
The Semantic Web
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The paper 'Linked Data Notifications: A Resource-Centric Communication Protocol' is published open access under a CC BY 4.0 license at link.springer.com.
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Content
- Intro
- Preface
- Organization
- Abstract of Keynotes
- Bringing Semantic Intelligence to Financial Markets
- Disrupting the Semantic Comfort Zone
- Semantic Web Technologies for Digital Archives
- Contents - Part I
- Contents -- Part II
- Semantic Data Management, Big Data, and Scalability Track
- Traffic Analytics for Linked Data Publishers
- 1 Introduction
- 2 Related Work
- 3 System Overview
- 4 Traffic Metrics
- 4.1 Content Metrics Extraction
- 4.2 Protocol Metrics Extraction and SPARQL Queries Weight
- 4.3 Audience Metrics Extraction and Visitor Session Identification
- 5 Results
- 6 Conclusions and Future Work
- References
- Explaining Graph Navigational Queries
- 1 Introduction
- 2 Related Work
- 3 Building Query Explanations with GeL
- 3.1 Syntax of GeL
- 3.2 Semantics of GeL
- 4 Algorithms and Complexity
- 4.1 Translating GeL into SPARQL
- 5 Implementation and Evaluation
- 6 Concluding Remarks and Future Work
- References
- A SPARQL Extension for Generating RDF from Heterogeneous Formats
- 1 Introduction
- 2 Use-Cases and Requirements
- 3 Related Work
- 4 SPARQL-Generate Specification
- 4.1 SPARQL-Generate Concrete Syntax
- 4.2 Abstract Syntax
- 4.3 SPARQL-Generate Semantics
- 5 Implementation and Evaluation
- 5.1 Generic Approach
- 5.2 Implementation on Top of Apache Jena
- 5.3 Evaluation
- 6 Conclusion and Future Work
- References
- Linked Data Track
- Exploiting Source-Object Networks to Resolve Object Conflicts in Linked Data
- 1 Introduction
- 2 Preliminaries
- 2.1 Basic Definitions
- 2.2 Problem Analysis
- 3 ObResolution Method
- 3.1 Model Details
- 3.2 Inference Algorithms
- 3.3 Practical Issues
- 4 Evaluation
- 4.1 The Datasets
- 4.2 Comparative Methods and Metrics
- 4.3 Results
- 5 Related Work
- 6 Conclusion and Future Work
- References
- Methods for Intrinsic Evaluation of Links in the Web of Data
- 1 Introduction
- 2 Preliminaries
- 3 Principles for Data Interlinking in the Web of Data
- 4 Intrinsic Measures for Assessing the Quality of Links
- 4.1 Basic Descriptive Statistics
- 4.2 Principles-Based Measures
- 5 Empirical Analysis
- 5.1 Data
- 5.2 Methodology
- 5.3 Measure Validation
- 5.4 Results
- 6 Related Work
- 7 Conclusions and Future Work
- References
- Entity Deduplication on ScholarlyData
- 1 Introduction
- 2 Related Work
- 3 Deduplication
- 3.1 Blocking Strategies
- 3.2 Classification
- 3.3 URI Harmonisation
- 4 Experiments
- 4.1 The Train/test Dataset
- 4.2 Blocking
- 4.3 Classification
- 4.4 URI Harmonisation
- 5 Conclusions
- References
- Machine Learning Track
- WOMBAT -- A Generalization Approach for Automatic Link Discovery
- 1 Introduction
- 2 Preliminaries
- 3 Constructing and Traversing Link Specifications
- 3.1 Learning Atomic Specifications
- 3.2 Combining Atomic Specifications
- 4 The WOMBAT Algorithm
- 5 Evaluation
- 6 Related Work
- 7 Conclusions and Future Work
- References
