With the ever-increasing and ever-changing flow of information available on the Web, information analysis has never been more important. Web text mining, which includes text categorization, text clustering, association analysis and prediction of trends, can assist us in discovering useful information in an effective and efficient manner. In this chapter, we have proposed a Web mining system that incorporates both online efficiency and off-line effectiveness to provide the “right” information based on users’ preferences. A Bi- Objective Fuzzy c-Means algorithm and information retrieval technique, for text categorization, clustering and integration, was employed for analysis. The proposed system is illustrated via a case involving the Web site marketing of mobile phones. A variety of Web sites exist on the Internet and a common type involves the trading of goods. In this type of Web site, the question to ask is: If we want to establish a Web site that provides information about products, how can we respond quickly and accurately to queries? This is equivalent to asking: How can we design a flexible search engine according to users’ preferences? In this study, we have applied data mining techniques to cope with such problems, by proposing, as an example, a Web site providing information on mobile phones in Taiwan. In order to efficiently provide useful information, two tasks were considered during the Web design phase. One related to off-line analysis: this was done by first carrying out a survey of frequent Web users, students between 15 and 40 years of age, regarding their preferences, so that Web customers’ behavior could be characterized. Then the survey data, as well as the products offered, were classified into different demand and preference groups. The other task was related to online query: this was done through the application of an information retrieval technique that responded to users’ queries. Based on the ideas above the remainder of the chapter is organized as follows: first, we present a literature review, introduce some concepts and review existing methods relevant to our study, then, the proposed Web mining system is presented, a case study of a mobile-phone marketing Web site is illustrated and finally, a summary and conclusions are offered.