Infoscale 2007 Keynote Speech:

Warehousing and Mining Massive RFID Data Sets

Keynote Speaker: Professor Jiawei Han Department of Computer Science University of Illinois at Urbana-Champaign, USA Home Page: http://www-faculty.cs.uiuc.edu/~hanj Email: hanj AT cs.uiuc.edu

Abstract

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. As a departure from the traditional data cube, we propose a new RFID data warehouse model that preserves object transitions while providing significant compression and path-dependent aggregates, based on the following observations: (1) items usually move together in large groups with dynamic merging and splitting of object groups during the transportation; and (2) although RFID data is registered at the primitive level, data analysis usually takes place at a higher abstraction level. Techniques for summarizing data, query processing in RFID data warehouse, RFID flow-cube construction, and data mining based on this framework are developed. We also illustrate a few promising research topics for mining such massive RFID data warehouses.

Short Biography

Jiawei Han, Professor, Department of Computer Science, University of Illinois at Urbana-Champaign. He has been working on research into data mining, data warehousing, database systems, data mining from spatiotemporal data, multimedia data, stream and RFID data, social network data, and biological data, with over 300 journal and conference publications. He has chaired or served in over 100 program committees of international conferences and workshops, including PC co-chair of 2005 (IEEE) International Conference on Data Mining (ICDM), Americas Coordinator of 2006 International Conference on Very Large Data Bases (VLDB). He is also serving as the founding Editor-In-Chief of ACM Transactions on Knowledge Discovery from Data. He is an ACM Fellow and has received 2004 ACM SIGKDD Innovations Award and 2005 IEEE Computer Society Technical Achievement Award. His book "Data Mining: Concepts and Techniques" (2nd ed., Morgan Kaufmann, 2006) has been popularly used as a textbook worldwide.