
The Semantic Web
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This book constitutes the refereed proceedings of the 15th International Semantic Web Conference, ESWC 2018, held in Heraklion, Crete, Greece.
The 48 revised full papers presented were carefully reviewed and selected from 179 submissions. The papers cover a large range of topics such as logical modelling and reasoning, natural language processing, databases and data storage and access, machine learning, distributed systems, information retrieval and data mining, social networks, and Web science and Web engineering.More details
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Persons
Content
- Intro
- Preface
- Organization
- Abstracts of Keynotes
- How to Make, Grow, and Sell a Semantic Web Start-Up
- Knowledge Representation and the Semantic Web - An Ontologician's View
- Structural Summarization of Semantic Graphs
- Contents
- Analyzing the Evolution of Vocabulary Terms and Their Impact on the LOD Cloud
- 1 Introduction
- 2 Related Work
- 3 Analysis Method
- 4 Datasets
- 5 Results
- 5.1 The LOD Cloud
- 5.2 Wikidata
- 6 Discussion
- 6.1 The LOD Cloud
- 6.2 Wikidata
- 7 Conclusion and Future Work
- References
- GSP (Geo-Semantic-Parsing): Geoparsing and Geotagging with Machine Learning on Top of Linked Data
- 1 Introduction
- 2 Related Work
- 3 The Geo-Semantic-Parsing Approach
- 3.1 E-GSP: Extracting Additional Geographic Information
- 3.2 GSP-F: Filtering Results to Increase Correctness
- 3.3 E-GSP-F: Expanded GSP with Filtering
- 4 System Implementation
- 4.1 Semantic Annotation
- 4.2 Extraction of Geographic Information
- 4.3 Machine Learning Filtering
- 5 Evaluation
- 5.1 Datasets
- 5.2 Benchmarks
- 5.3 Results
- 6 Conclusions
- References
- LDP-DL: A Language to Define the Design of Linked Data Platforms
- 1 Introduction
- 2 Foundations and Motivations
- 2.1 Requirements
- 2.2 LDP Overview and Current Limitations of Existing Approaches
- 2.3 Our Approach: The LDP Generation Workflow
- 3 LDP Design Language
- 3.1 Illustrative Example
- 3.2 Overview of the Language
- 3.3 Abstract Syntax
- 3.4 Overview of the Formal Semantics
- 4 Implementation and Evaluation
- 4.1 Implementation of LDP Generation Workflow
- 4.2 Evaluation
- 5 Conclusion and Future Work
- References
- Empirical Analysis of Ranking Models for an Adaptable Dataset Search
- 1 Introduction
- 2 Background Knowledge
- 3 Related Work
- 4 Ranking Models Used in the Experiments
- 4.1 Ranking by Cosine Similarity
- 4.2 Ranking by Preferential Attachment
- 4.3 Ranking by Bayesian Probabilities
- 4.4 Ranking with Rule Classifiers
- 5 Data Preparation and Methodology
- 6 Experiments
- 7 Conclusions and Future Work
- References
- sameAs.cc: The Closure of 500M owl:sameAs Statements
- 1 Introduction and Related Work
- 1.1 Related Work
- 1.2 Contributions and Structure of this Paper
- 2 Requirements
- 2.1 Preliminaries
- 2.2 Requirements
- 3 Algorithms and Implementation
- 3.1 Explicit Identity Relation
- 3.2 Explicit Identity Relation: Compaction
- 3.3 Implicit Identity Relation: Closure
- 3.4 Identity Schema
- 4 Data Analytics
- 4.1 Explicit Identity Relation
- 4.2 Implicit Identity Relation
- 4.3 Schema Assertions About Identity
- 5 sameAs.cc: Dataset and Web Service
- 6 Conclusion
- References
