Text Mining

Classification, Clustering, and Applications

von

Srivastava, Ashok N.Hrsg.Sahami, MehranHrsg.

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Verkaufsrang8449in

CHF130.00

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Beschreibung

Focuses on statistical methods for text mining and analysis. This work examines methods to automatically cluster and classify text documents and applies these methods in a variety of areas, including adaptive information filtering, information distillation, and text search.

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Details

ISBN/GTIN978-1-4200-5940-3

ProduktartBuch

EinbandGebunden

VerlagTaylor and FrancisChapman and Hall/CRC

ErscheinungslandUSA

Erscheinungsdatum15.06.2009

Auflage1. A.

ReiheChapman & Hall/CRC Data Mining and Knowledge Discovery Series

Seiten328 Seiten

SpracheEnglisch

MasseBreite 156 mm, Höhe 234 mm

Gewicht598 g

IllustrationenFarb., s/w. Abb.

Artikel-Nr.11017444

KatalogBuchzentrum

Datenquelle-Nr.23283674

Weitere Details

Reihe

Computational Methods of Feature Selection

Understanding Complex Datasets

Knowledge Discovery for Counterterrorism and Law Enforcement

Multimedia Data Mining

Constrained Clustering

Information Discovery on Electronic Health Records

Data Mining for Design and Marketing

Geographic Data Mining and Knowledge Discovery

The Top Ten Algorithms in Data Mining

Text Mining

Biological Data Mining

Statistical Data Mining Using SAS Applications

Knowledge Discovery from Data Streams

Handbook of Educational Data Mining

Mining Software Specifications

Spectral Feature Selection for Data Mining

Music Data Mining

Machine Learning and Knowledge Discovery for Engineering Systems Health Management

Advances in Machine Learning and Data Mining for Astronomy

Support Vector Machines

Contrast Data Mining

Data Clustering

RapidMiner

Computational Business Analytics

Computational Intelligent Data Analysis for Sustainable Development

Data Classification

Graph-Based Social Media Analysis

Event Mining

Accelerating Discovery

Healthcare Data Analytics

Text Mining and Visualization

Advances in Machine Learning and Data Mining for Astronomy

Data Mining with R

Data Science and Analytics with Python

Large-Scale Machine Learning in the Earth Sciences

Data Science and Analytics with Python

Social Networks with Rich Edge Semantics

Data Mining for Design and Marketing

Mining Software Specifications

Biological Data Mining

Autor

Srivastava, Ashok N.Hrsg.Sahami, MehranHrsg.

Ashok N. Srivastava is the Principal Investigator of the Integrated Vehicle Health Management research project in the NASA Aeronautics Research Mission Directorate. Dr. Srivastava also leads the Intelligent Data Understanding group at NASA Ames Research Center.Mehran Sahami is an Associate Professor and Associate Chair for Education in the computer science department at Stanford University.

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Schlagworte

AudienceCode

Tertiary education: For tertiary education typically in universities and colleges of higher education, equivalent to UNESCO's ISCED Levels 5-7. (05)

BIC

Data mining (UNF)

Dewey Decimal

005.741

THEMA Schlagwort

Data Mining (UNF)

THEMA Hauptschlagwort

Data Mining (UNF)

UKSLC

COM