Title: WSOLINK: web structure outlier detection algorithm

Authors: Rachna Miglani

Addresses: Department of Computer Applications, Global Institute of Management and Emerging Technologies, 11 KM Stone, Sohian Khurd, Batala Road, Amritsar 143501, India

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.

Keywords: web structure outlier mining; web structure outliers; web outliers; web mining; web structure mining.

DOI: 10.1504/IJKWI.2016.084742

International Journal of Knowledge and Web Intelligence, 2016 Vol.5 No.4, pp.287 - 303

Received: 06 Feb 2016
Accepted: 23 Aug 2016

Published online: 25 Jun 2017 *

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