- Modeling and Preserving Greek Government Decisions Using Semantic Web Technologies and Permissionless Blockchains
- 1 Introduction
- 2 Related Work
- 3 Background on Diavgeia
- 3.1 Greek Public Sector Decisions and Relevant Laws
- 3.2 Metadata of Decisions
- 3.3 Identifiers and Modifications of Decisions
- 4 Modeling Decisions Using Semantic Web Technologies
- 4.1 The Diavgeia Ontology
- 4.2 Web Editor and Visualizer
- 4.3 Linking Decisions with Other Public Sector Data
- 4.4 Querying the Resulting RDF Data Using SPARQL
- 5 Background on Bitcoin Blockchain
- 6 Preserving Decisions Using Bitcoin Blockchain
- 6.1 Stamper
- 6.2 Guarantees of Stamper
- 6.3 Consistency Verifier
- 7 Experimental Evaluation
- 7.1 Dataset
- 7.2 Test Environment
- 7.3 Experimental Results
- 7.4 Disk Space Reduction
- 8 Conclusions and Future Work
- References
- Towards a Binary Object Notation for RDF
- 1 Introduction
- 2 Related Work
- 2.1 Serializing RDF Data
- 2.2 Processing RDF Data
- 3 Theoretical Background
- 3.1 Definitions
- 3.2 Semantics and Complexity
- 3.3 Summary
- 4 Experiments and Discussion
- 4.1 SPITFIRE Data Sets
- 4.2 Desigo CC Data Set
- 4.3 Results
- 5 Conclusion
- References
- User-Centric Ontology Population
- 1 Introduction
- 2 State of the Art
- 3 Approach
- 3.1 Aligning User's Conceptualization with a Target Ontology
- 3.2 Ontology Maintenance
- 4 Experiments
- 4.1 Aligning User's Conceptualization with a Target Ontology
- 4.2 Ontology Maintenance
- 5 Conclusions and Future Work
- References
- Using Ontology-Based Data Summarization to Develop Semantics-Aware Recommender Systems
- 1 Introduction
- 2 Ontology-Driven Linked Data Summarization
- 3 Semantics-Aware Feature Selection
- 3.1 Feature Selection with Ontology-Based Summaries
- 3.2 Feature Selection with State-of-the-Art Techniques
- 3.3 Recommendation Method
- 4 Experimental Evaluation
- 4.1 Experimental Setup
- 4.2 Results and Discussion
- 5 Related Work
- 6 Conclusions
- References
- PageRank and Generic Entity Summarization for RDF Knowledge Bases
- 1 Introduction
- 2 Resources
- 3 Computation of PageRank on RDF Graphs
- 3.1 Runtime Comparison: Non-HDT Version vs. HDT-Version
- 3.2 Input Comparison: RDF Relations vs. Wikipedia Links
- 4 Re-usable API for Serving Summaries of Entities
- 4.1 The SUMMA API
- 4.2 Implementation Guide
- 5 Use Case: Question Answering
- 5.1 PageRank for Question Answering
- 5.2 Entity Summarization for Question Answering
- 6 Related Work
- 7 Summary
- References
- Answering Multiple-Choice Questions in Geographical Gaokao with a Concept Graph
- 1 Introduction
- 2 Related Work
- 3 Concept Graph Construction
- 3.1 Construct Concept Hierarchy
- 3.2 Add Concept Relations
- 3.3 Extract Concept Descriptions
- 4 Multiple-Choice Question Answering
- 4.1 Question Analysis
- 4.2 Information Enrichment
- 4.3 Inference Path Finding
- 4.4 Judgment and Explanation Generation
- 5 Experiments
- 5.1 Geographical Gaokao Datasets
- 5.2 Geographical Gaokao Concept Graph
- 5.3 Demo
- 5.4 Comparative Approaches
- 5.5 Procedures and Metrics
- 5.6 Results
- 6 Discussion
- 7 Conclusion
- References
- TweetsKB: A Public and Large-Scale RDF Corpus of Annotated Tweets
- 1 Introduction
- 2 Generating TweetsKB
- 2.1 Twitter Archival, Filtering and Processing
- 2.2 Entity Linking and Sentiment Extraction
