Web user clustering from access log using belief function

Authors:
Yunjuan Xie;Vir V. Phoha
Affiliations:
Louisiana Tech University, Ruston, LA;Louisiana Tech University, Ruston, LA
Venue:
Proceedings of the 1st international conference on Knowledge capture
Year:
2001

Citing 11
Cited 14

A simple view of the Dempster-Shafer theory of evidence and its implication for the rule of combination

AI Magazine
Dempster-Shafer's theory of evidence applied to structured documents: modelling uncertainty

Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Adaptive Web sites: automatically synthesizing Web pages

AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Using path profiles to predict HTTP requests

WWW7 Proceedings of the seventh international conference on World Wide Web 7
Data mining and the Web: past, present and future

Proceedings of the 2nd international workshop on Web information and data management
Efficient Data Mining for Path Traversal Patterns

IEEE Transactions on Knowledge and Data Engineering
Data Mining and Personalization Technologies

DASFAA '99 Proceedings of the Sixth International Conference on Database Systems for Advanced Applications
Grouping Web Page References into Transactions for Mining World Wide Web Browsing Patterns

KDEX '97 Proceedings of the 1997 IEEE Knowledge and Data Engineering Exchange Workshop
Creating Adaptive Web Sites Through Usage-Based Clustering of URLs

KDEX '99 Proceedings of the 1999 Workshop on Knowledge and Data Engineering Exchange
Knowledge discovery from users Web-page navigation

RIDE '97 Proceedings of the 7th International Workshop on Research Issues in Data Engineering (RIDE '97) High Performance Database Management for Large-Scale Applications
Web Mining: Information and Pattern Discovery on the World Wide Web

ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence

Adaptive Neural Network Clustering of Web Users

Computer
Mining interesting knowledge from weblogs: a survey

Data & Knowledge Engineering
The bipartite clique: a topological paradigm for WWWeb user search customization

Proceedings of the 43rd annual Southeast regional conference - Volume 1
Mining web browsing patterns for E-commerce

Computers in Industry
Web user behaviors prediction system using trend similarity

SMO'07 Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization
Discovering geographical-specific interests from web click data

Proceedings of the first international workshop on Location and the web
Web User Profiling Using Fuzzy Clustering

WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Computational Intelligence techniques for Web personalization

Web Intelligence and Agent Systems
Web Site Auditing Using Web Access Log Data

CNSR '09 Proceedings of the 2009 Seventh Annual Communication Networks and Services Research Conference
A web page usage prediction scheme using sequence indexing and clustering techniques

Data & Knowledge Engineering
A web-page usage prediction scheme using weighted suffix trees

SPIRE'07 Proceedings of the 14th international conference on String processing and information retrieval
Wavelet-based clustering of social-network users using temporal and activity profiles

PReMI'11 Proceedings of the 4th international conference on Pattern recognition and machine intelligence
Adaptive web usage profiling

WebKDD'05 Proceedings of the 7th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
A random indexing approach for web user clustering and web prefetching

PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this work, we present a novel approach to clustering Web site users into different groups and generating common user profiles. These profiles can be used to make recommendations, personalize Web sites, and for other uses such as targeting users for advertising. By using the concept of mass distribution in Dempster-Shafer's theory, the belief function similarity measure in our algorithm adds to the clustering task the ability to capture the uncertainty among Web user's navigation behavior. Our algorithm is relatively simple to use and gives comparable results to other approaches reported in the literature of web mining.