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Data mining techniques : for marketing, sales, and customer relationship management / Michael J.A. Berry, Gordon S. Linoff.

By: Contributor(s): Material type: TextTextPublication details: New York : Wiley, c2004.Edition: 2nd edDescription: xxv, 643 p. : ill. ; 24 cmISBN:
  • 9780471470649:
  • 0471470643
Subject(s): DDC classification:
  • 658.802
Online resources:
Contents:
Why and what is data mining? -- The virtuous cycle of data mining -- Data mining methodology and best practices -- Data mining applications in marketing and customer relationship management -- The lure of statistics: data mining using familiar tools -- Decision trees -- Artificial neural networks -- Nearest neighbor approaches : memory-based reasoning and collaborative filtering -- Market basket analysis and association rules -- Link analysis -- Automatic Cluster detection -- Knowing when to worry: hazard functions and survival analysis in marketing -- Genetic algorithms -- Data mining throughout the customer life cycle -- Data warehousing, OLAP, and data mining -- Building the data mining environment -- Preparing data for mining -- Putting data mining to work.
List(s) this item appears in: MSc IT Management
Holdings
Item type Current library Call number Copy number Status Date due Barcode
General Lending Carlow Campus Library General Lending 658.802 (Browse shelf(Opens below)) 1 Checked out 14/12/2018 46508

CW_KRITM_M

Includes index.

CW037

CW229

CW838

Why and what is data mining? -- The virtuous cycle of data mining -- Data mining methodology and best practices -- Data mining applications in marketing and customer relationship management -- The lure of statistics: data mining using familiar tools -- Decision trees -- Artificial neural networks -- Nearest neighbor approaches : memory-based reasoning and collaborative filtering -- Market basket analysis and association rules -- Link analysis -- Automatic Cluster detection -- Knowing when to worry: hazard functions and survival analysis in marketing -- Genetic algorithms -- Data mining throughout the customer life cycle -- Data warehousing, OLAP, and data mining -- Building the data mining environment -- Preparing data for mining -- Putting data mining to work.

46.47

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