Data Mining Based Soft Computing Methods For Web Intelligence

Abstract

Data mining is the procedure of extracting interesting knowledge from enormous amounts of data contained in databases, including such patterns, associations, changes, deviations, and prominent structures. Soft Computing Methods such as fuzzy logic, artificial neural network, etc. aims to uncover the potential for error and inaccuracy in order to accomplish scalability, durability, and reduced methods. In today's information age, the Web is the most common distribution medium. Due to its popularity on the Internet, it is widely used in commercial, entertainment, and educational purposes. Web Intelligence (WI) is engaged with the scientific study of the Web's new areas. It is a new area of computer science that integrates artificial intelligence with sophisticated information technology in the framework of the Web, expanding well outside each one of them. In online applications, data mining gives a plethora of possibilities. The biggest concern is figuring out how to identify relevant hidden patterns for improved application. Soft computing techniques such as neural networks, fuzzy logic, support vector machines, and genetic algorithms are used in evolutionary computation to solve this problem. We look at how soft computing approaches may be used to build web intelligences in this research.