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Web Mining: A Survey of Current Research, Techniques, and Software

2008, International Journal of Information Technology & Decision Making

The purpose of this paper is to provide a more current evaluation and update of web mining research and techniques available. Current advances in each of the three different types of web mining are reviewed in the categories of web content mining, web usage mining, and web structure mining. For each tabulated research work, we examine such key issues as web mining process, methods/techniques, applications, data sources, and software used. Unlike previous investigators, we divide web mining processes into the following five subtasks: (1) resource finding and retrieving, (2) information selection and preprocessing, (3) patterns analysis and recognition, (4) validation and interpretation, and (5) visualization. This paper also reports the comparisons and summaries of selected software for web mining. The web mining software selected for discussion and comparison in this paper are SPSS Clementine, Megaputer PolyAnalyst, ClickTracks by web analytics, and QL2 by QL2 Software Inc. Applicat...

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anurag kumar

Web Mining is moving the World Wide Web towards a more useful environment in which users can quickly and easily find the information they need. Large amount of text documents, multimedia files and images are available in the web and it is still increasing. Data mining is the form of extracting data’s available in the internet. Web mining is a part of data mining. Web mining is used to discover and extract information from Web-related data sources such as Web documents, Web content, hyperlinks and server logs. The term Web mining has been used in three distinct ways. The first, called Web content mining is the process of information discovery from sources across the World Wide Web. The second, called Web structure mining is the process of analyzing the relationship between Web pages linked by information or direct link connection through the use of graph theory. The third, called Web usage mining is the process of extracting patterns and information from server logs to gain insight on user activity. In this paper, we are trying to give a brief idea regarding web mining concerned with its techniques, tools and applications.

Richard Segall

Venkata Ramana

brijesh singh

Bonfring International Journal

Web is a platforms for information exchange, as it is simple and easy to publish documents. Searching for information becomes a difficult and time-consuming process as the web grows. Web mining uses various data mining techniques to discover useful knowledge from usage log file from the web. The mining tools are used to scan the HTML documents, images, and text, the results is provided for the search engines.It can assist search engines in providing productive results of each search in order of their relevance. In this paper, we brief introduction to the concepts related to web mining and then an overview of different Web usage mining.

Dr. M.A.Dorairangaswamy

This study presents the role of Web mining an explosive growth of the World Wide Web; websites are providing an information and knowledge to the end users. This is the review paper which show deep and intense study of various technologies available for web mining and it is the application of data mining techniques to extract knowledge from web. Current advances in each of the three different types of web mining are reviewed in the categories of web content mining, web usage mining, and web structure mining. Index Terms—web mining, web content mining, web usage mining, web structure mining.

aarti Pandey

Jawad Mughal

Research Publish Journals

Abstract: Web mining is a very hot research topic which combines two of the activated research areas: Data Mining and World Wide Web. The Web mining research relates to several research communities such as Database, Information Retrieval and Artificial Intelligence. Although there exists quite some confusion about the Web mining, the most recognized approach is to categorize Web mining into three areas: Web content mining, Web structure mining, and Web usage mining. Web content mining focuses on the discovery/retrieval of the useful information from the Web contents/data/documents, while the Web structure mining emphasizes to the discovery of how to model the underlying link structures of the Web. The distinction between these two categories isn't a very clear sometimes. Web usage mining is relative independent, but not isolated, category, which mainly describes the techniques that discover the user's usage pattern and try to predict the user's behaviors. This paper is a survey based on the recently published research papers. Besides providing an overall view of Web mining, this paper will focus on Web usage mining. Generally speaking, Web usage mining consists of three phases: Pre-processing, Pattern discovery and Pattern analysis. A detailed description will be given for each part of them, however, special attention will be paid to the user navigation patterns discovery and analysis. The user privacy is another important issue in this paper. An example of a prototypical Web usage mining system, WebSIFT, will be introduced to make it easier to understand the methodology of how to apply data mining techniques to large Web data repositories in order to extract usage patterns. Finally, along with some other interested research issues, a brief overview of the current research work in the area of Web usage mining is included. Title: WEB MINING AN APPLICATION OF DATA MINING Author: Sumit Dalal, Sumit Kumar, Vivek Dixit International Journal of Computer Science and Information Technology Research ISSN 2348-120X (online), ISSN 2348-1196 (print) Research Publish Journals

