Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
RFID Handbook: Fundamentals and Applications in Contactless Smart Cards and Identification
RFID Handbook: Fundamentals and Applications in Contactless Smart Cards and Identification
A Scalable Algorithm for Mining Maximal Frequent Sequences Using Sampling
ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
Data Mining and Knowledge Discovery Handbook
Data Mining and Knowledge Discovery Handbook
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
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The emergence of a range of new technologies like autoidentification devices, active tags, and smart items has impacted profoundly on business software solutions such as supply chain management, logistics, and inventory control. Integration of automatic data acquisition with enterprise applications as well as potential to provide real-time analytic functionality is opening new avenues for business process automation. In this paper, we propose a novel application of these technologies in a retailing environment leading to the vision of a smart shop floor. We firstly present the infrastructure for the smart shop floor. We then demonstrate how the proposed infrastructure is feasible and conducive to real-time acquisition of buyer behaviour data through three selected queries. Complete algorithmic solutions to each query are presented to provide proof of concept, and further deliberations on analytic potential of the proposed infrastructure are also provided.