- 2.3 Data Lifting and Availability
- 2.4 Runtime for Annotation and Triplification
- 3 RDF/S Model for Annotated Tweets
- 4 Use Cases and Sustainability
- 4.1 Scenarios and Queries
- 4.2 Sustainability, Maintenance and Extensibility
- 5 Related Work
- 6 Conclusion
- References
- HDTQ: Managing RDF Datasets in Compressed Space
- 1 Introduction
- 2 State of the Art
- 3 Preliminaries
- 3.1 RDF and SPARQL
- 3.2 HDT
- 4 HDTQ: Adding Graph Information to HDT
- 4.1 Extending the HDT Components
- 4.2 Quad Indexes: Graph and Triples Annotators
- 4.3 Search Operations
- 5 Evaluation
- 5.1 Space Requirements and Indexing Time
- 5.2 Performance for Quad Pattern Resolution
- 6 Conclusions and Future Work
- References
- Answers Partitioning and Lazy Joins for Efficient Query Relaxation and Application to Similarity Search
- 1 Introduction
- 2 Related Work
- 3 Preliminary Definitions
- 4 From Query Relaxation to Similarity Search
- 5 Anytime Partitioning of Approximate Answers
- 6 Optimization with Lazy Joins
- 7 Experiments
- 7.1 Methodology
- 7.2 Efficiency of Query Relaxation
- 7.3 Efficiency of Similarity Search
- 7.4 Effectiveness of Similarity Search
- 8 Conclusion and Perspectives
- References
- Evaluation of Schema.org for Aggregation of Cultural Heritage Metadata
- Abstract
- 1 Introduction
- 2 Motivation and Context
- 3 The Basic Principles for Applying Schema.org to the Cultural Heritage Domain
- 3.1 (Digital) Cultural Heritage Objects Represented in Schema.org
- 3.2 Aggregation Mechanisms for Schema.org Metadata
- 4 Case Studies
- 4.1 Experimental Setup
- 5 Analysis and Discussion
- 5.1 Results of the Mapping from Schema.org to EDM
- 5.2 Analysis of Data Obtained in the Experimental Schema.org-Based Aggregation Setup
- 6 Conclusions
- Acknowledgements
- References
- Dynamic Planning for Link Discovery
- 1 Introduction
- 2 Preliminaries
- 3 Condor
- 3.1 Planning
- 3.2 Plan Evaluation
- 3.3 Execution
- 3.4 Example Run
- 4 Evaluation
- 4.1 Experimental Setup
- 4.2 Results
- 5 Related Work
- 6 Conclusion and Future Work
- References
- A Dataset for Web-Scale Knowledge Base Population
- 1 Introduction
- 2 Knowledge Base Population
- 2.1 Knowledge Graph View
- 2.2 Subtasks of Knowledge Base Population
- 2.3 Variant Definitions
- 2.4 Evaluation
- 3 Related Datasets
- 4 Dataset Creation
- 4.1 Common Crawl
- 4.2 DBpedia
- 4.3 Baseline EDL
- 4.4 Baseline CSC
- 5 Dataset Statistics
- 6 Conclusion and Future Work
- References
- EventKG: A Multilingual Event-Centric Temporal Knowledge Graph
- 1 Introduction
- 2 Relevance
- 3 EventKG Data Model
- 4 EventKG Generation Pipeline
- 5 EventKG Characteristics
- 5.1 Comparison of EventKG to its Reference Sources
- 5.2 Relation and Fusion Statistics
- 5.3 Textual Descriptions
- 6 Reusability Aspects
- 7 Availability and Sustainability
- 8 Related Work
- 9 Conclusion
- References
- Semantic Concept Discovery over Event Databases
- 1 Introduction
- 2 Concept Discovery Framework
- 2.1 Event Data and Knowledge Sources
- 2.2 Ingestion
- 2.3 Curation
- 2.4 Semantic Embeddings Engine
- 2.5 Event Knowledge Graph and Concept Discovery APIs
- 3 Concept Ranking Algorithms
- 3.1 Index-Based Method (co-occur)
- 3.2 Deep Similarity Method Using Semantic Embeddings (context)
- 3.3 Combination Methods
- 4 Experiments
