Frequent Item Set Mining from Log Files Using Navigation Pattern and Hadoop Techniques

EasyChair Preprint no. 7252

Abstract

Because this site log contains a large amount of data, it is preprocessed before modeling. The web log file is preprocessed and transformed into a user web log sequence. Sessions of navigation the web navigation session is the time while you're on the internet. a user's web page navigation sequence over time window. Finally, the user navigation session is modeled. Utilizing a model when the user navigation model is finished, it's time to move on to the next step. Mining is a task that can be carried out in order to discover anything interesting. Pattern. Web log modeling is a critical task in web usage. Mining. A high level of prediction accuracy can be reached by using a to improve the web log by modeling it with an accurate model Caching is used to improve the performance of the servers. Pages that are often visited are cached on proxy servers. Pre-fetching of web pages is a new topic of study. When combined with caching, the performance skyrockets. In A better algorithm for predicting the future is presented in this work.

Keyphrases: Domain sequential pattern mining, Markov model, Prediction web log, Semantic Web, Web Usage Mining

@Booklet{EasyChair:7252,
  author = {Nikheel Kasar and Shahrukh Teli},
  title = {Frequent Item Set Mining from Log Files Using Navigation Pattern and Hadoop Techniques},
  howpublished = {EasyChair Preprint no. 7252},

  year = {EasyChair, 2021}}