Warehousing and mining massive RFID data sets

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4093 LNAI, Issue , 2006, Pages 1-18

  Han, Jiawei ^a   Gonzalez, Hector ^a   Li, Xiaolei ^a   Klabjan, Diego ^a  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; FLOW PATTERNS; INFORMATION ANALYSIS; NATURAL FREQUENCIES; OBJECT RECOGNITION; RADIO SYSTEMS; DATA WAREHOUSES; SUPPLY CHAIN MANAGEMENT;

MUTI-DIMENSIONAL ANALYSIS; NON-REDUNDANT FLOWS; RADIO FREQUENCY IDENTIFICATION (RFID); SUPPLY CHAIN MANAGEMENT; ABSTRACTION LEVEL; DIMENSIONAL ANALYSIS; DISTRIBUTION CENTERS; GENERAL TRENDS; NON-REDUNDANT; OBJECT TRACKING; RFID SYSTEMS; SUPPLY CHAIN MANAGEMENT SYSTEM;

DATA WAREHOUSES; RADIO FREQUENCY IDENTIFICATION (RFID);

EID: 33749412919     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11811305_1     Document Type: Conference Paper

References (18)

1. R. Agrawal, D. Gunopulos, and F. Leymann. Mining process models from workfiow logs. In Proc. 1998 Inl. Conf. Extending Database Technology (EDBT'98), pages 469-483, Valencia, Spain, Mar. 1998.
2. R. Agrawal and R. Srikant. Fast algorithm for mining association rules in large databases. In Research Report RJ 9839, IBM Almaden Research Center, San Jose, CA, June 1994.
3. K. Beyer and R. Ramakrishnan. Bottom-up computation of sparse and iceberg cubes. In Proc. 1999 ACM-SIGMOD Int. Conf. Management of Data (SIGMOD'99), pages 359-370, Philadelphia, PA, June 1999.
4. R. C. Carrasco and J. Oncina. Learning stochastic regular grammars by means of a state merging method. In Proc. 1994 Int. Col. Grammatical Inference (ICGI'94), pages 139-152, Alicante, Spain, Sept. 1994.
5. S. Chaudhuri and U. Dayal. An overview of data warehousing and OLAP technology. SIGMOD Record, 26:65-74, 1997.
6. H. Gonzalez, J. Han, and X. Li. Flowcube: Constructing RFID flowcubes for multi-dimensional analysis of commodity flows. In Proc. 2006 Int. Conf. Very Large Data Bases (VLDB'06), Seoul, Korea, Sept. 2006.
7. H. Gonzalez, J. Han, X. Li, and D. Klabjan. Warehousing and analysis of massive RFID data sets. In Proc. 2006 Int. Conf. Data Engineering (ICDE'06), Atlanta, Georgia, April 2006.
8. J. Gray, S. Chaudhuri, A. Bosworth, A. Layman, D. Reichart, M. Venkatrao, F. Pellow, and H. Pirahesh. Data cube: A relational aggregation operator generalizing group-by, cross-tab and sub-totals. Data Mining and Knowledge Discovery, 1:29-54, 1997.
9. J. Han and M. Kamber. Data Mining: Concepts and Techniques (2nd ed.). Morgan Kaufmann, 2006.
10. V. Harinarayan, A. Rajaraman, and J. D. Ullman. Implementing data cubes efficiently. In Proc. 1996 ACM-SIGMOD Int. Conf. Management of Data (SIGMOD'96), pages 205-216, Montreal, Canada, June 1996.
11. Venture development corporation (vdc). In http://www.vdc-corp.com/.
12. S. R. Jeffery, G. Alonso, and M. J. Franklin. Adaptive cleaning for RFID data streams. In Technical Report UCB/EECS-2006-29, EECS Department, University of California, Berkeley, March 2006.
13. S. R. Jeffery, G. Alonso, M. J. Franklin, W. Hong, and J. Widom. A pipelined framework for online cleaning of sensor data streams. In Proc. 2006 Int. Conf. Data Engineering (ICDE'06), Atlanta, Georgia, April 2006.
14. S. Sarma, D. L. Brock, and K. Ashton. The networked physical world. In White paper, MIT Auto-ID Center, http://archive.epcglobalinc.org/ publishedresearch/MIT-AUTOID-WH001.pdf, 2000.
15. S. E. Sarma, S. A. Weis, and D. W. Engels. RFID systems, security & privacy implications. In White paper, MIT Auto-ID Center, http://archive. epcglobalinc.org/publishedresearch/MITAUTOID-WH-014.pdf, 2002.
16. A. Shukla, P. M. Deshpande, and J. F. Naughton. Materialized view selection for multidimensional datasets. In Proc. 1998 Int. Conf. Very Large Data Bases (VLDB'98), pages 488-499, New York, NY, Aug. 1998.
17. F. Thollard, P. Dupont, and C. dela Higuera. Probabilistic DFA inference using kullbackleibler divergence and minimality. In Proc. 2000 Int. Conf. Machine Learning (ICML'00), pages 975-982, Stanford, CA, June 2000.
18. W. van der Aalst, T. Weijters, and L. Maruster. Workflow mining: Discovering process models from event logs. IEEE Trans. Knowl. Data Eng, 16:1128-1142, 2004.