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Knowledge Engineering and Knowledge Management

Overview of attention for book
Cover of 'Knowledge Engineering and Knowledge Management'

Table of Contents

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    Book Overview
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    Chapter 1 An Empirical Evaluation of RDF Graph Partitioning Techniques
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    Chapter 2 Fuzzy Semantic Labeling of Semi-structured Numerical Datasets
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    Chapter 3 From Georeferenced Data to Socio-Spatial Knowledge. Ontology Design Patterns to Discover Domain-Specific Knowledge from Crowdsourced Data
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    Chapter 4 Conceptual Schema Transformation in Ontology-Based Data Access
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    Chapter 5 SWRL Reasoning Using Decision Tables
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    Chapter 6 A Framework for Explaining Query Answers in DL-Lite
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    Chapter 7 DLFoil: Class Expression Learning Revisited
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    Chapter 8 Requirements Behaviour Analysis for Ontology Testing
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    Chapter 9 Interactive Interpretation of Serial Episodes: Experiments in Musical Analysis
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    Chapter 10 Network Metrics for Assessing the Quality of Entity Resolution Between Multiple Datasets
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    Chapter 11 Making Sense of Numerical Data - Semantic Labelling of Web Tables
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    Chapter 12 Towards Enriching DBpedia from Vertical Enumerative Structures Using a Distant Learning Approach
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    Chapter 13 The Utility of the Abstract Relational Model and Attribute Paths in SQL
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    Chapter 14 Support and Centrality: Learning Weights for Knowledge Graph Embedding Models
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    Chapter 15 OmniScience and Extensions – Lessons Learned from Designing a Multi-domain, Multi-use Case Knowledge Representation System
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    Chapter 16 A Semantic Use Case Simulation Framework for Training Machine Learning Algorithms
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    Chapter 17 KnIGHT: Mapping Privacy Policies to GDPR
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    Chapter 18 Automating Class/Instance Representational Choices in Knowledge Bases
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    Chapter 19 Comparative Preferences in SPARQL
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    Chapter 20 Interplay of Game Incentives, Player Profiles and Task Difficulty in Games with a Purpose
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    Chapter 21 Inferring Types on Large Datasets Applying Ontology Class Hierarchy Classifiers: The DBpedia Case
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    Chapter 22 A Framework for Tackling Myopia in Concept Learning on the Web of Data
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    Chapter 23 Boosting Holistic Ontology Matching: Generating Graph Clique-Based Relaxed Reference Alignments for Holistic Evaluation
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    Chapter 24 Prominence and Dominance in Networks
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    Chapter 25 Deploying Spatial-Stream Query Answering in C-ITS Scenarios
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    Chapter 26 Metaproperty-Guided Deletion from the Instance-Level of a Knowledge Base
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    Chapter 27 On Extracting Relations Using Distributional Semantics and a Tree Generalization
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    Chapter 28 A Query Model for Ontology-Based Event Processing over RDF Streams
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    Chapter 29 A Random Walk Model for Entity Relatedness
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    Chapter 30 Slicing and Dicing a Newspaper Corpus for Historical Ecology Research
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    Chapter 31 Using SPARQL – The Practitioners’ Viewpoint
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    Chapter 32 Combining Machine Learning and Semantics for Anomaly Detection
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    Chapter 33 EROSO: Semantic Technologies Towards Thermal Comfort in Workplaces
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    Chapter 34 Divided We Stand Out! Forging Cohorts fOr Numeric Outlier Detection in Large Scale Knowledge Graphs (CONOD)
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    Chapter 35 Decision Support Models to Assist in the Diagnosis of Meningitis
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    Chapter 36 A Framework to Conduct and Report on Empirical User Studies in Semantic Web Contexts
Overall attention for this book and its chapters
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Mentioned by

27 tweeters
1 Wikipedia page


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7 Mendeley
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Knowledge Engineering and Knowledge Management
Published by
Springer International Publishing, January 2019
DOI 10.1007/978-3-030-03667-6
978-3-03-003666-9, 978-3-03-003667-6

Faron Zucker, Catherine, Ghidini, Chiara, Napoli, Amedeo, Toussaint, Yannick

Twitter Demographics

The data shown below were collected from the profiles of 27 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 57%
Professor 1 14%
Student > Master 1 14%
Unknown 1 14%
Readers by discipline Count As %
Computer Science 3 43%
Energy 1 14%
Social Sciences 1 14%
Engineering 1 14%
Unknown 1 14%