Web mining in soft computing framework: relevance, state of the art and future directions

TLDR

The paper reviews Web data characteristics, mining components, and types, discusses why Web mining differs from data mining, highlights limitations of current methods, and underscores the role of soft computing techniques. The paper surveys soft Web mining literature, identifies priority application areas, and outlines future research directions. The authors conduct a comprehensive literature review and catalog commercially available soft Web mining systems. The study compiles an extensive bibliography of soft Web mining resources.

Abstract

The paper summarizes the different characteristics of Web data, the basic components of Web mining and its different types, and the current state 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) are 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.