maithreyan surya

The World Wide Web is a popular and interactive medium to disseminate information today. It is a system of interlinked hypertext documents accessed via the Internet. With a web browser, one can view web pages that may contain text, images, videos, and other multimedia, and navigate between them via hyperlinks. With the recent explosive growth of the amount of content on the Internet, it has become increasingly difficult for users to find and utilize information and for content providers to classify and catalog documents on the World Wide Web. Traditional web search engines often return hundreds or thousands of results for a search, which is time consuming for users to browse. On-line libraries, search engines, and other large document repositories (e.g. customer support databases, product specification databases, press release archives, news story archives, etc.) are growing so rapidly that it is difficult and costly to categorize every document manually. To deal with these problems web mining is used. Web mining is the use of data mining techniques to automatically discover and extract information from the web documents and services. This paper presents an overview of web mining, its methodologies, algorithms and applications.

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An Overview on Web Usage Mining

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• G. Neelima 6 &
• Sireesha Rodda 7  

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 338))

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The prolific growth of web-based applications and the enormous amount of data involved therein led to the development of techniques for identifying patterns in the web data. Web mining refers to the application of data mining techniques to the World Wide Web. Web usage mining is the process of extracting useful information from web server logs based on the browsing and access patterns of the users. The information is especially valuable for business sites in order to achieve improved customer satisfaction. Based on the user’s needs, Web Usage Mining discovers interesting usage patterns from web data in order to understand and better serve the needs of the web based application. Web Usage Mining is used to discover hidden patterns from weblogs. It consists of three phases like Preprocessing, pattern discovery and Pattern analysis. In this paper, we present each phase in detail, the process of extracting useful information from server log files and some of application areas of Web Usage Mining such as Education, Health, Human-computer interaction, and Social media.

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Patel, K.B., Patel, A.R.: Process of Web Usage Mining to find Interesting Patterns from Web Usage Data. In: International Journal of Computers & Technology Volume 3(1) (August 2012)

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Mitharam, M.D.: Preprocessing in Web Usage mining. International Journal of Scientific & Engineering Research 3(2), 1 (2012) ISSN 2229-5518

Sharma, A.: Web Usage Mining: Data Preprocessing, Pattern Discovery and Pattern Analysis on the RIT Web Data

Chaudhary, K., Gupta, S.K.: Web Usage Mining Tools & Techniques: A Survey. International Journal of Scientific & Engineering Research 4(6), 1762 (2013) ISSN 2229-5518

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Chitraa, V., Davamani, A.S.: A Survey on Preprocessing Methods for Web Usage Data. International Journal of Computer Science and Information Security (IJCSIS) 7(3) (2010)

Pani, S.K., Panigrahy, L.: Web Usage Mining: A Survey on Pattern Extraction from Web Logs. International Journal of Instrumentation, Control & Automation (IJICA) 1(1) (2011)

Romero, C., Ventura, S., Zafra, A., de Bra, P.: Applying Web usage mining for personalizing hyperlinks in Web-based adaptive educational systems (received January 8, 2009) (received in revised form May 4, 2009) (accepted May 4, 2009)

Siau, K.: Health Care Informatics. IEEE Transactions on Information Technology in Biomedicine 7(1) (March 2003)

Geeta, R.B., Totad, S.G., Reddy, P.: Amalgamation of Web Usage Mining and Web Structure Mining. International Journal of Recent Trends in Engineering 1(2) (May 2009)

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Zhang, Y.: Web Information Systems Engineering and Internet Technologies. Springer Science+Business Media, LLC (2011)

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GMRIT, Rajam, Srikakulam, A.P, India

GITAM University, Visakhapatnam, A.P, India

Sireesha Rodda

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Correspondence to G. Neelima .

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Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Vishakapatnam, India

Suresh Chandra Satapathy

School of Information Technology, Jawaharlal Nehru Technological University Hyderabad, Hyderabad, India

A. Govardhan

Department of CSE, Computer Society of India, Hyderabad, India

K. Srujan Raju

University of Kalyanai, Kalyanai, West Bengal, India

J. K. Mandal

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Neelima, G., Rodda, S. (2015). An Overview on Web Usage Mining. In: Satapathy, S., Govardhan, A., Raju, K., Mandal, J. (eds) Emerging ICT for Bridging the Future - Proceedings of the 49th Annual Convention of the Computer Society of India CSI Volume 2. Advances in Intelligent Systems and Computing, vol 338. Springer, Cham. https://doi.org/10.1007/978-3-319-13731-5_70

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