- Actively Learning to Rank Semantic Associations for Personalized Contextual Exploration of Knowledge Graphs
- 1 Introduction
- 2 Contextual KG Exploration
- 3 Active Learning to Rank for Semantic Associations
- 3.1 Features
- 4 Experiments
- 4.1 Experimental Settings
- 4.2 Configurations and Baselines
- 4.3 Results and Discussion
- 5 Related Work
- 6 Conclusion
- References
- Synthesizing Knowledge Graphs for Link and Type Prediction Benchmarking
- 1 Introduction
- 2 Related Work
- 3 Knowledge Graph Model
- 4 Synthesis Process
- 5 Experiments
- 6 Conclusion and Outlook
- References
- Online Relation Alignment for Linked Datasets
- 1 Introduction
- 2 Related Work
- 3 Preliminaries
- 4 Problem Statement
- 5 SORAL: Relation Alignment
- 5.1 Candidate Generation
- 5.2 Sampling Strategies
- 5.3 Features
- 6 Experimental Setup
- 7 Results and Discussion
- 7.1 Relation Alignment Accuracy
- 7.2 Query-Execution Overhead
- 8 Conclusion
- References
- Tuning Personalized PageRank for Semantics-Aware Recommendations Based on Linked Open Data
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 3.1 Graph-Based Representations
- 3.2 Running Personalized PageRank
- 4 Experimental Evaluation
- 4.1 Experimental Protocol
- 4.2 Discussion of the Results
- 5 Conclusions and Future Work
- References
- Terminological Cluster Trees for Disjointness Axiom Discovery
- 1 Introduction
- 2 Related Work
- 3 Disjointness Discovery as a Conceptual Clustering Problem
- 4 Terminological Cluster Trees for Disjointness Learning
- 4.1 Growing Terminological Cluster Trees
- 4.2 Extracting Candidate Disjointness Axioms from TCTs
- 5 Experiments
- 5.1 Re-discovery of a Target Disjoint Axiom
- 5.2 Comparison to Other Approaches Under SDA
- 6 Conclusions and Outlook
- References
- Embedding Learning for Declarative Memories
- 1 Introduction
- 2 Unique-Representation Hypothesis
- 3 Semantic and Episodic Knowledge Graph Models
- 3.1 Semantic Knowledge Graph
- 3.2 An Event Model for Episodic Memory
- 4 Tensor Decompositions
- 4.1 Tensor Decompositions
- 4.2 Inner Product Formulation of Tensor Decompositions
- 5 Querying Memories
- 5.1 Probabilistic Querying
- 5.2 Semantic Memory Derived from Episodic Memory
- 6 Relationships to Human Memories
- 6.1 Unique-Representation Hypothesis for Entities and Predicates
- 6.2 Perception and Memory Formation
- 6.3 Tensor Memory Hypothesis
- 6.4 Semantic Memory and Episodic Memory
- 7 Experiments
- 7.1 Data Set
- 7.2 Evaluation and Implementation
- 7.3 Experimental Results
- 8 Conclusions
- References
- Mobile Web, Sensors, and Semantic Streams Track
- Spatial Ontology-Mediated Query Answering over Mobility Streams
- 1 Introduction
- 2 V2X Integration using a Local Dynamic Map
- 3 Streams, Pulses, and Spatial Databases
- 4 Syntax, Semantics, and Query Language of DL-LiteA (S,F)
- 5 Query Rewriting by Stream Aggregation
- 6 Query Evaluation by Hypertree Decomposition
- 7 Implementation and Experimental Evaluation
- 8 Related Work and Conclusion
- References
- Optimizing the Performance of Concurrent RDF Stream Processing Queries
- 1 Introduction
- 2 Foundations
- 2.1 Multi-way Join
- 2.2 Shared Join Operator and Network of Shared Join Operators
- 3 Optimization for Concurrent CQELS Queries
