
Web User Access Behavior Analysis & Prediction
An Association Rule mining Approach using Map-Reduce Framework on Apache Spark
LAP Lambert Academic Publishing
Published on 8. December 2017
Book
Paperback/Softback
92 pages
978-620-2-07649-4 (ISBN)
Description
The analysis of Web users browsing behaviors is essential for putting appropriate information on the web. The browsing behaviors are stored as navigational patterns in web server logs. These weblogs are used to predict the frequently accessed patterns of web users, which can be used to predict user behavior and to collect business intelligence. However, owing to the exponentially increasing weblog size, existing implementations of frequent pattern mining algorithms often takes too much time and generate too many redundant patterns. This book discussed new association rule mining algorithms implemented on the Apache Spark platform for extracting frequent patterns from huge weblogs.
More details
Language
English
Dimensions
Height: 220 mm
Width: 150 mm
Thickness: 7 mm
Weight
155 gr
ISBN-13
978-620-2-07649-4 (9786202076494)
Schweitzer Classification
Persons
Vijay Khandal & Riya Singhal received their B.Tech. degrees in computer science & engineering respectively with honours and gold medal in 2016 from National Institute of Technology Raipur. Dr. Dilip Singh Sisodia is an assistant professor with the department of computer science engineering,National Institute of Technology Raipur.