Data Mining for Business Applications (Record no. 59172)

MARC details
000 -LEADER
fixed length control field 04704nam a22005175i 4500
001 - CONTROL NUMBER
control field 978-0-387-79420-4
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251006084421.0
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 100301s2009 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780387794204
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 99780387794204
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-0-387-79420-4
Source of number or code doi
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
Edition information 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Cao, Longbing.
Relator term editor.
245 10 - TITLE STATEMENT
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 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Boston, MA :
Name of producer, publisher, distributor, manufacturer Springer US,
Date of production, publication, distribution, manufacture, or copyright notice 2009.
300 ## - PHYSICAL DESCRIPTION
Other physical details online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
505 0# - FORMATTED CONTENTS NOTE
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.
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
Topical term or geographic name entry element COMPUTER SCIENCE.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element DATA MINING.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element INFORMATION STORAGE AND RETRIEVAL SYSTEMS.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element ELECTRONIC DATA PROCESSING.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element ARTIFICIAL INTELLIGENCE.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element COMPUTER SCIENCE.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element DATA MINING AND KNOWLEDGE DISCOVERY.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element INFORMATION STORAGE AND RETRIEVAL.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element ARTIFICIAL INTELLIGENCE (INCL. ROBOTICS).
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element COMPUTING METHODOLOGIES.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name 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
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
Relationship information 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>
Public note Ver el texto completo en las instalaciones del CICY
912 ## -
-- ZDB-2-SCS
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Libros electrónicos
Holdings
Lost status Source of classification or shelving scheme Damaged status Not for loan Collection Home library Current library Shelving location Date acquired Total checkouts Full call number Date last seen Price effective from Koha item type
  Dewey Decimal Classification     Libro electrónico CICY CICY Libro electrónico 06.10.2025   006.312 06.10.2025 06.10.2025 Libros electrónicos