- 3.1 CQELS+: Network of Shared Join Operators
- 3.2 Load Balancing for Parallel CQELS+ Instances
- 4 Evaluation
- 4.1 Evaluating Shared Joins in CQELS+
- 4.2 Evaluating Load Balancing over CQELS+
- 4.3 Evaluating the Query Registration Time
- 5 Related Work
- 6 Conclusions and Future Work
- References
- AGACY Monitoring: A Hybrid Model for Activity Recognition and Uncertainty Handling
- 1 Introduction
- 2 Related Work
- 3 The AGACY Monitoring Architecture Overview
- 4 Knowledge Based Layer
- 4.1 Ontological Modeling
- 4.2 Semantic Reasoning
- 5 Data Driven Layer
- 5.1 Time and Uncertainty-Based Features Extraction
- 5.2 Dempster-Shafer Theory for Activity Classification
- 5.3 Activities Instances Inferring Under Uncertainty
- 6 Evaluation and Discussion
- 6.1 DataSet
- 6.2 Implementation and Experimental Setup
- 6.3 Evaluation and Results
- 7 Conclusion and Future Work
- References
- Natural Language Processing and Information Retrieval Track
- Mapping Natural Language to Description Logic
- 1 Introduction
- 2 Related Work
- 3 Approach Overview
- 3.1 Grammar
- 3.2 Semantic Parser and Surface Realiser
- 4 Evaluation and Results
- 4.1 Mapping SIDPs to Complex Axioms
- 4.2 Assessing Correctness
- 4.3 Ontology Enrichment
- 5 Conclusion
- References
- Harnessing Diversity in Crowds and Machines for Better NER Performance
- 1 Introduction
- 2 Use Case and Datasets
- 3 Related Work
- 3.1 Open Knowledge Extraction Systems
- 3.2 Crowdsourcing Named Entities
- 3.3 Multi-NER, Hybrid Named Entity Recognition
- 4 Single-NER vs. Multi-NER Comparison
- 4.1 Single-NER vs. Multi-NER - Entity Surface
- 4.2 Single-NER vs. Multi-NER - Entity Surface and Entity Type
- 4.3 Analysis of False Negative Named Entities
- 4.4 Analysis of False Positive Named Entities
- 5 Experimental Setup
- 5.1 Crowdsourcing Experimental Data
- 5.2 Crowdsourcing Annotation Task
- 5.3 CrowdTruth Metrics
- 6 Results
- 7 Discussion
- 8 Conclusion
- References
- All that Glitters Is Not Gold -- Rule-Based Curation of Reference Datasets for Named Entity Recognition and Entity Linking
- 1 Introduction
- 2 Related Work
- 3 Formal Annotation Framework
- 3.1 Assumptions
- 3.2 Rule Set
- 3.3 Comparison with Related Work
- 3.4 Observations
- 4 Eaglet
- 4.1 Preprocessing Module
- 4.2 Completion Module
- 4.3 Error Detection Pipeline
- 4.4 Review Module
- 5 Evaluation
- 5.1 Experiment I
- 5.2 Experiment II
- 5.3 Experiment III
- 6 Conclusion
- References
- Semantic Annotation of Data Processing Pipelines in Scientific Publications
- 1 Introduction
- 2 Related Work
- 3 The DMS Ontology
- 4 DPP Knowledge Extraction Workflow
- 4.1 Training Data Generation
- 4.2 Classification and NER
- 4.3 Linked Data Generation
- 5 Evaluation
- 5.1 Dataset
- 5.2 Analysis of Rhetorical Classifiers
- 5.3 Quality of Extracted Entities
- 6 Conclusion
- References
- Combining Word and Entity Embeddings for Entity Linking
- 1 Introduction
- 2 Related Work
- 3 Combining Word and Entity Embeddings
- 3.1 Definitions
- 3.2 Extended Anchor Text
- 3.3 The EAT Model
- 4 Entity Linking System
- 4.1 Generation of Candidate Entities
- 4.2 Selection of the Best Candidate Entity
- 5 Experiments and Results
- 5.1 Learning the Embeddings
