Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Bottom-up computation of sparse and Iceberg CUBE
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
Mining Process Models from Workflow Logs
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Probabilistic DFA Inference using Kullback-Leibler Divergence and Minimality
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Learning Stochastic Regular Grammars by Means of a State Merging Method
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
Materialized View Selection for Multidimensional Datasets
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Workflow Mining: Discovering Process Models from Event Logs
IEEE Transactions on Knowledge and Data Engineering
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Warehousing and Analyzing Massive RFID Data Sets
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
A Pipelined Framework for Online Cleaning of Sensor Data Streams
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Flowcube: constructing RFID flowcubes for multi-dimensional analysis of commodity flows
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Performance testing: evaluating an RFID library inventory reader
International Journal of Internet Protocol Technology
An active product state tracking architecture in logistics sensor networks
Computers in Industry
Intelligent process control system with RFID cuboid
Proceedings of the 11th International Conference on Electronic Commerce
CAMS: OLAPing Multidimensional Data Streams Efficiently
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
Mining association rules for RFID data with concept hierarchy
ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 2
Adaptive product tracking in RFID-enabled large-scale supply chain
Expert Systems with Applications: An International Journal
Intelligent service-integrated platform based on the RFID technology and software agent system
Expert Systems with Applications: An International Journal
Generation of an adaptive simulation driven by product trajectories
Journal of Intelligent Manufacturing
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Radio Frequency Identification (RFID) applications are set to play an essential role in object tracking and supply chain management systems. In the near future, it is expected that every major retailer will use RFID systems to track the movement of products from suppliers to warehouses, store backrooms and eventually to points of sale. The volume of information generated by such systems can be enormous as each individual item (a pallet, a case, or an SKU) will leave a trail of data as it moves through different locations. We propose two data models for the management of this data. The first is a path cube that preserves object transition information while allowing muti-dimensional analysis of path dependent aggregates. The second is a workflow cube that summarizes the major patterns and significant exceptions in the flow of items through the system. The design of our models is based on the following observations: (1) items usually move together in large groups through early stages in the system (e.g., distribution centers) and only in later stages (e.g., stores) do they move in smaller groups, (2) although RFID data is registered at the primitive level, data analysis usually takes place at a higher abstraction level, (3) many items have similar flow patterns and only a relatively small number of them truly deviate from the general trend, and (4) only non-redundant flow deviations with respect to previously recorded deviations are interesting. These observations facilitate the construction of highly compressed RFID data warehouses and the exploration of such data warehouses by scalable data mining. In this study we give a general overview of the principles driving the design of our framework. We believe warehousing and mining RFID data presents an interesting application for advanced data mining.