Using data mining to profile TV viewers

Communications of the ACM

Volumn 46, Issue 12, 2003, Pages 66-72

  Spangler, William E ^a   Gal Or, Mordechai ^a   May, Jerrold H ^b  

^a DUQUESNE UNIVERSITY   (United States)

^b UNIVERSITY OF PITTSBURGH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADVERTIZING DELIVERY SYSTEM (ADS); CUSTOMIZED ADVERTIZING; PERSONAL VIDEO RECORDER (PVR); SERVICE PROVIDERS;

DATABASE SYSTEMS; ERROR ANALYSIS; FINANCE; INFORMATION ANALYSIS; INTEGRATION; MARKETING; PROBLEM SOLVING; RANDOM PROCESSES; RESEARCH; SAMPLING; TELEVISION NETWORKS; VIDEO RECORDING;

DATA MINING;

EID: 4243161971     PISSN: 00010782     EISSN: None     Source Type: Journal    
DOI: 10.1145/953460.953461     Document Type: Review

References (12)

1. Apte, C., Liu, B., Pednault, E., and Smyth, P. Business applications of data mining. Commun. ACM 45, 8 (Aug. 2002), 49-53.
2. Baudisch, P. and Brueckner, L. TV Scout: Lowering the entry barrier to personalized TV program recommendation. In Proceedings of the 2nd International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (Malaga, Spain, May 29-31). Springer-Verlag, Berlin, 2002, 58-68.
3. Berry, M. and Linoff, G. Mastering Data Mining. John Wiley& Sons, Inc., New York, 1999.
4. Chickering, D. and Heckerman, D. Targeted advertising with inventory management. In Proceedings of the ACM Conference on Electronic Commerce (Minneapolis, Oct. 17-20). ACM Press, New York, 2000, 145-149.
5. Chickering, D. and Heckerman, D. A decision-theoretic approach to targeted advertising. In Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence (Stanford, CA, June 30-July 3). Morgan Kaufman, San Francisco, 2000, 82-88.
6. Chunovic, L. Change ahead for channels. Electronic Media 20, 31 (July 30, 2001), 1.
7. Duda, R., Hart, P., and Stork, D. Pattern Classification. John Wiley& Sons, Inc., New York, 2000.
8. Konstan, J., Miller, B., Maltz, D., Herlocker, J., Gordon, L., and Riedl, J. GroupLens: Applying collaborative filtering to Usenet news. Commun. ACM 40, 3 (Mar. 1997), 77-87.
9. Ortega, J., Koppel, M., and Argamon, S. Arbitrating among competing classifiers using learned referees. Knowl. Inform. Syst. 3, 4 (Nov. 2001), 470-490.
10. Prodromidis, A. and Stolfo, S. Cost complexity-based pruning of ensemble classifiers. Knowl. Inform. Syst. 3, 4 (Nov. 2001), 449-469.
11. Smyth, B. and Cotter, P. A personalized television listings service. Commun. ACM 43, 8 (Aug. 2000), 107-111.
12. Spangler, W., May, J., and Vargas, L. Choosing data mining methods for multiple classification: Representational and performance measurement implications for decision support. J. Mgmt. Info. Syst. 16, 1 (summer 1999), 37-62.