- 5.2 Evaluation of the Embeddings
- 5.3 Dataset and Evaluation Measures for Entity Linking
- 5.4 Evaluation of Candidate Entity Generation
- 5.5 Entity Linking Results
- 6 Conclusion
- References
- Beyond Time: Dynamic Context-Aware Entity Recommendation
- 1 Introduction
- 2 Background and Problem Definition
- 2.1 Preliminaries
- 2.2 Problem Definition
- 3 Approach
- 3.1 Probabilistic Model
- 3.2 Candidate Entity Identification
- 3.3 Graph Enrichment
- 4 Model Parameter Estimation
- 4.1 Temporal Relatedness Model
- 4.2 Topical Relatedness Model
- 5 Experiment Setup
- 5.1 Entity Graph Construction
- 5.2 Automated Queries Construction
- 5.3 Baselines
- 6 Results and Discussion
- 7 Related Work
- 8 Conclusions
- References
- Vocabularies, Schemas, and Ontologies Track
- Patterns for Heterogeneous TBox Mappings to Bridge Different Modelling Decisions
- 1 Introduction
- 2 Related Works
- 3 Formal Representation of Patterns and Alignments
- 4 Aligning Alternate Modelling Patterns
- 4.1 Matching Modelling Patterns
- 4.2 Assessment and Formalisation of Other Correspondence Patterns
- 5 Alignment Pattern Search and Checking Algorithms
- 6 Discussion
- 7 Conclusions
- References
- Exploring Importance Measures for Summarizing RDF/S KBs
- 1 Introduction
- 2 Preliminaries
- 3 Importance Measures
- 3.1 Adapted Importance Measures
- 4 Construction of the RDF/S Summary Schema Graph
- 4.1 Algorithms, Approximation and Heuristics
- 5 Evaluation
- 5.1 Spearman's Rank Correlation Coefficient
- 5.2 The Similarity Measure
- 5.3 Additional Nodes Introduced
- 5.4 Execution Time
- 6 Related Work
- 7 Discussion and Conclusion
- References
- Data-Driven Joint Debugging of the DBpedia Mappings and Ontology
- 1 Introduction
- 2 Related Work
- 3 Approach
- 3.1 Preliminaries
- 3.2 Datasets Used
- 3.3 Identifying and Grouping Inconsistencies
- 3.4 Scoring Inconsistencies
- 4 Findings
- 4.1 Quantitative Results
- 4.2 Mapping Errors
- 4.3 Problems in the Ontology
- 4.4 Problems with the Mapping to DOLCE-Zero
- 5 Conclusion and Outlook
- References
- Rule-Based OWL Modeling with ROWLTab Protégé Plugin
- 1 Introduction
- 2 SWRL Rules to OWL Axioms Transformation
- 3 Plugin Description and Features
- 4 Evaluation
- 4.1 Time Used for Modeling
- 4.2 Correctness of Modeled Axioms
- 4.3 Participant Survey
- 5 Conclusions and Further Work
- References
- Chaudron: Extending DBpedia with Measurement
- 1 Introduction
- 2 Measurement
- 2.1 Measurement in Wikipedia's Infoboxes
- 3 Measures Extraction
- 3.1 Infobox Parsing and Filtering
- 3.2 List of Units
- 3.3 Extraction with Formal Grammar
- 3.4 Extraction and Discussion
- 4 Dataset
- 5 Availability and Applications
- 6 Evaluation
- 7 Conclusion and Future Work
- References
- SM4MQ: A Semantic Model for Multidimensional Queries
- 1 Introduction
- 2 Background
- 2.1 Multidimensional Model and OLAP Operations
- 2.2 The Semantic Web Technologies
- 3 A Semantic Model for Multidimensional Queries
- 3.1 MD Query Model
- 3.2 ROLL-UP and DRILL-DOWN Operations
- 3.3 DICE Operation
- 3.4 SLICE Operation
- 4 Exploiting SM4MQ
- 4.1 Modeling and Semantics
- 4.2 Automating SM4MQ Exploitation
- 5 Use Case Evaluation
- 6 Related Work
- 7 Conclusion and Future Work
