2013Unpublished venueRequires access

User Navigation Pattern Prediction using Longest Common Subsequence

Samir Shaikh, Pravin B. Landage, D. B. Kshirsagar

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Abstract

Web mining applies the data mining, the artificial intelligence and the chart technology and so on to the web data and traces users ' visiting characteristics, and then extracts the users’ using pattern. Web mining technologies are the right solutions for knowledge discovery on the Web. The knowledge extracted from the Web can be used to raise the performances for Web information retrievals, question answering, and Web based data warehousing. In this paper, I provide an introduction of Web mining as well as a review of the Web mining categories. Web mining applies the data mining, the artificial intelligence and the chart technology and so on to the web data. And traces users ' visiting characteristics, and then extracts the users ' navigation pattern. Web mining has quickly become one of the most important areas in Computer and Information Sciences because of its direct applications in ecommerce, e-CRM, Web analytics, information retrieval and filtering, and Web information systems. General Terms Longest common subsequence algorithm, Graph partitioning algorithm.

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What this paper is about

Web mining applies the data mining, the artificial intelligence and the chart technology and so on to the web data and traces users ' visiting characteristics, and then extracts the users’ using pattern. Web mining technologies are the right solutions for knowledge discovery on the Web. The knowledge extracted from the Web can be used to raise the performances for Web information retrievals, question answering, and Web based data warehousing. In this paper, I provide an introduction of Web mining as well as a review of the Web mining categories. Web mining applies the data mining, the artificial intelligence and the chart technology and so on to the web data. And traces users ' visiting characteristics, and then extracts the users ' navigation pattern. Web mining has quickly become one of the most important areas in Computer and Information Sciences because of its direct applications in ecommerce, e-CRM, Web analytics, information retrieval and filtering, and Web information systems. General Terms Longest common subsequence algorithm, Graph partitioning algorithm.

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Available abstract

Web mining applies the data mining, the artificial intelligence and the chart technology and so on to the web data and traces users ' visiting characteristics, and then extracts the users’ using pattern. Web mining technologies are the right solutions for knowledge discovery on the Web. The knowledge extracted from the Web can be used to raise the performances for Web information retrievals, question answering, and Web based data warehousing. In this paper, I provide an introduction of Web mining as well as a review of the Web mining categories. Web mining applies the data mining, the artificial intelligence and the chart technology and so on to the web data. And traces users ' visiting characteristics, and then extracts the users ' navigation pattern. Web mining has quickly become one of the most important areas in Computer and Information Sciences because of its direct applications in ecommerce, e-CRM, Web analytics, information retrieval and filtering, and Web information systems. General Terms Longest common subsequence algorithm, Graph partitioning algorithm.

Key concepts: Web mining, Web intelligence, Computer science, Web analytics, Data Web, Web modeling, Web mapping, World Wide Web

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