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Data mining: Metodi e strategie by Susi Dulli (Italian) Paperback Book

US $51.08
Approximately£38.14
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Item specifics

Condition
New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
ISBN-13
9788847011625
Book Title
Data mining
ISBN
9788847011625

About this product

Product Identifiers

Publisher
Springer Milan
ISBN-10
8847011620
ISBN-13
9788847011625
eBay Product ID (ePID)
203675337

Product Key Features

Number of Pages
IX, 182 Pages
Language
Italian
Publication Name
Data Mining : Metodi E Strategie
Publication Year
2009
Subject
Intelligence (Ai) & Semantics, Probability & Statistics / General, Databases / Data Mining
Type
Textbook
Subject Area
Mathematics, Computers
Author
Sara Furini, Edmondo Peron, Susi Dulli
Series
Unitext Ser.
Format
Trade Paperback

Dimensions

Item Weight
16 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Intended Audience
Scholarly & Professional
Reviews
From the reviews: "The aim of this book is to provide both researchers and students with an overview on the area ... . the book is quite well written and most of the concepts are presented in a clear manner. Moreover, the sketches of the main algorithms, the examples spread throughout the book and the exercises proposed at the end of each chapter make the book a pleasant reading and a useful tool for students and for those interested in an overview of the data mining field." (Luigi Palopoli, Zentralblatt MATH, Vol. 1170, 2009)
Number of Volumes
1 vol.
Illustrated
Yes
Table Of Content
Introduzione.- Trattamento preliminare dei dati.- Misure di distanza e di similarità.- Cluster Analysis.- Metodi di classificazione.- Serie Temporali.- Analisi delle associazioni.- Analisi dei link.
Synopsis
Il libro nasce dall'esigenza di coniugare esperienze e capacità procedurali diverse provenienti da vari ambiti disciplinari, quali l'informatica e la statistica, al fine di ricercare ed individuare percorsi e relazioni legate alla conoscenza. In un contesto di business, la conoscenza scoperta può avere un valore strategico per le aziende perchè consente di aumentare i profitti, riducendo i costi oppure aumentando le entrate con il conseguente aumento del ROI. Il volume è rivolto sia a studenti universitari e ricercatori, che a professionisti e manager aziendali che vogliano approfondire gli aspetti algoritmici delle tecniche di Data mining: lo studio degli algoritmi e delle principali tecniche è essenziale per conoscere meglio come la tecnologia possa essere applicata ai diversi tipi di dati e quindi anche diverse problematiche di business. Il testo pone volutamente l'attenzione sugli aspetti procedurali e di calcolo della metodologia, differenziandosi dagli altri testi in italiano che inquadrano puramente il contesto statistico. Il materiale esposto può essere utile a quanti vogliano completare la loro formazione scientifica in questa disciplina., Il libro nasce dall'esigenza di coniugare esperienze e capacit procedurali diverse provenienti da vari ambiti disciplinari, quali l'informatica e la statistica, al fine di ricercare ed individuare percorsi e relazioni legate alla conoscenza. In un contesto di business, la conoscenza scoperta pu avere un valore strategico per le aziende perch consente di aumentare i profitti, riducendo i costi oppure aumentando le entrate con il conseguente aumento del ROI. Il volume rivolto sia a studenti universitari e ricercatori, che a professionisti e manager aziendali che vogliano approfondire gli aspetti algoritmici delle tecniche di Data mining: lo studio degli algoritmi e delle principali tecniche essenziale per conoscere meglio come la tecnologia possa essere applicata ai diversi tipi di dati e quindi anche diverse problematiche di business. Il testo pone volutamente l'attenzione sugli aspetti procedurali e di calcolo della metodologia, differenziandosi dagli altri testi in italiano che inquadrano puramente il contesto statistico. Il materiale esposto pu essere utile a quanti vogliano completare la loro formazione scientifica in questa disciplina.
LC Classification Number
QA76.9.D343

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