Study on enterprise data mining solution based on extension set

Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology

Volumn 38, Issue 7, 2006, Pages 1124-1128

  Li, Xing Sen ^a   Shi, Yong ^a   Li, Ai Hua ^a  

^a UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

Author keywords

Data mining; Data mining consulting; Data quality; Enterprise information system; Extenics; Extension set; Matter element analysis

Indexed keywords

DATA MINING CONSULTING; DATA QUALITY; ENTERPRISE INFORMATION SYSTEM; EXTENICS; EXTENSION SET; MATTER ELEMENT ANALYSIS;

COMPUTER SOFTWARE; FEATURE EXTRACTION; MANAGEMENT INFORMATION SYSTEMS; MATHEMATICAL TRANSFORMATIONS; REQUIREMENTS ENGINEERING;

DATA MINING;

EID: 33749821919     PISSN: 03676234     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (18)

1. HAN J, MICHELINE K. Data Mining: Concepts and Techniques [M]. [s. l.]: Morgan Kaufmann, 2006.
2. KARGUPTA H, PARK B H, PITTIE S, et al. Contributed articles on online, interactive, and anytime data mining: MobiMine: monitoring the stock market from a PDA [J]. ACM SIGKDD Explorations Newsletter, 2002, 3 (2): 37-46.
3. CHEN Yongqiang, HU Leifang. Study on data mining application in CRM system based on insurance trade [A]. Proceedings of the 7th International Conference on Electronic Commerce ICEC 05 [C]. [s. l.]: CM Press, 2005. 839-841.
4. LARRY T, YU H, CHUNG Fulai, et al. Using emerging pattern based projected clustering and gene expression data for cancer detection [A]. Proceedings of the Second Conference on Asia-Pacific Bioinformatics-Volume 29 CRPIT 04 [C]. [s. l.]: Australian Computer Society, Inc, 2004. 75-84.
5. DASU T, VESONDER G T, WRIGHT J R. Data quality through knowledge engineering [A]. Conference on Knowledge Discovery in Data Archive, Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining [C]. Washington, D. C: [s. n.], 2003. 705-710.
6. JOHNSON T, DASU T. Data quality and data cleaning-An overview [A]. International Conference on Management of Data Archive, Proceedings of the 2003ACM SIGMOD International Conference on Management of Data [C]. San Diego: ACM Press, 2003. 681-681.
7. PIERCE E M. A Progress Report from MIT Information Quality Conference [EB/OL]. Http://www.Iqconference.org, 2003.
8. KUBICA J, MOORE A. Probabilistic noise identification and data cleaning [A]. Proceedings of the 3rd IEEE International Conference on Data Mining [C]. FL: [s. n.], 2003.
9. ZHU X, WU X. Class noise vs attribute noise: A quantitative study of their impacts [J]. Artificial Intelligence Review, 2004, 22 (3-4): 177-210.
10. KOU Gang, LIU Xiantao, PENG Yi, et al. Multiple criteria linear programming approach to data mining: Models, algorithm designs and software development [J]. Optimization Methods and Software, 2003, 18 (4): 453-473.