Knowledge Engineering and Knowledge Management: 21st International Conference, EKAW 2018, Nancy, France, November 12-16, 2018, Proceedings.

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Bibliographic Details
Authors and Corporations:	Faron Zucker, Catherine, Ghidini, Chiara, Napoli, Amedeo, Toussaint, Yannick
Other Authors:	Ghidini, Chiara. [] • Napoli, Amedeo. [] • Toussaint, Yannick. []
Edition:	1st ed.
Type of Resource:	E-Book
Language:	English
published:	Cham : Springer International Publishing AG, 2018. ©2018.
Series:	Lecture Notes in Computer Science Series
Subjects:	Knowledge acquisition (Expert systems)-Congresses. Electronic books.
Source:	Ebook Central
ISBN:	9783030036676

Table of Contents:

Intro
Preface
Program Committee
Contents
Research Papers
An Empirical Evaluation of RDF Graph Partitioning Techniques
1 Introduction
2 RDF Graph Partitioning
3 Evaluation
3.1 Evaluation Setup
3.2 Evaluation Results
4 Related Work
5 Conclusion and Future Work
References
Fuzzy Semantic Labeling of Semi-structured Numerical Datasets
1 Introduction
2 Related Work
3 Approach
3.1 Training-Data Extraction
3.2 Fuzzy Clustering
4 Evaluation
4.1 Olympic Games Dataset
4.2 Web Data Commons Dataset
4.3 Discussion
5 Future Work
References
From Georeferenced Data to Socio-Spatial Knowledge. Ontology Design Patterns to Discover Domain-Specific Knowledge from Crowdsourced Data
1 Introduction
2 Background
2.1 Computational Ontologies and Ontology Design Patterns
2.2 Ontology and Knowledge Discovery
3 ODPs of the Urban Environment: An Overview
3.1 Urban Artefact
3.2 Social Practice
3.3 Urban Artefacts Roles
4 An Experiment Using a Real-Data Sample
4.1 Data Extraction, Selection, Preprocessing and Transformation
4.2 Data Mining
4.3 Mapping and Ontology Based Data Access
5 Conclusion
References
Conceptual Schema Transformation in Ontology-Based Data Access
1 Introduction
2 Motivation
2.1 The Order Scenario
2.2 Challenges
3 Ontology-Based Data Access
4 2-Level Ontology Based Data Access
5 Using Annotations for Specifying Schema Transformations
6 Conclusions
References
SWRL Reasoning Using Decision Tables
1 Introduction
2 Preliminaries
2.1 Ontologies
2.2 SWRL Rules
2.3 SWRL Reasoning
3 Related Works
4 Naive Propositionalization
5 Typed Propositionalization
5.1 Reasoning with Typed Propositionalization
5.2 Rule Chaining
5.3 Handling OWL Axioms
5.4 Complexity
6 Experiments.
6.1 Settings
6.2 Results
7 Conclusion and Future Works
References
A Framework for Explaining Query Answers in DL-Lite
1 Introduction
2 Background
3 Framework
3.1 Explanations for Positive Queries
3.2 Explanations for Negative Queries
3.3 The Notion of Variant in DL-Lite
3.4 Weighting Explanations
4 Computing Explanations for Positive Queries
5 Computing Explanations for Negative Queries
6 Conclusions
References
DLFoil: Class Expression Learning Revisited
1 Introduction
2 Related Work
3 The Concept Learning Problem
3.1 Notation
3.2 Learning Concepts in DLs
3.3 Refinement Operators
4 The Revised Learning Algorithm
4.1 Specialization of Partial Definitions
4.2 Heuristics for Best Specialization Selection
4.3 Discussion
5 Empirical Evaluation
5.1 Experimental Design and Setup
5.2 Results
5.3 Examples of Induced Definitions
6 Conclusions and Outlook
References
Requirements Behaviour Analysis for Ontology Testing
1 Introduction
2 Related Work
3 Ontology Testing Framework
3.1 Test Design
3.2 Test Implementation
3.3 Test Execution
4 Testing process
5 Evaluation
6 Conclusions and Future Work
References
Interactive Interpretation of Serial Episodes: Experiments in Musical Analysis
1 Introduction
2 Related Works
3 Transmute
4 Interactive Interpretation of Serial Episodes
4.1 Definitions
4.2 Post-processing and Interactive Interpretation
5 Experiments
6 Discussion
7 Conclusion and Future Work
References
Network Metrics for Assessing the Quality of Entity Resolution Between Multiple Datasets
1 Introduction
2 Identity Link Networks
3 Related Work
4 Network Properties and Quality of a Link-Network
5 Datasets
6 eQ Put to the Test
6.1 Experiment Design.
6.2 Results of First Evaluation
6.3 Results of Second Evaluation
6.4 Analysis
7 eQ Estimations in Noisy Settings
7.1 Experiment Design
7.2 Strict vs. Liberal Clustering
7.3 Result and Analysis
8 eQ Put to a Ranking Test
9 Conclusions and Future Work
9.1 Conclusion
9.2 Future Work
References
Making Sense of Numerical Data - Semantic Labelling of Web Tables
1 Introduction
2 Problem Statement
3 Related Work
4 Approach
5 Evaluation
5.1 Benchmark
5.2 Evaluation Results
6 Discussion and Limitations
7 Conclusion and Future Work
References
