Analysis and Comparison of Various Web Mining Techniques
Deepak Vats, Avinash Sharma · Journal of Computational and Theoretical Nanoscience · 2019
The reason at the back of data overloading dilemma faced by internet users on internet includes: excessive web information and billions of users around worldwide. Because of this, providing the internet users with more intended data is a challenging task in web applications. The lots of information available on internet are a fertile field for applying data mining techniques. This is what we call Web Mining (WM). The research in WM deals with research from many fields like database, Artificial Intelligence (machine learning [supervised, semi supervised, unsupervised and reinforcement], neural network and natural language processing (NLP)) and information retrieval. Here, research related to web mining and their categories is highlighted. We also situate comparison of most popular algorithms used from the field of data mining in pattern discovery phase of the WM.