Companies and individuals are increasingly using the internet for business and personal transactions. Web data mining tools and techniques are used to identify patterns and improve customer service. Techniques include web content mining, web usage mining, and web structure mining. Data mining association analysis and regression are also used to predict future outcomes. Data mining software vendors offer tools to extract predictive information from large datasets.
More than ever before, both entities and individuals are using the World Wide Web to conduct a variety of business and personal transactions. As a result, companies are increasingly using web data mining tools and techniques to find ways to improve their bottom line and grow their customer base. Web data mining involves the process of gathering and summarizing data from a website’s hyperlink structure, page content, or usage log to identify patterns. Using web data mining, a business can identify a potential competitor, improve customer service, or meet customer needs and expectations. A government agency may also seek to uncover terrorist threats or other criminal activity through the use of a web data mining application.
Some common web data mining techniques include web content mining, web usage mining, and web structure mining. Web content mining examines the subject matter of a website. For example, miners of web content can analyze the audio, text, images and video features of a site. Web content miners typically focus on a site’s textual information more than other site features. Natural language processing and information retrieval are two data mining techniques often used by web content miners.
Web usage mining is typically an automated process whereby web servers collect and report user access patterns in server access logs. For example, a business might use a web usage data mining tool to report server access logs and user registration information in order to create a more effective website design. Web structure mining studies the node and connection structure of websites. It can be useful in identifying similarities and relationships that exist between different websites. Web structure mining often involves discovering patterns from hyperlinks or the extracting document structures on a web page.
Two general data mining techniques that can be employed by web data miners are data mining association analysis and data mining regression. Data mining association analysis helps uncover noteworthy relationships buried in large datasets. Data mining regression is a statistical technique whereby mathematical formulas are used to predict future outcomes, such as profit margins, home values, or sales figures.
Data mining software vendors offer web data mining tools that can extract predictive information from large amounts of data. Companies often use these software mining tools to analyze specific datasets related to consumer behavior. Using the results of data analysis, companies are able to predict future business trends.
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