- 4.1 Evaluation Data
- 4.2 Example Results
- 4.3 Evaluation Method
- 4.4 Evaluation Results
- 4.5 Discussion
- 5 Conclusion and Future Work
- References
- Smart Papers: Dynamic Publications on the Blockchain
- 1 Introduction
- 2 Motivating Example
- 3 Related Work
- 4 The Smart Papers Model
- 4.1 Design
- 4.2 Implementation
- 5 Discussion
- 5.1 Identity
- 5.2 Cost
- 6 Evaluation
- 7 Conclusions and Future Work
- References
- Mind the (Language) Gap: Generation of Multilingual Wikipedia Summaries from Wikidata for ArticlePlaceholders
- 1 Introduction
- 2 Related Work
- 3 Methods
- 3.1 Our System
- 4 Training and Automatic Evaluation
- 4.1 Dataset
- 4.2 Automatic Evaluation
- 4.3 Baselines for Automatic Evaluation
- 5 Community Study
- 6 Results and Discussions
- 6.1 Automatic Evaluation
- 6.2 Community Study
- 7 Conclusions
- References
- What Does an Ontology Engineering Community Look Like? A Systematic Analysis of the schema.org Community
- 1 Introduction
- 2 Related Work
- 2.1 Ontology Collaboration
- 2.2 Collaborative Coding with GitHub
- 2.3 Collaborative Ontology Engineering Using GitHub
- 3 Data and Methods
- 3.1 Data
- 3.2 Methods
- 4 Results and Discussion
- 4.1 Topic Prevalence
- 4.2 Topic Popularity
- 4.3 Participation Distribution
- 4.4 Typical User Profiles
- 4.5 Discussion
- 4.6 Limitations and Threats to Validity
- 5 Conclusions and Future Work
- References
- FERASAT: A Serendipity-Fostering Faceted Browser for Linked Data
- 1 Introduction
- 2 FERASAT: A Trigger and Facilitator for Serendipity on Linked Data
- 2.1 Interaction Layer
- 2.2 Data Layer
- 2.3 UI Layer
- 2.4 Adaptation Engine
- 3 Implementation
- 4 Use Cases
- 4.1 Analyzing Change in the Research/Higher Education (HE) Systems
- 4.2 Evaluating Research Portfolios with Regards to Current Societal Challenges
- 5 Related Work
- 6 Conclusions and Future Work
- References
- Classifying Crises-Information Relevancy with Semantics
- 1 Introduction
- 2 Related Work
- 3 Semantic Classification of Crisis-Related Content
- 3.1 Dataset and Data Selection
- 3.2 Features Engineering
- 3.3 Classifier Selection
- 4 Crisis-Related Content Classification Across Crises
- 4.1 Experimental Setting
- 4.2 Results: Crisis Classification
- 4.3 Results: Cross-Crisis Classification
- 5 Discussion and Future Work
- 6 Conclusion
- References
- Efficient Temporal Reasoning on Streams of Events with DOTR
- 1 Introduction
- 2 Background and Motivations
- 3 The DOTR Model
- 4 Implementation
- 5 Evaluation
- 6 Related Work
- 7 Conclusions
- References
- Intelligent Clients for Replicated Triple Pattern Fragments
- 1 Introduction
- 2 Related Work
- 3 Ulysses Approach
- 3.1 Replication Model
- 3.2 Replication-Aware Source Selection for Triple Pattern Fragments
- 3.3 A Cost-Model for Evaluating TPF Servers Capabilities
- 3.4 Accessing TPF Servers Based on Capabilities
- 3.5 Ulysses Adaptive Client-Side Load Balancing with Fault Tolerance
- 4 Experimental Study
- 4.1 Experimental Setup
- 4.2 Experimental Results
- 5 Conclusion and Future Works
- References
- Knowledge Guided Attention and Inference for Describing Images Containing Unseen Objects
- 1 Introduction
- 2 Previous Work on Describing Images with Unseen Objects
- 3 Describing Images with Unseen Objects Using Knowledge Guided Assistance (KGA)
