Taxonomy Matching Using Background Knowledge Linked Data, Semantic Web and Heterogeneous Repositories /

This important text/reference presents a comprehensive review of techniques for taxonomy matching, discussing matching algorithms, analyzing matching systems, and comparing matching evaluation approaches. Different methods are investigated in accordance with the criteria of the Ontology Alignment Ev...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Angermann, Heiko (Συγγραφέας), Ramzan, Naeem (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 04066nam a22005055i 4500
001 978-3-319-72209-2
003 DE-He213
005 20180108110603.0
007 cr nn 008mamaa
008 180108s2017 gw | s |||| 0|eng d
020 |a 9783319722092  |9 978-3-319-72209-2 
024 7 |a 10.1007/978-3-319-72209-2  |2 doi 
040 |d GrThAP 
050 4 |a Q337.5 
050 4 |a TK7882.P3 
072 7 |a UYQP  |2 bicssc 
072 7 |a COM016000  |2 bisacsh 
082 0 4 |a 006.4  |2 23 
100 1 |a Angermann, Heiko.  |e author. 
245 1 0 |a Taxonomy Matching Using Background Knowledge  |h [electronic resource] :  |b Linked Data, Semantic Web and Heterogeneous Repositories /  |c by Heiko Angermann, Naeem Ramzan. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2017. 
300 |a XIV, 103 p. 14 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 |a Part I: Introduction to Taxonomy Matching -- Background Taxonomy Matching -- Background of Taxonomic Heterogeneity.- Part II: Recent Matching Techniques, Algorithms, Systems, Evaluations, and Datasets -- Matching Techniques, Algorithms, and Systems -- Matching Evaluations and Datasets.- Part III: Taxonomy Heterogeneity Applications -- Related Areas.- Part IV: Conclusions -- Conclusions. 
520 |a This important text/reference presents a comprehensive review of techniques for taxonomy matching, discussing matching algorithms, analyzing matching systems, and comparing matching evaluation approaches. Different methods are investigated in accordance with the criteria of the Ontology Alignment Evaluation Initiative (OAEI). The text also highlights promising developments and innovative guidelines, to further motivate researchers and practitioners in the field. Topics and features: Discusses the fundamentals and the latest developments in taxonomy matching, including the related fields of ontology matching and schema matching Reviews next-generation matching strategies, matching algorithms, matching systems, and OAEI campaigns, as well as alternative evaluations Examines how the latest techniques make use of different sources of background knowledge to enable precise matching between repositories Describes the theoretical background, state-of-the-art research, and practical real-world applications Covers the fields of dynamic taxonomies, personalized directories, catalog segmentation, and recommender systems This stimulating book is an essential reference for practitioners engaged in data science and business intelligence, and for researchers specializing in taxonomy matching and semantic similarity assessment. The work is also suitable as a supplementary text for advanced undergraduate and postgraduate courses on information and metadata management. Dr. Heiko Angermann is an e-commerce, enterprise content management, and omni/multi-channel consultant, and the Head of Project Management at an e-commerce consulting house located in Nuremberg, Germany. Prof. Naeem Ramzan is a full Professor of Computing Engineering in the School of Engineering and Computing at the University of West of Scotland, Paisley, UK. His other publications include the successful Springer title Social Media Retrieval. 
650 0 |a Computer science. 
650 0 |a Management information systems. 
650 0 |a Data mining. 
650 0 |a Artificial intelligence. 
650 0 |a Pattern recognition. 
650 1 4 |a Computer Science. 
650 2 4 |a Pattern Recognition. 
650 2 4 |a Data Mining and Knowledge Discovery. 
650 2 4 |a Business Information Systems. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
700 1 |a Ramzan, Naeem.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783319722085 
856 4 0 |u http://dx.doi.org/10.1007/978-3-319-72209-2  |z Full Text via HEAL-Link 
912 |a ZDB-2-SCS 
950 |a Computer Science (Springer-11645)