메뉴 건너뛰기




Volumn , Issue , 2008, Pages 182-185

KDD, semma and CRISP-DM: A parallel overview

Author keywords

Data mining; Data mining standards; Knowledge discovery in databases

Indexed keywords

CRISP-DM; DATA MINING; DATA MINING STANDARDS; INDUSTRIAL STANDARDS; KNOWLEDGE DISCOVERY IN DATABASES;

EID: 58449118356     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (283)

References (17)
  • 1
    • 58449113720 scopus 로고    scopus 로고
    • Fayyad, U. M. et al. 1996. From data mining to knowledge discovery: an overview. In Fayyad, U. M.et al (Eds.), Advances in knowledge discovery and data mining. AAAI Press / The MIT Press.
    • Fayyad, U. M. et al. 1996. From data mining to knowledge discovery: an overview. In Fayyad, U. M.et al (Eds.), Advances in knowledge discovery and data mining. AAAI Press / The MIT Press.
  • 3
    • 0001896313 scopus 로고    scopus 로고
    • The process of knowledge discovery in databases
    • Fayyad, U. M. et al, Eds, AAAI Press, The MIT Press
    • Brachman, R. J. & Anand, T., 1996. The process of knowledge discovery in databases. In Fayyad, U. M. et al. (Eds.), Advances in knowledge discovery and data mining. AAAI Press / The MIT Press.
    • (1996) Advances in knowledge discovery and data mining
    • Brachman, R.J.1    Anand, T.2
  • 4
    • 0030387631 scopus 로고    scopus 로고
    • Data Mining: An Overview from a Database Perspective
    • Chen, M. et al, 1996. Data Mining: An Overview from a Database Perspective. IEEE Transactions on Knowledge and Data Engineering, Vol. 8, No. 6, pp 866-883.
    • (1996) IEEE Transactions on Knowledge and Data Engineering , vol.8 , Issue.6 , pp. 866-883
    • Chen, M.1
  • 5
    • 0030270281 scopus 로고    scopus 로고
    • Reality check for data mining
    • Simoudis, E., 1996. Reality check for data mining. IEEE Expert, Vol. 11, No. 5, pp 26-33.
    • (1996) IEEE Expert , vol.11 , Issue.5 , pp. 26-33
    • Simoudis, E.1
  • 6
    • 0030270991 scopus 로고    scopus 로고
    • Data mining and knowledge discovery: Making sense out of data
    • Fayyad, U. M., 1996. Data mining and knowledge discovery: making sense out of data. IEEE Expert, Vol. 11 No. 5, pp 20-25.
    • (1996) IEEE Expert , vol.11 , Issue.5 , pp. 20-25
    • Fayyad, U.M.1
  • 7
    • 58449130033 scopus 로고    scopus 로고
    • Dzeroski, S., 2006. Towards a General Framework for Data Mining.. In Dzeroski, S and Struyf, J (Eds.), Knowledge Discovery in Inductive Databases. LNCS 47474. Springer-Verlag.
    • Dzeroski, S., 2006. Towards a General Framework for Data Mining.. In Dzeroski, S and Struyf, J (Eds.), Knowledge Discovery in Inductive Databases. LNCS 47474. Springer-Verlag.
  • 9
    • 22044442392 scopus 로고    scopus 로고
    • An Extension to SQL for Mining Association Rules
    • Kluwer Academic Publishers
    • Meo, R. e tal, 1998. An Extension to SQL for Mining Association Rules. Data Mining and Knowledge Discovery Vol. 2, pp 195-224. Kluwer Academic Publishers.
    • (1998) Data Mining and Knowledge Discovery , vol.2 , pp. 195-224
    • Meo, R.1    e tal2
  • 10
    • 22844454898 scopus 로고    scopus 로고
    • MSQL: A Query Language for Database Mining
    • Kluwer Academic Publishers
    • Imielinski, T.; Virmani, A., 1999. MSQL: A Query Language for Database Mining. Data Mining and Knowledge Discovery Vol. 3, pp 373-408. Kluwer Academic Publishers.
    • (1999) Data Mining and Knowledge Discovery , vol.3 , pp. 373-408
    • Imielinski, T.1    Virmani, A.2
  • 11
    • 23044518930 scopus 로고    scopus 로고
    • Integrating Association Rule Mining with Relational Database Systems: Alternatives and Implications
    • Sarawagi, S. et al, 2000. Integrating Association Rule Mining with Relational Database Systems: Alternatives and Implications. Data Mining and Knowledge Discovery, Vol. 4, pp 89-125.
    • (2000) Data Mining and Knowledge Discovery , vol.4 , pp. 89-125
    • Sarawagi, S.1
  • 12
    • 33745779547 scopus 로고    scopus 로고
    • Query Languages Supporting Descriptive Rule Mining: A Comparative Study. Database Support for Data Mining Applications
    • Botta, Marco, et al, 2004. Query Languages Supporting Descriptive Rule Mining: A Comparative Study. Database Support for Data Mining Applications. LNAI 2682, pp 24-51.
    • (2004) LNAI , vol.2682 , pp. 24-51
    • Botta, M.1
  • 13
    • 58449113204 scopus 로고    scopus 로고
    • SAS Enterprise Miner, SEMMA. SAS Institute
    • SAS Enterprise Miner - SEMMA. SAS Institute.
  • 14
    • 84868889613 scopus 로고    scopus 로고
    • Accessed from, on May 2008
    • Accessed from http://www.sas.corn/teclmologies/analytics/datammmg/miner/ sernma.html, on May 2008
  • 16
    • 58449124564 scopus 로고    scopus 로고
    • Chapman, P. et al, 2000. CRISP-DM 1.0 - Step-by-step data mining guide.
    • Chapman, P. et al, 2000. CRISP-DM 1.0 - Step-by-step data mining guide.
  • 17
    • 84868870355 scopus 로고    scopus 로고
    • Accessed from on May 2008
    • Accessed from http://www.crisp-dm.org/CRISPWP-0800.pdf on May 2008


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.