Hybrid Data Aggregation Technique to Categorize the Web Users to Discover Knowledge About the Web Users

Hybrid Data Aggregation Technique to Categorize the Web Users to Discover Knowledge About the Web... Web usage mining is a knowledge discovery technique where a data analyst can discover useful information from the web users’ data. Web contains billions of web pages. The web access behaviour of one web user differs from that of another and also it changes with respect to their temporal property. By analyzing the users’ data, the web administrator can personalize the web pages according to individual web users’ interest. Personalizing the web page gives various advantages in this fast era such as low search time, less data transfer, higher availability of data, lower bandwidth traffic, targeted advertisement and identifying the threaded web users and high web users satisfaction. Due to the above advantages, it is very much essential in the present World Wide Web. Various algorithms, techniques and tools are available in the field of web usage mining. Although there are various techniques, algorithms and tools developed related to web usage mining, new techniques are required to make the discovery of knowledge more accurate. In this paper, a novel technique is proposed by using various methods such as web log, web ranking, web rating and web review based method to identify the success rate of various web pages and summarize the value to identify the accurate success rate of each web page. The success rate is normalized and aggregated into three categories for personalizing the web user. Personalizing the web user based on grouping relevant web access behaviour reduces the calculation complexity. It is very effective in very large websites. This technique is very much effective for analyzing the outreach of web advertisement to the web users. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Wireless Personal Communications Springer Journals

Hybrid Data Aggregation Technique to Categorize the Web Users to Discover Knowledge About the Web Users

Loading next page...
 
/lp/springer_journal/hybrid-data-aggregation-technique-to-categorize-the-web-users-to-J9Dabn0a02
Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media, LLC
Subject
Engineering; Communications Engineering, Networks; Signal,Image and Speech Processing; Computer Communication Networks
ISSN
0929-6212
eISSN
1572-834X
D.O.I.
10.1007/s11277-017-4779-x
Publisher site
See Article on Publisher Site

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

Monthly Plan

  • Read unlimited articles
  • Personalized recommendations
  • No expiration
  • Print 20 pages per month
  • 20% off on PDF purchases
  • Organize your research
  • Get updates on your journals and topic searches

$49/month

Start Free Trial

14-day Free Trial

Best Deal — 39% off

Annual Plan

  • All the features of the Professional Plan, but for 39% off!
  • Billed annually
  • No expiration
  • For the normal price of 10 articles elsewhere, you get one full year of unlimited access to articles.

$588

$360/year

billed annually
Start Free Trial

14-day Free Trial