- References
- Using Insights from Psychology and Language to Improve How People Reason with Description Logics
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Human Reasoning and Human Language
- 4 Previous Studies
- 5 Overview of Current Study
- 6 Functional and Inverse Functional Object Properties
- 6.1 Functional Object Properties - Comparison with Study 2
- Hypothesis H1
- 6.2 Inverse Functional Object Properties
- Hypothesis H2
- 7 Boolean Concept Constructors
- 7.1 Negated Conjunction and Disjunction
- Hypotheses H3
- 7.2 Use of Prefix Notation
- Hypothesis H4
- 7.3 Use of except in Place of and not
- Hypothesis H5
- 8 Negation and Restriction
- 8.1 noneOrOnly and including
- Hypothesis H6
- 8.2 not . any
- Hypothesis H7
- 9 Nested Restrictions
- 9.1 noneOrOnly and including
- Hypothesis H6
- 9.2 not . any
- Hypothesis H7
- 10 Conclusions and Future Work
- Acknowledgements
- References
- Reasoning Track
- Updating Wikipedia via DBpedia Mappings and SPARQL
- 1 Introduction
- 2 The DBpedia OBDM Setting
- 3 Challenges of DBpedia OBDM
- 4 Pragmatic DBpedia OBDM
- 4.1 Update Translation Steps
- 4.2 Update Resolution Policies
- 5 Related Work
- 6 Conclusion
- References
- Learning Commonalities in RDF
- 1 Introduction
- 2 The Resource Description Framework (RDF)
- 3 Finding Commonalities Between RDF Graphs
- 3.1 Defining the lgg of RDF Graphs
- 3.2 Computing an lgg of RDF Graphs
- 4 Algorithms
- 4.1 Least General Anti-unifier of Triples
- 4.2 lgg of RDF Graphs
- 5 Related Work and Conclusion
- References
- Lean Kernels in Description Logics
- 1 Introduction
- 2 Preliminaries
- 3 Lean Kernels
- 4 Computing Lean Kernels
- 5 Experiments
- 6 Conclusions
- References
- Social Web and Web Science Track
- Linked Data Notifications: A Resource-Centric Communication Protocol
- 1 Introduction
- 2 Related Work
- 3 Requirements and Design Considerations
- 3.1 R1 Modularity
- 3.2 R2 Reusable Notifications
- 3.3 R3 Persistence and Retrievability
- 3.4 R4 Adaptability
- 3.5 R5 Subscribing
- 4 The LDN Protocol
- 4.1 Sender to Receiver Interactions
- 4.2 Consumer to Receiver Interactions
- 4.3 Example Notifications
- 5 Implementations
- 6 Analysis and Evaluation
- 6.1 Comparison Summary
- 6.2 Compatibility with Existing Systems
- 6.3 Optimising Implementation
- 6.4 Data Formats and Content Negotiation
- 6.5 Precision
- 6.6 Accommodating Different Targets
- 7 Conclusions
- References
- Crowdsourced Affinity: A Matter of Fact or Experience
- Abstract
- 1 Introduction
- 2 Related Work
- 3 First Experiment: Gold Standard Study
- 3.1 Experiment Dataset
- 3.2 Folksonomy Engineering
- 3.3 Knowledge Graph Engineering
- 3.4 Candidate Approaches
- 3.5 Common Affinity Prediction Algorithm
- 3.6 Protocol
- 3.7 Quality Dimensions and Metrics
- 3.8 Results and Discussions
- 4 Semantic Affinity Framework
- 5 Second Experiment: User Study
- 5.1 Protocol and Metrics
- 5.2 Results and Discussions
- 6 Conclusion
- References
- A Semantic Graph-Based Approach for Radicalisation Detection on Social Media
- 1 Introduction
- 2 Related Work
- 3 Semantic Graph-Based Approach for Pro-ISIS Stance Detection
- 4 Experimental Setup
- 4.1 Dataset of pro-ISIS and anti-ISIS Twitter Users