Towards Enriching DBpedia from Vertical Enumerative Structures Using a Distant Learning Approach
1 Introduction
2 Background
2.1 Distant Learning
2.2 Vertical Enumerative Structures
3 Proposed Approach
3.1 Learning Examples Building
3.2 Learning Model
4 Experiments
4.1 Corpus
4.2 Learning Examples
4.3 Evaluation Setting
4.4 Results and Discussion
4.5 DBpedia Enrichment
5 Related Work
6 Conclusion and Future Work
References
The Utility of the Abstract Relational Model and Attribute Paths in SQL
1 Introduction
2 Background
3 On Deriving ARM Schemata from RM Schemata
4 User Evaluation
4.1 Experimental Design
4.2 Results and Discussion
5 Related Work
6 Conclusions
References
Support and Centrality: Learning Weights for Knowledge Graph Embedding Models
1 Introduction
2 Related Work
3 Methodology
3.1 Rule Mining
3.2 Rule Instantiation
3.3 Triple Inference Graph Construction and Weights Calculation
3.4 Learning a Weighted Knowledge Graph Embedding Model
4 Experiment
5 Conclusion
References
OmniScience and Extensions - Lessons Learned from Designing a Multi-domain, Multi-use Case Knowledge ...
Abstract
1 Introduction.
2 Use Cases for a Multi-KOS Model
3 We Are One
4 And We Are Multiple
5 Semantic Search in the Engineering Domain Proof of Concept
6 Conclusion
Acknowledgements
References
A Semantic Use Case Simulation Framework for Training Machine Learning Algorithms
1 Introduction
2 Related Work
3 Approach
3.1 The Framework Architecture
3.2 The Simulation Meta-model
3.3 The Generation of Numerical State Representations
3.4 State Reasoning Using SPARQL Queries
3.5 The Reasoning of Rewards
4 Proof-of-Concept
4.1 The Chronic Kidney Disease Pathway
4.2 Intelligent Smart Home Control Systems
5 Evaluation
6 Conclusion and Outlook
References
KnIGHT: Mapping Privacy Policies to GDPR
1 Introduction
2 Related Work
3 Approach
3.1 Preparation
3.2 Semantic Text Matching
4 Evaluation and Discussion
4.1 Posteriori Assessment
4.2 Potential End-Users Impact
4.3 Discussion
5 Conclusion and Future Work
References
Automating Class/Instance Representational Choices in Knowledge Bases
1 Introduction
1.1 Contributions
2 Related Work
3 Approach
3.1 Word Representation Learning
3.2 Bag-of-Embeddings
3.3 Sub-syntactic Representation Learning
3.4 Document Representation and Classification
3.5 Training
4 Experiments
4.1 Datasets
4.2 Baseline Approaches
5 Discussion
6 Analysis of Sub-syntactic Representations
7 Conclusion and Future Work
References
Comparative Preferences in SPARQL
1 Introduction
2 Foundations and Motivation
3 Previous Work
4 Simple Comparative Preferences
5 Non-Simple Comparative Preferences
6 Comparative Preferences in SPARQL
7 Implementing SPARQL Preferences
8 Multiple Skylines
9 Conclusions
References
Interplay of Game Incentives, Player Profiles and Task Difficulty in Games with a Purpose.
1 Introduction
2 Related Work
3 Use Case: The Night Knights GWAP
4 Extending GWAP Metrics
4.1 [Q1] How Do User Participation and GWAP Results Change with Different Incentives?
4.2 [Q2] Do the Extrinsic Reward Effects Last over Time?
4.3 [Q3] Does Playing Style Change with the Incentive?
5 Applying Citizen Science Engagement Profiles
5.1 [Q4] How Does GWAP Behaviour Compare to Traditional Citizen Science Engagement?
5.2 [Q5] What Does Player Behaviour Tell About the Game Nature?
6 Defining GWAP Engagement Profiles
6.1 [Q6] What Kind of GWAP Player Profiles Can Be Identified?
6.2 [Q7] Does Player Behaviour Change with Different Incentives?
6.3 [Q8] Does Player Behaviour Change with Task Difficulty?
6.4 [Q9] Does Player Behaviour Change with Task Variety?
7 Conclusions
References
Inferring Types on Large Datasets Applying Ontology Class Hierarchy Classifiers: The DBpedia Case
1 Introduction
2 Related Work
3 Methodology
3.1 Type Paths in DBpedia Resources
3.2 Features Description
3.3 Approach 1: Naive Approach for Type Prediction
3.4 Approach 2: Ontology Class Hierarchy for Type Prediction
4 Evaluation
4.1 SDType Evaluation
4.2 K-Fold Evaluation
4.3 Gold Standard
4.4 A Novel Set of Measure Criteria
5 Results
5.1 Comparison with SDType Results
5.2 Comparison with K-Fold Results
5.3 Comparison with Gold Standard Results
6 Conclusions and Future Work
References
A Framework for Tackling Myopia in Concept Learning on the Web of Data
1 Introduction
2 Related Work
3 Concept Learning Problem and Hill-Climbing Optimization
3.1 Notation
3.2 Learning Concepts in DLs
3.3 Refinement Operators
3.4 The Hill-Climbing Optimization Strategy
4 The DL-Focl Framework
4.1 The DL-Foil Algorithm
4.2 DL-Focl I: Repeated Sequential Covering.
4.3 DL-Focl II: Sequential Covering with Lookahead.