• K.Pariplavi
• B. Raghuram

Data mining has matured as a field of fundamental and applied research in computer science. The objective of this dissertation is to evaluate, propose and improve the use of some of the recent approaches, architectures and Web mining techniques (collecting personal data from customers) are the means of utilizing data mining methods to induce and extract useful data from Web data and service where data mining has been applied in the fields of e-commerce and e-business (that means User's behavior). In the context of web mining, clustering could be used to cluster comparative snap streams to determine learning behaviors on account of e-learning or general site access behaviors in e-commerce. A large portion of the calculations presented in the literature to deal with clustering web sessions treat sessions as sets of visited pages inside a time period and don't consider the sequence of the snap stream appearance. This has a huge consequence when looking at similarities between web sessions. Wang and Zaiane propose a calculation based on sequence alignment to measure similarities between web sessions where sessions are sequentially ordered sequences of page accesses

User behavior,web mining, e-commerce, data mining, clustering

"An Overview on the Internet Users Behavior towards E-Commerce", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 5, page no.738-746, May-2018, Available :http://www.jetir.org/papers/JETIR1805311.pdf

"An Overview on the Internet Users Behavior towards E-Commerce", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 5, page no. pp738-746, May-2018, Available at : http://www.jetir.org/papers/JETIR1805311.pdf