- 4.2 Baseline Features
- 4.3 Classification Method
- 5 Evaluation Results
- 6 Signals of Radicalisation (pro-ISIS vs. anti-ISIS)
- 7 Discussion and Future Work
- 8 Conclusions
- References
- Semantic Web and Transparency Track
- Modeling and Querying Greek Legislation Using Semantic Web Technologies
- 1 Introduction
- 2 Related Work
- 3 Background on Greek Legislation
- 3.1 Types and Encoding of Greek Legislation
- 3.2 Metadata of Greek Legislation
- 3.3 Legislative Modifications
- 4 Modeling Greek Legislation Using Semantic Web Technologies
- 4.1 An OWL Ontology for Greek Legislation
- 4.2 Persistent URIs in Nomothesia
- 4.3 Population of Nomothesia Ontology
- 4.4 Linking Legislation with Other Open Data
- 5 Modeling Greek Legislation Using Nomothesia: A Short Example
- 5.1 Representing P.D. 2011/54 in RDF
- 5.2 Capturing the Legislative Interaction between P.D. 2011/54 and P.D. 2012/10
- 5.3 Linking P.D. 2011/54 with Greek administration Geography
- 5.4 Querying the Resulting RDF Data Using SPARQL
- 6 The Nomothesia Web Platform and RESTful API
- 6.1 Querying Legislation Using SPARQL
- 7 Preliminary Feedback on Nomothesia
- 8 Conclusions and Future Work
- References
- Self-Enforcing Access Control for Encrypted RDF
- 1 Introduction
- 2 Related Work
- 3 Secure and Fine-Grained Encryption of RDF
- 3.1 A Functional Encryption Scheme for RDF
- 4 Optimising Query Execution over Encrypted RDF
- 5 Evaluation
- 6 Conclusion
- References
- Removing Barriers to Transparency: A Case Study on the Use of Semantic Technologies to Tackle Procurement Data Inconsistency
- 1 Introduction and Motivations
- 2 Study Context
- 2.1 The Italian Legislative Context
- 2.2 Source Data
- 3 Data Quality Problems
- 3.1 Interdependence Between Quality Metrics
- 3.2 Focus on Data Consistency
- 4 Applying the Linked Data Approach
- 4.1 Harvesting of XML Files
- 4.2 Cleaning of Procurement Data
- 4.3 Public Contracts Ontology
- 4.4 Triplification and Interlinking
- 5 Results
- 5.1 Harvesting Results
- 5.2 Quality Problems Addressed
- 6 Discussion on Inconsistency Issues
- 6.1 Limitations
- 7 Related Work
- 8 Conclusion and Future Works
- References
- NdFluents: An Ontology for Annotated Statements with Inference Preservation
- 1 Introduction
- 2 Welty and Fikes' 4dFluents Ontology
- 3 The NdFluents Ontology
- 4 Design Patterns
- 4.1 Contexts in Context
- 4.2 Use Multiple Contextual Extents on Each Contextual Part
- 4.3 Combine Different Contexts on One Contextual Extent
- 5 Additional Considerations
- 5.1 Dealing with Datatype Properties
- 5.2 Relations Between ContextualParts of Different Dimensions
- 6 Reasoning with Annotated Data
- 6.1 RDF Representation Approaches
- 6.2 Comparison of Rule Preservation
- 7 Related Work
- 8 Conclusions
- References
- Adopting Semantic Technologies for Effective Corporate Transparency
- 1 Introduction
- 2 XBRL Fundamentals
- 3 Related Work
- 4 Transforming XBRL into Linked Data
- 4.1 Lightweight Vocabulary for XBRL (XBRLL)
- 4.2 From XBRL Data to Linked Data
- 4.3 Linking XBRL Data to Other Data
- 5 Validation
- 6 Discussion
- 7 Conclusions and Further Research
- References
- Author Index
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