In the past, business owners were able to meet their customers and remember their wants and needs. Because of advances in technology, the Internet is now a major component of conducting business. While this creates many positive advantages, it is also more difficult for business owners and executives to determine the wants and needs of consumers.
Data mining as used in web personalization allows business owners to concentrate on solving many problems and making e-commerce more of a viable business option. One of the goals of web personalization can be to convert potential buyers into buyers by personalizing and customizing web site structure and content. Web site design and usability can be greatly improved by using web personalization. The personalization process uses information that can change the structure and content and generate better results. Web personalization can also improve customer loyalty by providing content that is targeted to consumer wants and needs.
Another goal for web personalization is to increase cross-selling by changing the structure and layout of sites as suggested by data mining. This can be accomplished by using information to suggest additional purchases to complement user tastes and preferences. Finally, web personalization can also be used to help individual users quickly find content that they will be able to use quickly.
Components of Web Personalization
There are several components necessary for successful web personalization. These components include categorizing and preprocessing web site data, extracting existing correlations between and across these data sets, and finally, determining the actions that should be taken by the system based on recommendations by the web personalization system (Mobasher, et al., 2000). In addition, there are four types of web data that can be collected and used for web personalization. Content data can include text, pictures, or database information. User profile data gives information about the users of a particular site. This can include operating system information, age, race, country of origin, ethnicity, education, and user preferences. Usage data describes how visitors used a web site and can include file accession logs, IP addresses, peak access times, and the addresses of referring web sites. Finally, structure data show how web site content is organized. This can include metatags, hyperlinks from one page to another, and the type of file format used on the web page (Srivastava, et. al., 2000).
Web personalization can be categorized into four distinct classes, the first class being the most simple and the fourth class being the most complex. Memorization is the simplest category of web personalizati