MARC details
| 000 -LEADER |
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04747nam a22005415i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
978-0-387-79420-4 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20170628033358.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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| fixed length control field |
cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
100301s2009 xxu| s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780387794204 |
| -- |
978-0-387-79420-4 |
| 024 7# - OTHER STANDARD IDENTIFIER |
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| Standard number or code |
10.1007/978-0-387-79420-4 |
| Source of number or code |
doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
QA76.9.D343 |
| 072 #7 - SUBJECT CATEGORY CODE |
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| Subject category code |
UNF |
| Source |
bicssc |
| 072 #7 - SUBJECT CATEGORY CODE |
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| Subject category code |
UYQE |
| Source |
bicssc |
| 072 #7 - SUBJECT CATEGORY CODE |
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| Subject category code |
COM021030 |
| Source |
bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.312 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Cao, Longbing. |
| Relator term |
editor. |
| 245 10 - TITLE STATEMENT |
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| Title |
Data Mining for Business Applications |
| Medium |
[electronic resource] / |
| Statement of responsibility, etc |
edited by Longbing Cao, Philip S. Yu, Chengqi Zhang, Huaifeng Zhang. |
| 264 #1 - |
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| -- |
Boston, MA : |
| -- |
Springer US, |
| -- |
2009. |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
XX, 302 p. |
| Other physical details |
online resource. |
| 336 ## - |
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| -- |
text |
| -- |
txt |
| -- |
rdacontent |
| 337 ## - |
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| -- |
computer |
| -- |
c |
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rdamedia |
| 338 ## - |
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| -- |
online resource |
| -- |
cr |
| -- |
rdacarrier |
| 347 ## - |
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| -- |
text file |
| -- |
PDF |
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rda |
| 505 0# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Domain Driven KDD Methodology -- to Domain Driven Data Mining -- Post-processing Data Mining Models for Actionability -- On Mining Maximal Pattern-Based Clusters -- Role of Human Intelligence in Domain Driven Data Mining -- Ontology Mining for Personalized Search -- Novel KDD Domains & Techniques -- Data Mining Applications in Social Security -- Security Data Mining: A Survey Introducing Tamper-Resistance -- A Domain Driven Mining Algorithm on Gene Sequence Clustering -- Domain Driven Tree Mining of Semi-structured Mental Health Information -- Text Mining for Real-time Ontology Evolution -- Microarray Data Mining: Selecting Trustworthy Genes with Gene Feature Ranking -- Blog Data Mining for Cyber Security Threats -- Blog Data Mining: The Predictive Power of Sentiments -- Web Mining: Extracting Knowledge from the World Wide Web -- DAG Mining for Code Compaction -- A Framework for Context-Aware Trajectory -- Census Data Mining for Land Use Classification -- Visual Data Mining for Developing Competitive Strategies in Higher Education -- Data Mining For Robust Flight Scheduling -- Data Mining for Algorithmic Asset Management. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
Data Mining for Business Applications presents state-of-the-art data mining research and development related to methodologies, techniques, approaches and successful applications. The contributions of this book mark a paradigm shift from "data-centered pattern mining" to "domain-driven actionable knowledge discovery (AKD)" for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future data mining research and development in the dialogue between academia and business. Part I centers on developing workable AKD methodologies, including: domain-driven data mining post-processing rules for actions domain-driven customer analytics the role of human intelligence in AKD maximal pattern-based cluster ontology mining Part II focuses on novel KDD domains and the corresponding techniques, exploring the mining of emergent areas and domains such as: social security data community security data gene sequences mental health information traditional Chinese medicine data cancer related data blog data sentiment information web data procedures moving object trajectories land use mapping higher education data flight scheduling algorithmic asset management Researchers, practitioners and university students in the areas of data mining and knowledge discovery, knowledge engineering, human-computer interaction, artificial intelligence, intelligent information processing, decision support systems, knowledge management, and KDD project management are sure to find this a practical and effective means of enhancing their understanding of and using data mining in their own projects. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Data mining. |
| 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 |
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| Topical term or geographic name as entry element |
Electronic data processing. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Artificial intelligence. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Data Mining and Knowledge Discovery. |
| 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 |
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| Topical term or geographic name as entry element |
Artificial Intelligence (incl. Robotics). |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Computing Methodologies. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Models and Principles. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Yu, Philip S. |
| Relator term |
editor. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Zhang, Chengqi. |
| Relator term |
editor. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Zhang, Huaifeng. |
| Relator term |
editor. |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
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| Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY |
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| Title |
Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
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| Display text |
Printed edition: |
| International Standard Book Number |
9780387794198 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
<a href="http://dx.doi.org/10.1007/978-0-387-79420-4">http://dx.doi.org/10.1007/978-0-387-79420-4</a> |
| 912 ## - |
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ZDB-2-SCS |
