Web Data mining-A Research area in Web usage mining

Web usage mining techniques and applications across industries is still exploratory and, despite an increase in academic research, there are challenge of analyze web which quantitatively capture web users' common interests and characterize their underlying tasks. This chapter addresses the problem of how to support web usage mining techniques and applications across industries by combining language of web pages and algorithms that used in web data mining. Existing research in web usage mining techniques tend to focus on finding out how each techniques can apply in different industries fields. However, there is little evidence that researchers have approached the issue of web usage mining across industries. Consequently, the aim of this chapter is to provide an overview of how the web usage mining techniques and applications across industries can be supported.

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Effectiveness of Web Usage Mining Techniques in Business Application

The Dark Web ◽

10.4018/978-1-5225-3163-0.ch011 ◽

2018 ◽

pp. 227-253

Author(s):

Ahmed El Azab ◽

Mahmood A. Mahmood ◽

Abd El-Aziz

Keyword(s):

Data Mining ◽

Academic Research ◽

Web Usage Mining ◽

Web Pages ◽

Web Data ◽

Web Data Mining ◽

Web Usage ◽

Business Application ◽

Common Interests ◽

The Web

Web usage mining techniques and applications across industries is still exploratory and, despite an increase in academic research, there are challenge of analyze web which quantitatively capture web users' common interests and characterize their underlying tasks. This chapter addresses the problem of how to support web usage mining techniques and applications across industries by combining language of web pages and algorithms that used in web data mining. Existing research in web usage mining techniques tend to focus on finding out how each techniques can apply in different industries fields. However, there is little evidence that researchers have approached the issue of web usage mining across industries. Consequently, the aim of this chapter is to provide an overview of how the web usage mining techniques and applications across industries can be supported.

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First Look on Web Mining Techniques to Improve Business Intelligence of E-Commerce Applications

Advances in Business Information Systems and Analytics - Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence ◽

10.4018/978-1-5225-2031-3.ch018 ◽

2017 ◽

pp. 298-314 ◽

Cited By ~ 2

Author(s):

G. Sreedhar ◽

A. Anandaraja Chari

Keyword(s):

Data Mining ◽

Web Mining ◽

Web Content ◽

Web Data ◽

Web Data Mining ◽

Useful Knowledge ◽

Web Usage ◽

Web Structure ◽

Web Structure Mining ◽

Content Mining

Web Data Mining is the application of data mining techniques to extract useful knowledge from web data like contents of web, hyperlinks of documents and web usage logs. There is also a strong requirement of techniques to help in business decision in e-commerce. Web Data Mining can be broadly divided into three categories: Web content mining, Web structure mining and Web usage mining. Web content data are content availed to users to satisfy their required information. Web structure data represents linkage and relationship of web pages to others. Web usage data involves log data collected by web server and application server which is the main source of data. The growth of WWW and technologies has made business functions to be executed fast and easier. As large amount of transactions are performed through e-commerce sites and the huge amount of data is stored, valuable knowledge can be obtained by applying the Web Mining techniques.

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Extracting Knowledge from Web Data

Journal of Information Technology Research ◽

10.4018/jitr.2014100103 ◽

2014 ◽

Vol 7 (4) ◽

pp. 27-41

Author(s):

Hanane Ezzikouri ◽

Mohamed Fakir ◽

Cherki Daoui ◽

Mohamed Erritali

Keyword(s):

Web Mining ◽

User Behavior ◽

Data Extraction ◽

Research Area ◽

Web Usage Mining ◽

Web Data ◽

Main Research ◽

Web Log ◽

Web Usage ◽

Log File

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.

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World Wide Web Usage Mining

Encyclopedia of Data Warehousing and Mining ◽

10.4018/978-1-59140-557-3.ch234 ◽

2011 ◽

pp. 1242-1248 ◽

Cited By ~ 3

Author(s):

Wen-Chen Hu ◽

Hung-Jen Yang ◽

Chung-wei Lee ◽

Jyh-haw Yeh

Keyword(s):

Data Mining ◽

World Wide Web ◽

World Wide ◽

Data Gathering ◽

Web Usage Mining ◽

Web Data ◽

Mining System ◽

Data Mining Techniques ◽

Web Usage ◽

Content Mining

World Wide Web data mining includes content mining, hyperlink structure mining, and usage mining. All three approaches attempt to extract knowledge from the Web, produce some useful results from the knowledge extracted, and apply the results to certain real-world problems. The first two apply the data mining techniques to Web page contents and hyperlink structures, respectively. The third approach, Web usage mining (the theme of this article), is the application of data mining techniques to the usage logs of large Web data repositories in order to produce results that can be applied to many practical subjects, such as improving Web sites/pages, making additional topic or product recommendations, user/customer behavior studies, and so forth. This article provides a survey and analysis of current Web usage mining technologies and systems. A Web usage mining system must be able to perform five major functions: (i) data gathering, (ii) data preparation, (iii) navigation pattern discovery, (iv) pattern analysis and visualization, and (v) pattern applications. Many Web usage mining technologies have been proposed, and each technology employs a different approach. This article first describes a generalized Web usage mining system, which includes five individual functions. Each system function is then explained and analyzed in detail. Related surveys of Web usage mining techniques also can be found in Hu, et al. (2003) and Kosala and Blockeel (2000).

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