2010Unpublished venueRequires access

AN IMPLEMENTATION OF WEB PERSONALIZATION USING WEB MINING TECHNIQUES

A. Jebaraj Ratnakumar

Open publisher page 24 citations

Abstract

Web mining is the application of data mining techniques to extract knowledge from Web. Web mining has been explored to a vast degree and different techniques have been proposed for a variety of applications that includes Web Search, Classification and Personalization etc. Most research on Web mining has been from a ‘data-centric’ point of view. In this paper, we highlight the significance of studying the evolving nature of the Web personalization. Web usage mining is used to discover interesting user navigation patterns and can be applied to many real-world problems, such as improving Web sites/pages, making additional topic or product recommendations, user/customer behavior studies, etc. A Web usage mining system performs five major tasks: i) data gathering, ii) data preparation, iii) navigation pattern discovery, iv) pattern analysis and visualization, and v) pattern applications. Each task is explained in detail and its related technologies are introduced. The Web mining research is a converging research area from several research communities, such as Databases, Information Retrieval and Artificial Intelligence. In this paper we implement how Web mining techniques can be apply for the Customization i.e Web personalization.

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What this paper is about

Web mining is the application of data mining techniques to extract knowledge from Web. Web mining has been explored to a vast degree and different techniques have been proposed for a variety of applications that includes Web Search, Classification and Personalization etc. Most research on Web mining has been from a ‘data-centric’ point of view. In this paper, we highlight the significance of studying the evolving nature of the Web personalization. Web usage mining is used to discover interesting user navigation patterns and can be applied to many real-world problems, such as improving Web sites/pages, making additional topic or product recommendations, user/customer behavior studies, etc. A Web usage mining system performs five major tasks: i) data gathering, ii) data preparation, iii) navigation pattern discovery, iv) pattern analysis and visualization, and v) pattern applications. Each task is explained in detail and its related technologies are introduced. The Web mining research is a converging research area from several research communities, such as Databases, Information Retrieval and Artificial Intelligence. In this paper we implement how Web mining techniques can be apply for the Customization i.e Web personalization.

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OpenAlex reports 24 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Web mining is the application of data mining techniques to extract knowledge from Web. Web mining has been explored to a vast degree and different techniques have been proposed for a variety of applications that includes Web Search, Classification and Personalization etc. Most research on Web mining has been from a ‘data-centric’ point of view. In this paper, we highlight the significance of studying the evolving nature of the Web personalization. Web usage mining is used to discover interesting user navigation patterns and can be applied to many real-world problems, such as improving Web sites/pages, making additional topic or product recommendations, user/customer behavior studies, etc. A Web usage mining system performs five major tasks: i) data gathering, ii) data preparation, iii) navigation pattern discovery, iv) pattern analysis and visualization, and v) pattern applications. Each task is explained in detail and its related technologies are introduced. The Web mining research is a converging research area from several research communities, such as Databases, Information Retrieval and Artificial Intelligence. In this paper we implement how Web mining techniques can be apply for the Customization i.e Web personalization.

Key concepts: Web mining, Web intelligence, Computer science, Web modeling, Data Web, World Wide Web, Personalization, Web navigation

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