World Journal of Engineering Research and Technology (WJERT) has indexed with various reputed international bodies like : Google Scholar , Index Copernicus , Indian Science Publications , SOCOLAR, China , International Institute of Organized Research (I2OR) , Cosmos Impact Factor , Research Bible, Fuchu, Tokyo. JAPAN , Scientific Indexing Services (SIS) , Jour Informatics (Under Process) , UDLedge Science Citation Index , International Impact Factor Services , International Scientific Indexing, UAE , International Society for Research Activity (ISRA) Journal Impact Factor (JIF) , International Innovative Journal Impact Factor (IIJIF) , Science Library Index, Dubai, United Arab Emirates , Scientific Journal Impact Factor (SJIF) , Science Library Index, Dubai, United Arab Emirates , Eurasian Scientific Journal Index (ESJI) , Global Impact Factor (0.342) , IFSIJ Measure of Journal Quality , Web of Science Group (Under Process) , Directory of Research Journals Indexing , Scholar Article Journal Index (SAJI) , International Scientific Indexing ( ISI ) , Scope Database , 

World Journal of Engineering
Research and Technology

( An ISO 9001:2015 Certified International Journal )

An International Peer Reviewed Journal for Engineering Research and Technology

ISSN 2454-695X

Impact Factor : 5.924

ICV : 79.45

News & Updation

  • Article Invited for Publication

    Article are invited for publication in WJERT Coming Issue

  • ICV

    WJERT Rank with Index Copernicus Value 79.45 due to high reputation at International Level

  • New Issue Published

    Its Our pleasure to inform you that, WJERT November 2022 Issue has been Published, Kindly check it on https://www.wjert.org/home/current_issues

  • WJERT New Impact Factor

    Its our Pleasure to Inform you that WJERT Impact Factor has been increased from  5.549 to 5.924 due to high quality Publication at International Level

  • WJERT: NOVEMBER ISSUE PUBLISHED

    NOVEMBER 2022 Issue has been successfully launched on 1 November 2022.

Indexing

Abstract

FOCUS-RRK FEATURE SELECTION TECHNIQUE FOR ENHANCING THE ACCURACY IN SOCIAL NETWORK DATA

Rajkumar Ramasamy*

ABSTRACT

Feature Selection is an effective technique in reducing the dimensionality of features in many applications where Online Social Network’s datasets involve hundreds or thousands of features. The raw data are usually with inferior qualities such as redundancy and unreliability. Mining raw data for a given task has proved to be deteriorating in efficiency. There are many algorithms in data mining which can be used in dealing with redundant or missing data. Before the mining process begins those instances with missing value are considered insignificant to the result and thus can be eliminated from the dataset. The purpose of this research paper is twofold: Identifying and removing the redundant features with their latest solutions for Consistency Measure in an Online Social Network.

[Full Text Article]