WSOLINK: web structure outlier detection algorithm
by Rachna Miglani
International Journal of Knowledge and Web Intelligence (IJKWI), Vol. 5, No. 4, 2016

Abstract: In this world of specialisation where everything is getting specialised, data warehouses and web mining techniques are also getting specialised. Web usage mining, web content mining, and web structure mining are various categories of web mining techniques depending upon the data to be mined. Apriori algorithm, FP growth algorithm, and average linear time algorithm are available to analyse the general access patterns in web server logs whereas WCOND-mine and signed with weight technique are web content outlier mining algorithms. However, no such algorithm is available to check the authenticity and availability of hyperlinks in the resultant web pages given by web search engines. The present research work aims at detection of outliers from the results of queries over web pages through web search engines.

Online publication date: Sun, 25-Jun-2017

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Knowledge and Web Intelligence (IJKWI):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com