Abstract

Data and web mining involves the use of data mining techniques to extract information from the web in order to gain insights into online behavior, customer preferences, and trends. The process requires data preprocessing to clean and prepare the data for analysis, and pattern recognition to identify relationships and patterns within the data. The benefits of data and web mining include improved decision-making and business growth, while challenges include the large volume of data and ensuring data quality. Web mining can be divided into three main categories: web content mining, web structure mining, and web usage mining. Web content mining involves extracting information from the content of web pages, such as text, images, and videos. Web structure mining involves analyzing the links between web pages to identify patterns and relationships. Web usage mining involves analyzing user behavior on the web, such as clickstream data and session logs, to extract useful information. KEYWORDS: data mining, web mining, information extraction, data preprocessing, pattern recognition, online behavior, customer preferences,

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