| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA9910780454403321 |
|
|
Autore |
Berry Michael J. A |
|
|
Titolo |
Data mining techniques [[electronic resource] ] : for marketing, sales, and customer relationship management / / Michael J.A. Berry, Gordon S. Linoff |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Indianapolis, Ind., : Wiley Pub., c2004 |
|
|
|
|
|
|
|
ISBN |
|
1-280-35280-9 |
9786610352807 |
0-7645-6907-4 |
|
|
|
|
|
|
|
|
Edizione |
[2nd ed.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (671 p.) |
|
|
|
|
|
|
Altri autori (Persone) |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Data mining |
Marketing - Data processing |
Business - Data processing |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Note generali |
|
|
|
|
|
|
Nota di contenuto |
|
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. |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problems Each chapter covers a new data mining technique, and then shows readers how to apply the technique for improved marketing, sales, and customer |
|
|
|
|
|
|
|
|
|
|
support The authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data mining More advanced ch |
|
|
|
|
|
| |