Advanced Fuzzy Logic Based Pattern Classification Method For Knowledge Discovery in Web Usage Document

Abstract

Text processing has been crucial in helping natural language processing applications such as social networking, data mining, and internet search overcome the ambiguity problem. We'll utilize semantic similarity to examine the connections between Word-Pairs on social media. It is crucial to group a vast amount of unstructured text documents into a limited number of word sense disambiguation ideas so that the lexical source can include the characteristics needed to capture additional semantic data. Pre-processing document collections, text categorization and classification, and term and information extraction from golden standard data sets are all components of text mining. The purpose of this effort is to further foster research collaboration between the information technology and knowledge management communities and to raise awareness of the potential of text mining as a tool for knowledge discovery. Since its inception, text mining has been the subject of multidisciplinary research with a primary focus on Web-based collaborative writing, database technology, text analysis, machine learning, and knowledge discovery. In order to detect the online usage document utilizing a variety of metrics and obtain precise results from the web page, we built a unique Advanced Fuzzy logic approach in this research.