- 3.1 Caption Generation Model
- 3.2 KGA-CGM Training
- 3.3 KGA-CGM Constrained Inference
- 4 Experimental Setup
- 4.1 Resources and Datasets
- 4.2 Multi-label Image Classifiers
- 4.3 Entity-Label Embeddings
- 4.4 Evaluation Measures
- 5 Experiments
- 5.1 Implementation
- 5.2 Describing Out-of-Domain MSCOCO Images
- 5.3 Describing ImageNet Images
- 6 Key Findings
- 7 Conclusion and Future Work
- References
- Benchmarking of a Novel POS Tagging Based Semantic Similarity Approach for Job Description Similarity Computation
- 1 Introduction
- 2 Literature Survey
- 3 Methodology
- 3.1 Document Representation
- 3.2 Document Parsing and Dictionary Creation
- 3.3 Assignment Problem Formulation
- 3.4 Score Calculation
- 3.5 Experimental Setup and Data-Sets
- 4 Evaluation
- 5 Conclusion and Future Work
- References
- A Tri-Partite Neural Document Language Model for Semantic Information Retrieval
- 1 Introduction
- 2 Related Work
- 3 The Tripartite Neural Document Language Model
- 3.1 Neural Network Architecture
- 3.2 Network Training
- 4 Experimental Design
- 4.1 Dataset
- 4.2 Evaluation Methodology
- 4.3 Experimental Setting
- 5 Results
- 5.1 Analyzing the Quality of Document Embeddings
- 5.2 Evaluating the Effectiveness of Learned Embeddings in IR Tasks
- 6 Conclusion
- References
- Multiple Models for Recommending Temporal Aspects of Entities
- 1 Introduction
- 2 Related Work
- 3 Background and Problem Statement
- 3.1 Preliminaries
- 3.2 Problem Definitions
- 4 Our Approach
- 4.1 Aspect Extraction
- 4.2 Time and Type Identification
- 4.3 Time and Type-Dependent Ranking Models
- 4.4 Ranking Features
- 5 Evaluation
- 5.1 Experimental Setting
- 5.2 Cascaded Classification Evaluation
- 5.3 Ranking Aspect Suggestions
- 6 Conclusion
- References
- GDPRtEXT - GDPR as a Linked Data Resource
- 1 Introduction
- 2 Creation of Resource
- 2.1 Motivation
- 2.2 Scope
- 2.3 GDPR as Linked Data
- 2.4 GDPRtEXT Ontology
- 2.5 Documentation
- 3 Linking DPD Obligations with GDPR
- 4 Related Work
- 5 Applications and Benefit to Community
- 6 Conclusion and Future Work
- References
- Transfer Learning for Item Recommendations and Knowledge Graph Completion in Item Related Domains via a Co-Factorization Model
- 1 Introduction
- 2 Related Work
- 3 Learning with a Co-Factorization Model
- 3.1 Factorization Machines for Item Recommendations
- 3.2 Translating Embeddings for KG Completion
- 3.3 Transfer Learning via a Co-Factorization Model for the Two Tasks
- 4 Experiment Setup
- 4.1 Evaluation Metrics
- 4.2 Dataset
- 4.3 Compared Methods
- 5 Results
- 6 Conclusions
- References
- Modeling and Summarizing News Events Using Semantic Triples
- 1 Introduction
- 2 Related Work
- 3 Background
- 4 Improvements and Extensions
- 4.1 Triple Extraction and Grouping
- 4.2 Entity Linking and Predicate Similarity
- 4.3 Fusion Graph and Strict Merging
- 4.4 Summary Sentence Selection
- 5 Experiments
- 5.1 Setup
- 5.2 Results
- 5.3 Manual Evaluation
- 6 Conclusions and Lessons Learned
- References
- GNIS-LD: Serving and Visualizing the Geographic Names Information System Gazetteer as Linked Data
- 1 Introduction and Motivation
- 2 Geometry and the Linked Data Web
- 3 Converting GNIS to Linked Data
- 4 The Dataset
- 5 User Interface
- 6 Availability and Sustainability
- 7 Summary and Future Work
- References
