Mining compressed commodity workflows from massive RFID data sets

Radio Frequency Identification (RFID) technology is fast becoming a prevalent tool in tracking commodities in supply chain management applications. The movement of commodities through the supply chain forms a gigantic workflow that can be mined for the discovery of trends, flow correlations and outlier paths, that in turn can be valuable in understanding and optimizing business processes. In this paper, we propose a method to construct compressed probabilistic workflows that capture the movement trends and significant exceptions of the overall data sets, but with a size that is substantially smaller than that of the complete RFID workflow. Compression is achieved based on the following observations: (1) only a relatively small minority of items deviate from the general trend, (2) only truly non-redundant deviations, i.e., those that substantially deviate from the previously recorded ones, are interesting, and (3) although RFID data is registered at the primitive level, data analysis u...

• Type: Conference
• Year: 2006
• Where: CIKM
• Authors: Hector Gonzalez, Jiawei Han, Xiaolei Li
• Keywords: CIKM 2006, Complete Rfid Workflow, Information Management, Supply Chain, Supply Chain Management