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2018 | OriginalPaper | Chapter

Web Usage Data Cleaning

A Rule-Based Approach for Weblog Data Cleaning

Authors : Amine Ganibardi, Chérif Arab Ali

Published in: Big Data Analytics and Knowledge Discovery

Publisher: Springer International Publishing

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Abstract

This paper addresses the issue of Weblog Data cleaning within the scope of Web Usage Mining. Weblog data are information on end-user clicks and underlying user-agent hits recorded by webservers. Since Web Usage Mining is interested in end-user behavior, user-agent hits are referred to as noise to be cleaned before mining. The most referenced and implemented cleaning methods are the conventional and advanced cleaning. They are content-centric filtering heuristics, based on the requested resource attribute of the weblog database. These cleaning methods are limited in terms of relevancy, workability and cost constraints, within the context of dynamic and responsive web. In order to deal with dynamic and responsive web constraints, this contribution introduces a rule-based cleaning method focused on the logging structure rules. The rule-based cleaning method experimentation demonstrates significant advantages compared to the content-centric methods.

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Title: Web Usage Data Cleaning
Authors: Amine Ganibardi
Chérif Arab Ali
Publisher: Springer International Publishing
Book: Big Data Analytics and Knowledge Discovery
Print ISBN: 978-3-319-98538-1

Electronic ISBN: 978-3-319-98539-8

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-98539-8_15

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