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Telecommunication Case Modelling – Call Center

Telecommunication Case Modelling – Call Center . C.Chudzian, J.Granat, W.Traczyk Decision Support Systems Laboratory National Institute of Telecommunications Warsaw, Poland . The goal.

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Telecommunication Case Modelling – Call Center

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  1. Telecommunication Case Modelling –Call Center C.Chudzian, J.Granat, W.Traczyk Decision Support Systems Laboratory National Institute of Telecommunications Warsaw, Poland

  2. The goal Selecting prospective clients for targeting a marketing campaign based on the existing data (call center data, billing data and others). Data Mining in Practice, Dortmund, 18th February 2003

  3. Model of the call center Data Mining in Practice, Dortmund, 18th February 2003

  4. The data is distributed Target group ofclients Analysis Switch Callcenter Data Mining in Practice, Dortmund, 18th February 2003

  5. Process of building a table for data mining Data Mining in Practice, Dortmund, 18th February 2003

  6. Switch data Billing YES No List of clients Call Center Classification of clients Data Mining in Practice, Dortmund, 18th February 2003

  7. SAS Enterprise Miner Data Mining in Practice, Dortmund, 18th February 2003

  8. MiningMart requirements Data Mining in Practice, Dortmund, 18th February 2003

  9. The set of operators Data Mining in Practice, Dortmund, 18th February 2003

  10. Preprocessing (part I) Process details for all clients Segmentation Process details for a client TimeIntervalManualDiscretization RowSelectionByQuery SpecifiedStatistics RowSelectionByQuery SpecifiedStatistics SpecifiedStatistics Client Features II Client Features I Client Features III UnSegment UnSegment UnSegment Features II for all clients Features III for all clients Features I for all clients JoinByKey Features (I,II,III) for all clients Data Mining in Practice, Dortmund, 18th February 2003

  11. Preprocessing (part II) All features for all clients GenericFeatureConstruction Features(I,II,III) for all clients Call Center Data UnionByKey UnionByKey Service info Service users GenericFeatureConstruction Mining Concept Service info (switch prefered) Data Mining in Practice, Dortmund, 18th February 2003

  12. NIT case - HCI view Data Mining in Practice, Dortmund, 18th February 2003

  13. Business data Data Mining in Practice, Dortmund, 18th February 2003

  14. NIT case – preprocessing steps Data Mining in Practice, Dortmund, 18th February 2003

  15. Conclusions Conceptual modeling improves: • the understanding of the data preparation process • maintenance of the data preparation process • Knowledge transfer for other people We do not need to use programming language Data Mining in Practice, Dortmund, 18th February 2003

  16. Questions & discussion ? J.Granat@itl.waw.pl Data Mining in Practice, Dortmund, 18th February 2003

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