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Taxonomy Matching Using Background Knowledge

Linked Data, Semantic Web and Heterogeneous Repositories

  • Heiko Angermann
  • Naeem Ramzan

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Introduction to Taxonomy Matching

    1. Front Matter
      Pages 1-1
    2. Heiko Angermann, Naeem Ramzan
      Pages 3-13
    3. Heiko Angermann, Naeem Ramzan
      Pages 15-24
  3. Recent Matching Techniques, Algorithms, Systems, Evaluations, and Datasets

    1. Front Matter
      Pages 25-25
    2. Heiko Angermann, Naeem Ramzan
      Pages 27-50
    3. Heiko Angermann, Naeem Ramzan
      Pages 51-68
  4. Taxonomy Heterogeneity Applications

    1. Front Matter
      Pages 69-69
    2. Heiko Angermann, Naeem Ramzan
      Pages 71-83
  5. Conclusions

    1. Front Matter
      Pages 85-85
    2. Heiko Angermann, Naeem Ramzan
      Pages 87-90
  6. Back Matter
    Pages 91-103

About this book

Introduction

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.

Keywords

Taxonomy matching Pattern matching Schema matching Semantic heterogeneity Ontology matching

Authors and affiliations

  • Heiko Angermann
    • 1
  • Naeem Ramzan
    • 2
  1. 1. University of the West of ScotlandPaisleyUnited Kingdom
  2. 2.University of the West of ScotlandPaisleyUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-72209-2
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-72208-5
  • Online ISBN 978-3-319-72209-2
  • Buy this book on publisher's site
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