- Event-Enhanced Learning for KG Completion
- 1 Introduction
- 2 Existing Methods for KG Completion
- 3 Event-Enhanced KG Completion
- 3.1 Problem Definition
- 3.2 Limitation of Existing Methods
- 3.3 Adaptation of Joint Model Formulation
- 3.4 Combining LK and LS
- 3.5 Defining LS via Negative Sampling
- 3.6 Defining LS via Autoencoders: EKLAuto Model
- 4 Evaluation
- 4.1 Evaluation Protocol
- 4.2 Dataset Descriptions
- 4.3 Evaluation Results
- 5 Conclusions
- References
- Exploring Enterprise Knowledge Graphs: A Use Case in Software Engineering
- 1 Introduction
- 2 Use Case
- 3 Implementing Exploratory Search: Approach
- 4 Creating the STAR EKG of Architectural Knowledge
- 5 Defining Relatedness Metrics for Exploratory Search
- 6 Evaluation of Relatedness Metrics
- 6.1 Comparative Evaluation of Relatedness Metrics
- 6.2 User Based Evaluation
- 7 System Implementation
- 8 Related Work
- 9 Conclusions and Lessons Learned
- References
- Using Link Features for Entity Clustering in Knowledge Graphs
- 1 Introduction
- 2 Related Work
- 3 Overview
- 4 Approach
- 4.1 Concepts
- 4.2 Entity Clustering with CLIP
- 4.3 Cluster Repair with RLIP
- 5 Evaluation
- 5.1 Datasets and Similarity Graphs
- 5.2 Cluster Quality
- 5.3 Runtimes and Speedup
- 6 Conclusion and Outlook
- References
- Modeling Relational Data with Graph Convolutional Networks
- 1 Introduction
- 2 Neural Relational Modeling
- 2.1 Relational Graph Convolutional Networks
- 2.2 Regularization
- 3 Entity Classification
- 4 Link Prediction
- 5 Empirical Evaluation
- 5.1 Entity Classification Experiments
- 5.2 Link Prediction Experiments
- 6 Related Work
- 6.1 Relational Modeling
- 6.2 Neural Networks on Graphs
- 7 Conclusions
- References
- Ontology-Driven Sentiment Analysis of Product and Service Aspects
- 1 Introduction
- 2 Related Work
- 3 Specification of Data and Tasks
- 4 Method
- 4.1 Ontology Design
- 4.2 Sentiment Computation
- 4.3 Bag-of-Words Model
- 4.4 Bag-of-Words Model with Ontology Features
- 5 Evaluation
- 6 Conclusion
- References
- Frankenstein: A Platform Enabling Reuse of Question Answering Components
- 1 Introduction
- 2 Broader Impact
- 3 Reusable Components and Characteristics
- 4 Approach for Building Reusable QA Components Within Frankenstein
- 4.1 Integration Approach and Its Challenges
- 4.2 Integrating Evaluation Module
- 5 Availability and Sustainability
- 6 Related Work
- 7 Conclusion and Future Work
- References
- Querying APIs with SPARQL: Language and Worst-Case Optimal Algorithms
- 1 Introduction
- 2 Preliminaries
- 3 Enabling SPARQL to Make JSON Calls
- 3.1 Syntax and Semantics of the Extended SERVICE Operator
- 3.2 A Basic Implementation
- 4 A Worst-Case Optimal Algorithm
- 4.1 API Calls as Relational Access Methods
- 4.2 The Algorithm
- 5 Experiments
- 6 Conclusion
- References
- Task-Oriented Complex Ontology Alignment: Two Alignment Evaluation Sets
- 1 Introduction
- 2 Background
- 2.1 Complex Alignments
- 2.2 Tasks Involving Complex Ontology Alignments
- 3 Related Work
- 3.1 Complex Ontology Matchers
- 3.2 Evaluation of Matchers
- 4 Methodology
- 5 Complex Alignment Set
- 5.1 The Conference Dataset
- 5.2 Conference Complex Alignment Sets
- 6 Evaluation of Complex Matchers
- 7 Discussion
- 8 Conclusion and Perspectives
- References
- Where is My URI?
