Paper Title

Big Data Approach to Enhancing Quality of Web Application Contents

Authors

Swapna Sahu , Mr Anuj kumar Pal

Keywords

Big data, Web Mining, Web Usage, Hadoop.

Abstract

In this paper we propose a technique for selecting big data approach since it enhances the quality of web contents. Big data is a technique for data sets that are so compound that conventional data processing application software is not enough to deal with them. Study of server log data can provide noteworthy and useful information. Information provided can help to find out user perception. This can improve the effectiveness of the Web sites by adapting the information structure to the users’ behavior. The several web usage mining methods for extracting useful features is discussed and employ all these techniques to cluster the users of the domain to study their behaviours comprehensively. The goal of this project is to create a application that can able to give web log access information and store in a sophisticated way which is use to analyze user behaviour by mining enriched web access log data using BIG DATA HADOOP technology. The contributions of this research are a data enrichment that is content and source based and a tree-like visualization of frequent navigational sequences.

How To Cite

"Big Data Approach to Enhancing Quality of Web Application Contents", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.2, Issue 7, page no.162 - 167, July-2017, Available :https://ijsdr.org/papers/IJSDR1707023.pdf

Issue

Volume 2 Issue 7, July-2017

Pages : 162 - 167

Other Publication Details

Paper Reg. ID: IJSDR_170609

Published Paper Id: IJSDR1707023

Downloads: 000347168

Research Area: Engineering

Country: Bhilai, Chhattisgarh, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR1707023

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR1707023

About Publisher

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

Article Preview

academia
publon
sematicscholar
googlescholar
scholar9
maceadmic
Microsoft_Academic_Search_Logo
elsevier
researchgate
ssrn
mendeley
Zenodo
orcid
sitecreex