EFFICIENT USER NAVIGATION PATTERN PREDICTION TECHNIQUE FROM WEB LOG DATA

November 2015
Vol-1, Issue-4
Paper ID: 1320
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
Computer Engineering
Keywords
Web usage mining Navigation pattern classification weblog clustering Graph partitioning
Abstract
Web Usage Mining (WUM) is one of the most interesting areas of data mining. The main aim of WUM is to survey the web log files in order to extract users’ navigation pattern .The web log files contain abstract data which needs to be processed in order to discover the meaningful data from it. Later on mining techniques are applied for clustering users, to organize frequently used data sets, for classification of users and association rule mining. This paper emphasizes on identifying user navigation pattern from web log data. The working is divided into two steps: In first step web log data is processed. In second step the processed web log data is analyzed in order to identify the user access navigation pattern from it.

Author Information

# Name Institute / Affiliation
1 Vyas Mahesh Bharat SRES COE ,Kopargaon
2 Mali Prasad Atmaram SRES COE,Kopargaon
3 Prof V. N. Nirgude SRES COE,Kopargaon

How to Cite

Use the following formats to cite this article in your research.

APA Style
Bharat, Vyas Mahesh, Atmaram, Mali Prasad, & Nirgude, Prof V. N. (2015). EFFICIENT USER NAVIGATION PATTERN PREDICTION TECHNIQUE FROM WEB LOG DATA. International Journal of Advance Research and Innovative Ideas In Education, 1(4), 424-427.
MLA Style
Bharat, Vyas Mahesh, et al. "EFFICIENT USER NAVIGATION PATTERN PREDICTION TECHNIQUE FROM WEB LOG DATA." International Journal of Advance Research and Innovative Ideas In Education, vol. 1, no. 4, 2015, pp. 424-427.
IEEE Style
Vyas Mahesh Bharat, Mali Prasad Atmaram, and Prof V. N. Nirgude, "EFFICIENT USER NAVIGATION PATTERN PREDICTION TECHNIQUE FROM WEB LOG DATA," International Journal of Advance Research and Innovative Ideas In Education, vol. 1, no. 4, pp. 424-427, 2015.
Vancouver Style
Bharat Vyas Mahesh, Atmaram Mali Prasad, Nirgude Prof V. N.. EFFICIENT USER NAVIGATION PATTERN PREDICTION TECHNIQUE FROM WEB LOG DATA. International Journal of Advance Research and Innovative Ideas In Education. 2015;1(4):424-427.
Harvard Style
Bharat, Vyas Mahesh, Atmaram, Mali Prasad, & Nirgude, Prof V. N. (2015) 'EFFICIENT USER NAVIGATION PATTERN PREDICTION TECHNIQUE FROM WEB LOG DATA', International Journal of Advance Research and Innovative Ideas In Education, 1(4), pp. 424-427.
Chicago Style
Bharat, Vyas Mahesh, Mali Prasad Atmaram, and Prof V. N. Nirgude. "EFFICIENT USER NAVIGATION PATTERN PREDICTION TECHNIQUE FROM WEB LOG DATA." International Journal of Advance Research and Innovative Ideas In Education 1, no. 4 (2015): 424-427.
Turabian Style
Bharat, Vyas Mahesh, Mali Prasad Atmaram, and Prof V. N. Nirgude. "EFFICIENT USER NAVIGATION PATTERN PREDICTION TECHNIQUE FROM WEB LOG DATA." International Journal of Advance Research and Innovative Ideas In Education 1, no. 4 (2015): 424-427.

Export Citation

Related Research

A Deep Learning-Based Framework for Mood-Oriented Music Recommendation Using Facial Expression Analysis
Vaibhav Ashok Bhangare et al. 2026 Computer Engineering
PDF Unavailable
Survey On : Intelligent Payroll and Human Resource Management Systems: A Systematic Review of Automation, Security, and Analytics
Vishakha Jadhav et al. 2026 Human Resource Management, Artificial Intelligence, Machine Learning, Payroll Systems, Cybersecurity, Business Intelligence, Robotic Process Automation, Employee Analytics, Digital Transforma
PDF Unavailable
Civic Engagement & Empowerment Platform
Supriya Dadaso Bankar et al. 2026 Computer engineering
PDF Unavailable
RAG System Development with Pydantic AI ChromaDB & Groq
Prof. Priyanka P. Kakade et al. 2026 Computer Engineering
PDF Unavailable
Machine Learning Based Early Stage Diabetes Detection System
Rohan Mulik et al. 2026 Computer Engineering
PDF Unavailable
A Survey on Skillsense:AI Career Analyzer App
Kirti Datir et al. 2026 Computer Engineering
PDF Unavailable
Employee Performance Portal
P.Harika et al. 2026 Computer science and engineering
PDF Unavailable