Welcome to the InfoSci Platform
Extracting Knowledge from Web Data

Extracting Knowledge from Web Data

Hanane Ezzikouri, Mohamed Fakir, Cherki Daoui, Mohamed Erritali
Copyright: © 2014 |Volume: 7 |Issue: 4 |Pages: 15
ISSN: 1938-7857|EISSN: 1938-7865|EISBN13: 9781466657717|DOI: 10.4018/jitr.2014100103
Cite Article Cite Article

MLA

Ezzikouri, Hanane, et al. "Extracting Knowledge from Web Data." JITR vol.7, no.4 2014: pp.27-41. http://doi.org/10.4018/jitr.2014100103

APA

Ezzikouri, H., Fakir, M., Daoui, C., & Erritali, M. (2014). Extracting Knowledge from Web Data. Journal of Information Technology Research (JITR), 7(4), 27-41. http://doi.org/10.4018/jitr.2014100103

Chicago

Ezzikouri, Hanane, et al. "Extracting Knowledge from Web Data," Journal of Information Technology Research (JITR) 7, no.4: 27-41. http://doi.org/10.4018/jitr.2014100103

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

The user behavior on a website triggers a sequence of queries that have a result which is the display of certain pages. The Information about these queries (including the names of the resources requested and responses from the Web server) are stored in a text file called a log file. Analysis of server log file can provide significant and useful information. Web Mining is the extraction of interesting and potentially useful patterns and implicit information from artifacts or activity related to the World Wide Web. Web usage mining is a main research area in Web mining focused on learning about Web users and their interactions with Web sites. The motive of mining is to find users' access models automatically and quickly from the vast Web log file, such as frequent access paths, frequent access page groups and user clustering. Through Web Usage Mining, several information left by user access can be mined which will provide foundation for decision making of organizations, Also the process of Web mining was defined as the set of techniques designed to explore, process and analyze large masses of consecutive information activities on the Internet, has three main steps: data preprocessing, extraction of reasons of the use and the interpretation of results. This paper will start with the presentation of different formats of web log files, then it will present the different preprocessing method that have been used, and finally it presents a system for “Web content and Usage Mining'' for web data extraction and web site analysis using Data Mining Algorithms Apriori, FPGrowth, K-Means, KNN, and ID3.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.