17 Data Mining in Web Applications Julio Ponce 1 , Alberto Hernández 2 , Alberto Ochoa 4,5 , Felipe Padilla 3 , Alejandro Padilla 1 , Francisco Álvarez 1 and Eunice Ponce de León 1 1 Aguascalientes University, 2 CIICAp-UAEM, 3 UQAM, 4 Juarez City University 5 CIATEC 1,2,4,5 México 3 Canada 1. Introduction The World Wide Web is rapidly emerging as an important medium for commerce as well as for the dissemination of information related to a wide range of topics (e.g., business and government). According to most predictions, the majority of human information will be available on the Web. These huge amounts of data raise a grand challenge, namely, how to turn the Web into a more useful information utility (Garofalakis et al., 1999) . At the moment with the popularity of Internet, people are exhibited to a lot of information that is available for study. Nowadays there is also a great amount of applications and services that are available through Internet as they are seeking, chats, sales, etc., nevertheless much of that information is not useful for many people, but in the area of Data Mining, all the information available in the Internet represents a work opportunity and it is possible to do a lot of analysis on the basis of these with specific purposes. Knowledge Discovery and Data Mining are powerful data analysis tools. The rapid dissemination of these technologies calls for an urgent examination of their social impact. We show an overview of these technologies. The terms “Knowledge Discovery” and “Data Mining” are used to describe the ‘non-trivial extraction of implicit, previously unknown and potentially useful information from data (Wahlstrom & Roddick, 2000). Knowledge discovery is a concept that describes the process of searching on large volumes of data for patterns that can be considered knowledge about the data. The most well-known branch of knowledge discovery is data mining. 1.1 Data mining Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential. Data mining is a knowledge discovery process in large and complex data sets, refers to extracting or “mining” knowledge from large amounts of data. Moreover, data mining can be used to predict an outcome for a given entity (Hernández et al., 2006). Thus clustering algorithms in data mining are equivalent to the task of identifying groups of records that are similar between themselves but different from the rest. (Varan, 2006). Open Access Database www.intechweb.org Source: Data Mining and Knowledge Discovery in Real Life Applications, Book edited by: Julio Ponce and Adem Karahoca, ISBN 978-3-902613-53-0, pp. 438, February 2009, I-Tech, Vienna, Austria www.intechopen.com