Energy characterization of data mining algorithms on mobile devices

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

Volumn 8046 LNCS, Issue , 2013, Pages 98-113

  Comito, Carmela ^a,b   Talia, Domenico ^a,b  

^a UNIVERSITY OF CALABRIA   (Italy)

^b ICAR CNR   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

COLLABORATIVE ANALYSIS; COMPLEX APPLICATIONS; DATA MINING ALGORITHM; DATA-INTENSIVE APPLICATION; DECISION TREE INDUCTION; ENERGY CHARACTERIZATION; INFORMATION SHARING; MOBILE COMPUTING DEVICES;

ALGORITHMS; DECISION TREES; ENERGY EFFICIENCY; ENERGY UTILIZATION; MOBILE DEVICES; SENSOR NETWORKS; SENSORS;

DATA MINING;

EID: 84885793305     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40517-4_9     Document Type: Conference Paper

References (13)

1. Kargupta, H., Park, B., Pitties, S., Liu, L., Kushraj, D., Sarkar, K.: Mobimine: monitoring the stock marked from a PDA. ACM SIGKDD Explorations 3(2), 37-46 (2002)
2. Kargupta, H., Bhargava, R., Liu, K., Powers, M., Blair, P., Bushra, S., Dull, J.: VEDAS: a mobile and distributed data stream mining system for realtime vehicle monitoring. In: SIAM Data Mining Conference (2003)
3. Comito, C., Talia, D., Trunfio, P.: An energy-aware clustering scheme for mobile applications. In: IEEE Scalcom'11, pp. 15-22 (2011)
4. Comito, C., Talia, D., Trunfio, P.: An energy aware framework for mobile data mining. In: Zomaya, A., Choon Lee, Y. (eds.) Energy Efficient Distributed Computing Systems, Chapter 23. Wiley-IEEE Computer Society Press, New York (2012)
5. Bhargava, R., Kargupta, H., Powers, M.: Energy consumption in data analysis for on-board and distributed applications. In: ICML 03 Workshop on Machine Learning Technologies for Autonomous Space Applications (2003)
6. Witten, H., Frank, E.: Data Mining: Practical Machine Learning Tools with Java Implementations. Morgan Kaufmann, San Francisco (2000)
7. http://www.android.com/
8. Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Morgan Kaufmann Publishers, San Mateo (2000)
9. MacQueen, J.B.: Some methods for classification and analysis of multivariate observations. In: Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281-297 (1967)
10. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: Proceedings of the 20th International Conference on Very Large Data Bases, pp. 487-499 (1994)
11. Agarwal, R., Mannila, H., Srikant, R., Toivonen, H., Verkamo, A.: Fast discovery of association rules. Advances in Knowledge Discovery and Data Mining, pp. 307-328. MIT Press, Cambridge (1996)
12. Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo (1993)
13. http://kdd.ics.uci.edu/databases/