• DocumentCode
    294148
  • Title

    Knowledge guided data mining

  • Author

    Milne, Dr Robert ; Nelson, Mr Chris

  • Author_Institution
    Intelligent Applications Ltd., Livingston Village, UK
  • fYear
    1995
  • fDate
    34731
  • Firstpage
    42522
  • Lastpage
    42524
  • Abstract
    Intelligent Applications Ltd. have recently completed the final phase of the development of a software model for a client. The client has a very large number of customers made up from members of the general public. The model predicts which customers of the client have an increased likelihood of being lost to a competitor. The model was developed by performing data mining on a representative set of data from the client, using knowledge-guided induction. One of the main benefits to the client is the provision of intelligence, resulting from the data mining, to help them target their mailshot campaigns and other marketing exercises in the most effective way. The model has undergone extensive tests and validation routines to measure its accuracy based on customer data taken from a 3-year time window. The model has consistently yielded extremely high accuracies for most customer types, and more than 90% for certain customer types in particular
  • Keywords
    deductive databases; knowledge acquisition; marketing data processing; accuracy; competition; customer losses; customer types; data mining; knowledge guided data mining; knowledge-guided induction; mailshot campaigns; marketing exercises; software model development; validation routines;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Knowledge Discovery in Databases, IEE Colloquium on (Digest No. 1995/021 (A))
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1049/ic:19950117
  • Filename
    476229