The use of meta-rules in rule based legal computer systems
ICAIL '93 Proceedings of the 4th international conference on Artificial intelligence and law
Advances in knowledge discovery and data mining
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Discovery of Multiple-Level Association Rules from Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Incremental Meta-Mining from Large Temporal Data Sets
ER '98 Proceedings of the Workshops on Data Warehousing and Data Mining: Advances in Database Technologies
Discovering High-Order Periodic Patterns
Knowledge and Information Systems
Supporting RFID-based item tracking applications in Oracle DBMS using a bitmap datatype
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Warehousing and Analyzing Massive RFID Data Sets
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
RFID data management for effective objects tracking
Proceedings of the 2007 ACM symposium on Applied computing
Warehousing and mining massive RFID data sets
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
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Recently, Radio Frequency Identification (RFID) technology is being deployed for several applications, including supply-chain optimization, business process automation, asset tracking, and problem traceability applications. The problem with RFID data is that its degree increases according to time and location, thus, resulting in an enormous volume of data duplication. Therefore, it is difficult to extract useful hidden knowledge in RFID data using traditional association rule mining techniques, or analyze data using statistical techniques or queries. This paper suggest association rule generation method based on the meta rule which could find a meaningful rule by using inclusion relation and concept hierarchy between data, in order to extract a hidden pattern from RFID data. Therefore, we could not only eliminate the duplicated rule efficiently by using meta-rule but also reduce the complexity by processing the limited association rule examination. Also, this method is useful to improve the storage efficiency and to find a hidden association relationship between objects.