- 1 Introduction
- 2 Related Work
- 3 The Approach
- 3.1 The Index Creation
- 3.2 The Web Interface and the API Service
- 4 Use Cases
- 4.1 Data Quality in Link Repositories
- 4.2 Finding Class Axioms for Link Discovery
- 4.3 Federated Query Processing
- 4.4 Usage Examples
- 5 Statistics About the Datasets
- 6 Conclusion and Future Work
- References
- Optimizing Semantic Reasoning on Memory-Constrained Platforms Using the RETE Algorithm
- Abstract
- 1 Introduction
- 2 OWL2 RL Ruleset
- 3 Using RETE for Reasoning on RDF
- 4 The RETEpool Algorithm
- 4.1 Implementation of RETEpool
- 4.2 Reciprocal Join Issue
- 5 Semantic Reasoning Benchmarks
- 5.1 Benchmark Setup
- 5.1.1 Baseline System
- 5.1.2 OWL2 RL Ontologies and Ruleset
- 5.1.3 Benchmark Platforms
- 5.1.4 RETEpool Configurations
- 5.1.5 Benchmark Metrics
- 5.2 Benchmark Results
- 6 Related Work
- 7 Conclusions and Future Work
- References
- Efficient Ontology-Based Data Integration with Canonical IRIs
- 1 Introduction
- 2 Preliminaries
- 2.1 RDF and SPARQL
- 2.2 SPARQL Entailment Regimes
- 2.3 SPARQL Entailment Regimes for sameAs
- 2.4 Ontology-Based Data Access and Integration
- 3 Canonical IRI Semantics
- 4 Handling Canonical IRI Semantics by Query Rewriting
- 5 Handling Canonical IRI Statements in OBDA
- 6 Implementation and Experiments
- 6.1 Real-World Experiments
- 6.2 Controlled Experiments Using Wisconsin Benchmark
- 7 Conclusions
- References
- Formal Query Generation for Question Answering over Knowledge Bases
- 1 Introduction
- 2 Related Work
- 3 Approach
- 3.1 Query Generation
- 3.2 Query Ranking
- 4 Empirical Study
- 4.1 Datasets
- 4.2 Performance Evaluation
- 5 Conclusions and Future Works
- References
- A LOD Backend Infrastructure for Scientific Search Portals
- 1 Introduction
- 2 Use Case
- 3 Linked Open Data Backend Infrastructure
- 3.1 Architecture
- 3.2 Data Sources
- 3.3 Data Format
- 3.4 Link Detection
- 3.5 Entity Disambiguation and Link Merging
- 3.6 Research Data Ontology
- 3.7 Link Database
- 3.8 Elasticsearch Index
- 4 Evaluation
- 5 Related Work
- 6 Conclusion and Outlook
- References
- Detecting Hate Speech on Twitter Using a Convolution-GRU Based Deep Neural Network
- 1 Introduction
- 2 Related Work
- 2.1 Terminology
- 2.2 State of the Art
- 2.3 Datasets
- 3 Methodology
- 3.1 Pre-processing
- 3.2 The CNN+GRU Architecture
- 4 Dataset Creation
- 5 Experiment
- 5.1 Datasets
- 5.2 Baseline and Comparative Models
- 5.3 Implementation, Parameter Tuning, and Evaluation Metrics
- 5.4 Results and Discussion
- 5.5 Error Analysis
- 6 Conclusion and Future Work
- References
- Author Index
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