Data Mining and Knowledge Discovery Handbook (Record no. 109747)
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000 -LEADER | |
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fixed length control field | 05952nam a22005295i 4500 |
001 - CONTROL NUMBER | |
control field | 978-0-387-09823-4 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | DE-He213 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20140220084454.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
fixed length control field | cr nn 008mamaa |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 100917s2010 xxu| s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9780387098234 |
-- | 978-0-387-09823-4 |
024 7# - OTHER STANDARD IDENTIFIER | |
Standard number or code | 10.1007/978-0-387-09823-4 |
Source of number or code | doi |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
Classification number | QA76.9.D3 |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | UN |
Source | bicssc |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | UMT |
Source | bicssc |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | COM021000 |
Source | bisacsh |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 005.74 |
Edition number | 23 |
100 1# - MAIN ENTRY--PERSONAL NAME | |
Personal name | Maimon, Oded. |
Relator term | editor. |
245 10 - TITLE STATEMENT | |
Title | Data Mining and Knowledge Discovery Handbook |
Medium | [electronic resource] / |
Statement of responsibility, etc | edited by Oded Maimon, Lior Rokach. |
250 ## - EDITION STATEMENT | |
Edition statement | 2. |
264 #1 - | |
-- | Boston, MA : |
-- | Springer US, |
-- | 2010. |
300 ## - PHYSICAL DESCRIPTION | |
Extent | XX, 1285p. 40 illus. |
Other physical details | online resource. |
336 ## - | |
-- | text |
-- | txt |
-- | rdacontent |
337 ## - | |
-- | computer |
-- | c |
-- | rdamedia |
338 ## - | |
-- | online resource |
-- | cr |
-- | rdacarrier |
347 ## - | |
-- | text file |
-- | |
-- | rda |
505 0# - FORMATTED CONTENTS NOTE | |
Formatted contents note | to Knowledge Discovery and Data Mining -- Preprocessing Methods -- Data Cleansing: A Prelude to Knowledge Discovery -- Handling Missing Attribute Values -- Geometric Methods for Feature Extraction and Dimensional Reduction - A Guided Tour -- Dimension Reduction and Feature Selection -- Discretization Methods -- Outlier Detection -- Supervised Methods -- Supervised Learning -- Classification Trees -- Bayesian Networks -- Data Mining within a Regression Framework -- Support Vector Machines -- Rule Induction -- Unsupervised Methods -- A survey of Clustering Algorithms -- Association Rules -- Frequent Set Mining -- Constraint-based Data Mining -- Link Analysis -- Soft Computing Methods -- A Review of Evolutionary Algorithms for Data Mining -- A Review of Reinforcement Learning Methods -- Neural Networks For Data Mining -- Granular Computing and Rough Sets - An Incremental Development -- Pattern Clustering Using a Swarm Intelligence Approach -- Using Fuzzy Logic in Data Mining -- Supporting Methods -- Statistical Methods for Data Mining -- Logics for Data Mining -- Wavelet Methods in Data Mining -- Fractal Mining - Self Similarity-based Clustering and its Applications -- Visual Analysis of Sequences Using Fractal Geometry -- Interestingness Measures - On Determining What Is Interesting -- Quality Assessment Approaches in Data Mining -- Data Mining Model Comparison -- Data Mining Query Languages -- Advanced Methods -- Mining Multi-label Data -- Privacy in Data Mining -- Meta-Learning - Concepts and Techniques -- Bias vs Variance Decomposition for Regression and Classification -- Mining with Rare Cases -- Data Stream Mining -- Mining Concept-Drifting Data Streams -- Mining High-Dimensional Data -- Text Mining and Information Extraction -- Spatial Data Mining -- Spatio-temporal clustering -- Data Mining for Imbalanced Datasets: An Overview -- Relational Data Mining -- Web Mining -- A Review of Web Document Clustering Approaches -- Causal Discovery -- Ensemble Methods in Supervised Learning -- Data Mining using Decomposition Methods -- Information Fusion - Methods and Aggregation Operators -- Parallel and Grid-Based Data Mining – Algorithms, Models and Systems for High-Performance KDD -- Collaborative Data Mining -- Organizational Data Mining -- Mining Time Series Data -- Applications -- Multimedia Data Mining -- Data Mining in Medicine -- Learning Information Patterns in Biological Databases - Stochastic Data Mining -- Data Mining for Financial Applications -- Data Mining for Intrusion Detection -- Data Mining for CRM -- Data Mining for Target Marketing -- NHECD - Nano Health and Environmental Commented Database -- Software -- Commercial Data Mining Software -- Weka-A Machine Learning Workbench for Data Mining. |
520 ## - SUMMARY, ETC. | |
Summary, etc | Knowledge Discovery demonstrates intelligent computing at its best, and is the most desirable and interesting end-product of Information Technology. To be able to discover and to extract knowledge from data is a task that many researchers and practitioners are endeavoring to accomplish. There is a lot of hidden knowledge waiting to be discovered – this is the challenge created by today’s abundance of data. Data Mining and Knowledge Discovery Handbook, Second Edition organizes the most current concepts, theories, standards, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This handbook first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook, Second Edition is designed for research scientists, libraries and advanced-level students in computer science and engineering as a reference. This handbook is also suitable for professionals in industry, for computing applications, information systems management, and strategic research management. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Computer science. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Information systems. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Database management. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Information storage and retrieval systems. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Artificial intelligence. |
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Computer Science. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Database Management. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Information Storage and Retrieval. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Artificial Intelligence (incl. Robotics). |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Information Systems Applications (incl.Internet). |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Information Systems and Communication Service. |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Rokach, Lior. |
Relator term | editor. |
710 2# - ADDED ENTRY--CORPORATE NAME | |
Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY | |
Title | Springer eBooks |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9780387098227 |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | http://dx.doi.org/10.1007/978-0-387-09823-4 |
912 ## - | |
-- | ZDB-2-SCS |
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