Abstract-This paper summarizes the different characteristics of web data, the basic components of web mining and its different types, and their current states of the art. The reason for considering web mining, a separate field from data mining, is explained. The limitations of some of the existing web mining methods and tools are enunciated, and the significance of soft computing (comprising fuzzy logic (FL), artificial neural networks (ANNs), genetic algorithms (GAs), and rough sets (RSs) highlighted. A survey of the existing literature on "soft web mining" is provided along with the commercially available systems. The prospective areas of web mining where the application of soft computing needs immediate attention are outlined with justification. Scope for future research in developing "soft web mining" systems is explained. An extensive bibliography is also provided. Index Terms-Artificial neural networks (ANNs), data mining, fuzzy logic (FL), genetic algorithms (GAs), information retrieval (IR), knowledge discovery, pattern recognition, rough sets (RSs), search engines.
Sankar K. Pal, Fellow REF a deep survey of the existing literature on soft web mining along with commercially available systems.
Web Mining in Soft Computing Framework: Relevance, State of the Art and Future Directions
IEEE Transactions on Neural Networks
Medicine Computer Science