Characterising Data Mining software.

Item request has been placed! ×
Item request cannot be made. ×
  Processing Request
  • Additional Information
    • Author-Supplied Keywords:
      business decision support
      data mining
      tool characterisation
      tool comparison
    • NAICS/Industry Codes:
      511211 Software publishers (except video game publishers)
      443144 Computer and software stores
      423430 Computer and Computer Peripheral Equipment and Software Merchant Wholesalers
      417310 Computer, computer peripheral and pre-packaged software merchant wholesalers
    • Abstract:
      The ever-increasing number of fielded Data Mining applications is evidence that the technology works and produces added value in a variety of business areas. Most of the research-lab generated algorithms have found their way under various guises in a number of commercial software packages. When considering the use of Data Mining, the average business user is now faced with a plethora of DM software to choose from. In order to be informed, such a choice requires a standard basis from which to compare and contrast alternatives along relevant, business-focused dimensions, as well as the location of candidate tools within the space outlined by these dimensions. This paper aims at meeting this business requirement. It presents a standard schema for the characterisation of Data Mining software tools and the results of a recent survey of 41 popular Data Mining tools described within this schema. [ABSTRACT FROM AUTHOR]
    • Abstract:
      Copyright of Intelligent Data Analysis is the property of IOS Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
    • Author Affiliations:
      1ELCA Informatique SA, Av. de la Harpe, 22-24, CH-1000 Lausanne 13, Switzerland. Tel.: +41 21 613 21 11; Fax: +41 21 613 21 00; E-mail: cgc@elca.ch
    • ISSN:
      1088-467X
    • Accession Number:
      10.3233/IDA-2003-7302
    • Accession Number:
      10388834
  • Citations
    • ABNT:
      GIRAUD-CARRIER, C.; POVEL, O. Characterising Data Mining software. Intelligent Data Analysis, [s. l.], v. 7, n. 3, p. 181–192, 2003. Disponível em: . Acesso em: 20 ago. 2019.
    • AMA:
      Giraud-Carrier C, Povel O. Characterising Data Mining software. Intelligent Data Analysis. 2003;7(3):181-192. doi:10.3233/IDA-2003-7302.
    • APA:
      Giraud-Carrier, C., & Povel, O. (2003). Characterising Data Mining software. Intelligent Data Analysis, 7(3), 181–192. https://doi.org/10.3233/IDA-2003-7302
    • Chicago/Turabian: Author-Date:
      Giraud-Carrier, C., and O. Povel. 2003. “Characterising Data Mining Software.” Intelligent Data Analysis 7 (3): 181–92. doi:10.3233/IDA-2003-7302.
    • Harvard:
      Giraud-Carrier, C. and Povel, O. (2003) ‘Characterising Data Mining software’, Intelligent Data Analysis, 7(3), pp. 181–192. doi: 10.3233/IDA-2003-7302.
    • Harvard: Australian:
      Giraud-Carrier, C & Povel, O 2003, ‘Characterising Data Mining software’, Intelligent Data Analysis, vol. 7, no. 3, pp. 181–192, viewed 20 August 2019, .
    • MLA:
      Giraud-Carrier, C., and O. Povel. “Characterising Data Mining Software.” Intelligent Data Analysis, vol. 7, no. 3, June 2003, pp. 181–192. EBSCOhost, doi:10.3233/IDA-2003-7302.
    • Chicago/Turabian: Humanities:
      Giraud-Carrier, C., and O. Povel. “Characterising Data Mining Software.” Intelligent Data Analysis 7, no. 3 (June 2003): 181–92. doi:10.3233/IDA-2003-7302.
    • Vancouver/ICMJE:
      Giraud-Carrier C, Povel O. Characterising Data Mining software. Intelligent Data Analysis [Internet]. 2003 Jun [cited 2019 Aug 20];7(3):181–92. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=10388834&custid=s8280428