東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Data mining and constraint programmi...

Bessiere, Christian.

Linked to FindBook

Google Book

Amazon

博客來

Data mining and constraint programming = foundations of a cross-disciplinary approach /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data mining and constraint programming/ edited by Christian Bessiere ... [et al.].
Reminder of title:	foundations of a cross-disciplinary approach /
other author:	Bessiere, Christian.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	xii, 349 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction to Combinatorial Optimisation in Numberjack -- Data Mining and Constraints: An Overview -- New Approaches to Constraint Acquisition -- ModelSeeker: Extracting Global Constraint Models from Positive Examples -- Learning Constraint Satisfaction Problems: An ILP Perspective -- Learning Modulo Theories -- Algorithm Selection for Combinatorial Search Problems: A Survey -- Adapting Consistency in Constraint Solving -- Modeling in MiningZinc -- Partition-Based Clustering Using Constraint Optimisation -- The Inductive Constraint Programming Loop -- ICON Loop Carpooling Show Case -- ICON Loop Health Show Case -- ICON Loop Energy Show Case.
Contained By:	Springer eBooks
Subject:	Data mining. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-50137-6
ISBN:	9783319501376

Data mining and constraint programming = foundations of a cross-disciplinary approach /
Data mining and constraint programmingfoundations of a cross-disciplinary approach /[electronic resource] :edited by Christian Bessiere ... [et al.]. - Cham :Springer International Publishing :2016. - xii, 349 p. :ill., digital ;24 cm. - Lecture notes in computer science,101010302-9743 ;. - Lecture notes in computer science ;10101..

Introduction to Combinatorial Optimisation in Numberjack -- Data Mining and Constraints: An Overview -- New Approaches to Constraint Acquisition -- ModelSeeker: Extracting Global Constraint Models from Positive Examples -- Learning Constraint Satisfaction Problems: An ILP Perspective -- Learning Modulo Theories -- Algorithm Selection for Combinatorial Search Problems: A Survey -- Adapting Consistency in Constraint Solving -- Modeling in MiningZinc -- Partition-Based Clustering Using Constraint Optimisation -- The Inductive Constraint Programming Loop -- ICON Loop Carpooling Show Case -- ICON Loop Health Show Case -- ICON Loop Energy Show Case.

A successful integration of constraint programming and data mining has the potential to lead to a new ICT paradigm with far reaching implications. It could change the face of data mining and machine learning, as well as constraint programming technology. It would not only allow one to use data mining techniques in constraint programming to identify and update constraints and optimization criteria, but also to employ constraints and criteria in data mining and machine learning in order to discover models compatible with prior knowledge. This book reports on some key results obtained on this integrated and cross- disciplinary approach within the European FP7 FET Open project no. 284715 on "Inductive Constraint Programming" and a number of associated workshops and Dagstuhl seminars. The book is structured in five parts: background; learning to model; learning to solve; constraint programming for data mining; and showcases.

ISBN: 9783319501376

Standard No.: 10.1007/978-3-319-50137-6doiSubjects--Topical Terms:

562972
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Data mining and constraint programming = foundations of a cross-disciplinary approach /
LDR:02674nmm a2200337 a 4500 001 2082485
003 DE-He213
005 20161202191739.0
006 m d
007 cr nn 008maaau
008 170717s2016 gw s 0 eng d
020 $a 9783319501376 $q (electronic bk.)
020 $a 9783319501369 $q (paper)
024 7 $a 10.1007/978-3-319-50137-6 $2 doi
035 $a 978-3-319-50137-6
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D343
072 7 $a UYQ $2 bicssc
072 7 $a TJFM1 $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 006.312 $2 23
090 $a QA76.9.D343 $b D232 2016
245 0 0 $a Data mining and constraint programming $h [electronic resource] : $b foundations of a cross-disciplinary approach / $c edited by Christian Bessiere ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xii, 349 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 10101
505 0 $a Introduction to Combinatorial Optimisation in Numberjack -- Data Mining and Constraints: An Overview -- New Approaches to Constraint Acquisition -- ModelSeeker: Extracting Global Constraint Models from Positive Examples -- Learning Constraint Satisfaction Problems: An ILP Perspective -- Learning Modulo Theories -- Algorithm Selection for Combinatorial Search Problems: A Survey -- Adapting Consistency in Constraint Solving -- Modeling in MiningZinc -- Partition-Based Clustering Using Constraint Optimisation -- The Inductive Constraint Programming Loop -- ICON Loop Carpooling Show Case -- ICON Loop Health Show Case -- ICON Loop Energy Show Case.
520 $a A successful integration of constraint programming and data mining has the potential to lead to a new ICT paradigm with far reaching implications. It could change the face of data mining and machine learning, as well as constraint programming technology. It would not only allow one to use data mining techniques in constraint programming to identify and update constraints and optimization criteria, but also to employ constraints and criteria in data mining and machine learning in order to discover models compatible with prior knowledge. This book reports on some key results obtained on this integrated and cross- disciplinary approach within the European FP7 FET Open project no. 284715 on "Inductive Constraint Programming" and a number of associated workshops and Dagstuhl seminars. The book is structured in five parts: background; learning to model; learning to solve; constraint programming for data mining; and showcases.
650 0 $a Data mining. $3 562972
650 0 $a Constraint programming (Computer science) $3 672805
650 1 4 $a Computer Science. $3 626642
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Information Systems Applications (incl. Internet) $3 1565452
650 2 4 $a Simulation and Modeling. $3 890873
650 2 4 $a Algorithm Analysis and Problem Complexity. $3 891007
650 2 4 $a Database Management. $3 891010
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
700 1 $a Bessiere, Christian. $3 3205934
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Lecture notes in computer science ; $v 10101. $3 3205935
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-50137-6
950 $a Computer Science (Springer-11645)