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Mining of Data with Complex Structures (Record no. 11414)

000 -LEADER
fixed length control field 03923nam a22004335i 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140310143345.0
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 110203s2010 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783642175572
978-3-642-17557-2
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519
Edition number 23
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg,
-- 2010.
912 ## -
-- ZDB-2-ENG
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Hadzic, Fedja.
Relator term author.
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title Mining of Data with Complex Structures
Medium [electronic resource] /
Statement of responsibility, etc by Fedja Hadzic, Henry Tan, Tharam S. Dillon.
300 ## - PHYSICAL DESCRIPTION
Extent XX, 328 p.
Other physical details online resource.
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Studies in Computational Intelligence,
International Standard Serial Number 1860-949X ;
Volume number/sequential designation 333
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Tree Mining Problem -- Algorithm Development Issues -- Tree Model Guided Framework -- TMG Framework for Mining Ordered Subtrees -- TMG Framework for Mining Unordered Subtrees -- Mining Distance-Constrained Embedded Subtrees -- Mining Maximal and Closed Frequent Subtrees -- Tree Mining Applications -- Extension of TMG Framework for Mining Frequent Subsequences -- Graph Mining -- New Research Directions.
520 ## - SUMMARY, ETC.
Summary, etc Mining of Data with Complex Structures: - Clarifies the type and nature of data with complex structure including sequences, trees and graphs - Provides a detailed background of the state-of-the-art of sequence mining, tree mining and graph mining. - Defines the essential aspects of the tree mining problem: subtree types, support definitions, constraints. - Outlines the implementation issues one needs to consider when developing tree mining algorithms (enumeration strategies, data structures, etc.) - Details the Tree Model Guided (TMG) approach for tree mining and provides the mathematical model for the worst case estimate of complexity of mining ordered induced and embedded subtrees. -  Explains the mechanism of the TMG framework for mining ordered/unordered induced/embedded and distance-constrained embedded subtrees. -  Provides a detailed comparison of the different tree mining approaches highlighting the characteristics and benefits of each approach. -  Overviews the implications and potential applications of tree mining in general knowledge management related tasks, and uses Web, health and bioinformatics related applications as case studies. -  Details the extension of the TMG framework for sequence mining - Provides an overview of the future research direction with respect to technical extensions and application areas The primary audience is 3rd year, 4th year undergraduate students, Masters and PhD students and academics. The book can be used for both teaching and research. The secondary audiences are practitioners in industry, business, commerce, government and consortiums, alliances and partnerships to learn how to introduce and efficiently make use of the techniques for mining of data with complex structures into their applications. The scope of the book is both theoretical and practical and as such it will reach a broad market both within academia and industry. In addition, its subject matter is a rapidly emerging field that is critical for efficient analysis of knowledge stored in various domains.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering.
Topical term or geographic name as entry element Artificial intelligence.
Topical term or geographic name as entry element Engineering mathematics.
Topical term or geographic name as entry element Engineering.
Topical term or geographic name as entry element Appl.Mathematics/Computational Methods of Engineering.
Topical term or geographic name as entry element Artificial Intelligence (incl. Robotics).
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Tan, Henry.
Relator term author.
Personal name Dillon, Tharam S.
Relator term author.
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 9783642175565
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-642-17557-2
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type E-Book
Copies
Price effective from Permanent location Date last seen Not for loan Date acquired Source of classification or shelving scheme Koha item type Damaged status Lost status Withdrawn status Current location Full call number
2014-04-01AUM Main Library2014-04-01 2014-04-01 E-Book   AUM Main Library519

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