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

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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:
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.