Logic programming and databases
Logic programming and databases
Relational Data Mining
Levelwise Search and Borders of Theories in KnowledgeDiscovery
Data Mining and Knowledge Discovery
Mining Association Rules in Multiple Relations
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Scalability and efficiency in multi-relational data mining
ACM SIGKDD Explorations Newsletter
Inducing Multi-Level Association Rules from Multiple Relations
Machine Learning
Find Recent Frequent Items with Sliding Windows in Data Streams
IIH-MSP '07 Proceedings of the Third International Conference on International Information Hiding and Multimedia Signal Processing (IIH-MSP 2007) - Volume 02
Approximate mining of frequent patterns on streams
Intelligent Data Analysis - Knowlegde Discovery from Data Streams
Verifying and Mining Frequent Patterns from Large Windows over Data Streams
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Finding patterns in large star schemas at the right aggregation level
MDAI'12 Proceedings of the 9th international conference on Modeling Decisions for Artificial Intelligence
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Some challenges in frequent pattern mining from data streams are the drift of data distribution and the computational efficiency. In this work an additional challenge is considered: data streams describe complex objects modeled by multiple database relations. A multi-relational data mining algorithm is proposed to efficiently discover approximate relational frequent patterns over a sliding time window of a complex data stream. The effectiveness of the method is proved on application to the Internet packet stream.