new technology which uses virtual machines instead of physical machines to host, store and network different components. Load balancing is a methodology to distribute workload across multiple compute...

Improved BSP Clustering Algorithm for Social Network Analysis

Social network analysis is a new research field in data mining. Social network analysis is the study of social networks to recognize the structure and behavior of friends. Social network analysis views social relationshi...

An Overview of Applications of Big Data Analytics

In recent years, the volume, variety and velocity of data is increased in all the applications. To discover information from large volume of data is a challenging task. Big Data Analytics helps to find useful information...

Secure Sharing of Sensitive Data on a Big Data Platform

Clients store immense measures of delicate information on a major information stage. Sharing touchy information will help ventures decrease the expense of giving clients customized benefits and offer some incentive inclu...

Provisioning of Data Security for File Transformation on Multi Cloud Storage

In file transformation utilizing proxy re-signatures, once a user in the group is revoked; the data cloud server is able to re-sign the blocks, which were signed by the revoked user, with a resigning key. As a result, th...

Download PDF file
  • EP ID EP405029
  • DOI 10.9756/BIJSESC.8386
  • Views 128
  • Downloads 0

How To Cite

Preethi L, Dr. Periyasamy S (2018). Enhanced Scalable Learning for Identifying and Ranking for Big Data Using Social Media Factors. Bonfring International Journal of Software Engineering and Soft Computing, 8(1), 31-35. https://europub.co.uk/articles/-A-405029