Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
ACM SIGKDD Explorations Newsletter
Discovering unexpected information from your competitors' web sites
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
Data Mining for Measuring and Improving the Success of Web Sites
Data Mining and Knowledge Discovery
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Managing Interesting Rules in Sequence Mining
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
SPIRIT: Sequential Pattern Mining with Regular Expression Constraints
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Interestingness of Discovered Association Rules in Terms of Neighborhood-Based Unexpectedness
PAKDD '98 Proceedings of the Second Pacific-Asia Conference on Research and Development in Knowledge Discovery and Data Mining
Finding Informative Rules in Interval Sequences
IDA '01 Proceedings of the 4th International Conference on Advances in Intelligent Data Analysis
Improving the Effectiveness of a Web Site with Web Usage Mining
WEBKDD '99 Revised Papers from the International Workshop on Web Usage Analysis and User Profiling
Using Sequential and Non-Sequential Patterns in Predictive Web Usage Mining Tasks
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Chance Discovery
Sequential Association Rule Mining with Time Lags
Journal of Intelligent Information Systems
Mining unexpected rules by pushing user dynamics
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Web Log Sequential Patterns with Position Coded Pre-Order Linked WAP-Tree
Data Mining and Knowledge Discovery
Unified algorithm for undirected discovery of exception rules: Research Articles
International Journal of Intelligent Systems - Knowledge Discovery: Dedicated to Jan M. Żytkow
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Fast discovery of unexpected patterns in data, relative to a Bayesian network
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
A survey of interestingness measures for knowledge discovery
The Knowledge Engineering Review
On Characterization and Discovery of Minimal Unexpected Patterns in Rule Discovery
IEEE Transactions on Knowledge and Data Engineering
Sequence Data Mining (Advances in Database Systems)
Sequence Data Mining (Advances in Database Systems)
Mining user navigation patterns for personalizing topic directories
Proceedings of the 9th annual ACM international workshop on Web information and data management
Web usage mining: extracting unexpected periods from web logs
Data Mining and Knowledge Discovery
An incremental data mining algorithm for discovering web access patterns
International Journal of Business Intelligence and Data Mining
Web process and workflow path mining using the Multimethod approach
International Journal of Business Intelligence and Data Mining
Mining Unexpected Web Usage Behaviors
ICDM '08 Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
Toward Recommendation Based on Ontology-Powered Web-Usage Mining
IEEE Internet Computing
Data mining for web personalization
The adaptive web
Post-analysis of learned rules
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
International Journal of Business Intelligence and Data Mining
| Hi-index | 0.01 |
Web usage mining has been much concentrated on the discovery of relevant user behaviours from web access record data. In this paper, we present WebUser, an approach to discover unexpected usage in web access log. We present a belief-driven method for extracting unexpected web usage sequences, where the belief system consists of a temporal relation and semantics constrained sequence rules acquired with respect to prior knowledge. Our experiments show the effectiveness and usefulness of the proposed approach. Furthermore, discovered rules of unexpected web usage can be used for web content personalisation and recommendation, site structure optimisation and critical event prediction.