Semantic Technology

Name: Semantic Technology | 7th Joint International Conference, JIST 2017, Gold Coast, QLD, Australia, November 10-12, 2017, Proceedings
Brand: Springer
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7th Joint International Conference, JIST 2017, Gold Coast, QLD, Australia, November 10-12, 2017, Proceedings

Zhe Wang Anni-Yasmin Turhan Kewen Wang Xiaowang Zhang(Herausgeber*in)

Springer (Verlag)

Erschienen am 6. November 2017

XIII, 352 Seiten

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978-3-319-70682-5 (ISBN)

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Inhalt

Intro
Preface
Organization
Contents
Ontology and Data Management
Building Wikipedia Ontology with More Semi-structured Information Resources
1 Introduction
2 Related Work
3 English Wikipedia Ontology Building Method
3.1 Is-a Relation Extraction Method
3.2 Class-Instance Relation Extraction Method
3.3 Triple Extraction Method
3.4 Upper-Lower Relation Extraction Method from Define Statements
4 Evaluation of Built Ontology
4.1 Result of Is-a Relation Extraction
4.2 Result of Class-Instance Relation Extraction
4.3 Result of Triple Extraction
4.4 Result of Upper-Lower Relation Extraction from Define Statements
5 Evaluation by Comparison with Existing Ontology
5.1 Comparison with YAGO
5.2 Comparison with DBpedia Ontology
6 Conclusion
References
Data Structuring for Launching Web Services Triggered by Media Content
Abstract
1 Introduction
2 Issues
3 Related Work
4 Data Model
4.1 Analysis of Actual Service Categories and Genres
4.2 Overview About Data Model
4.3 Structuring Data
4.3.1 Data Structure for Content
4.3.2 Data Structure for Service Description
4.4 Inference-Based Matching/Query Generation Processing
4.4.1 Processing Matches for Content and Services
4.4.2 Processing Query Generation for Launching Services
5 Discussion
5.1 Service Linking When Watching Broadcast Content
5.2 Added Service Linkage to Existing IFTTT Service
6 Summary
References
Refined JST Thesaurus Extended with Data from Other Open Life Science Data Sources
Abstract
1 Introduction
2 Related Work
3 Update of Refined JST Thesaurus
4 Evaluation of the Refined JST Thesaurus
4.1 Method
4.2 Results
5 Conclusions
Acknowledgment
References
Refinement-Based OWL Class Induction with Convex Measures
1 Introduction
1.1 Preliminaries
2 Beam Search for Concepts
3 Utility and Quality Functions in Beam Search
4 A Top-k Beam Search for Supervised Concept Learning
5 Experimental Evaluation
6 Related Work
7 Conclusion
References
Ontology Reasoning
Reasoning on Context-Dependent Domain Models
1 Introduction
2 Basic Notions
3 Reasoning on Role-Based Models
4 JConHT - a SHOIQ[[SHOIQ]] Reasoner
5 Case Studies
6 Related Work
7 Conclusion
References
Energy-Efficiency of OWL Reasoners---Frequency Matters
1 Introduction
2 Experimental Setup
2.1 Experimental Data and Systems
2.2 Setup of the Experiments
3 Observations
3.1 Running Times
3.2 Energy and Power Consumption
3.3 Impact of the CPU Frequency
4 Conclusion
References
The Identity Problem in Description Logic Ontologies and Its Application to View-Based Information Hiding
1 Introduction
2 The Identity Problem
3 Three DLs with Equality Power
4 The Complexity of the Identity Problem
5 The View-Based Identity Problem
6 Conclusions and Future Work
References
Linked Data and Query
Resolving Range Violations in DBpedia
1 Introduction
2 Range Violation Errors in DBpedia
3 Related Work
4 Our Approach
4.1 Constructing a Reduced Search Space
4.2 Calculating Scores
5 Experiments
5.1 Datasets
5.2 Experiment 1: Evaluating the Search Space
5.3 Experiment 2: Evaluating the Whole Approach
6 Conclusion
References
Entity Linking in Queries Using Word, Mention and Entity Joint Embedding
1 Introduction
2 Word, Mention and Entity Joint Embedding
2.1 The Skip-Gram Model
2.2 Joint Embedding by Skip-Gram Model
2.3 Using Wikipedia as Training Corpus
3 Query Entity Linking Approach
3.1 Identifying Mentions and Its Candidate Entities
3.2 Features for Entity Disambiguation
3.3 Entity Linking as Ranking
4 Evaluation
4.1 Dataset
4.2 Comparison Systems
4.3 Evaluation Results
5 Related Work
5.1 Entity Embedding
5.2 Entity Linking
6 Conclusion
References
Publishing E-RDF Linked Data for Many Agents by Single Third-Party Server
Abstract
1 Introduction
2 Related Works
3 Systematic URI Standard of Third-Party Server
3.1 URI Definition Standard
3.2 Graph: Multiple Agents Management
3.3 Ontology: Concept and Property
3.4 Resource: Instance or Individual
4 E-RDF: An Extension Notion of RDF
5 Confidential Data Protection
6 Prototype System
7 Interlinking and 5-Star Data Improvement
8 Conclusion
Acknowledgments
References
Missing RDF Triples Detection and Correction in Knowledge Graphs
1 Introduction
2 Related Work
3 Knowledge Graph Analysis for Discovering RDF Triples
3.1 Graph-Based Approach for Object Property Triples
3.2 Word Embedding Based Approach for Datatype Property Triples
4 Experiment
4.1 Knowledge Graphs
4.2 Implementation
4.3 Exp 1: Discover Similar Object Properties
4.4 Exp 2: Discover Object Property Triples
4.5 Exp 3: Discover Similar Datatype Properties
4.6 Exp 4: Discover Datatype Property Triples
5 Conclusion and Future Work
References
Information Retrieval and Knowledge Discovery
A New Sentiment and Topic Model for Short Texts on Social Media
1 Introduction
2 Related Work
2.1 Topic Models on Short Texts
2.2 Joint Sentiment/Topic Models
3 The Proposed Work
3.1 Brief Review of TUS-LDA
3.2 Sentiment Topic Model for Posts
3.3 Parameters Inference for STMP
3.4 Incorporating Prior Knowledge
4 Experiment
4.1 Dataset Description
4.2 Sentiment Lexicon
4.3 Parameter Settings
4.4 Sentiment Classification
4.5 Qualitative Analysis
5 Conclusion and Future Work
References
Semi-supervised Stance-Topic Model for Stance Classification on Social Media
1 Introduction
2 Related Work
2.1 Supervised Stance Classification
2.2 Weakly-supervised or Semi-supervised Stance Classification
3 Our Proposed Model
3.1 Generative Process
3.2 Setting x with a Maximum Entropy Model
3.3 Inference
4 Experiment Analysis
4.1 Dataset Description
4.2 Parameter Settings
4.3 Stance Classification
4.4 Case Analysis for Stance Detection
4.5 Visualization of Stance-Related Topics
5 Conclusion and Future Work
References
Mining Inverse and Symmetric Axioms in Linked Data
1 Introduction
1.1 Challenges and Contributions
2 Related Work
2.1 Limitations of Existing Work
3 Preliminaries
3.1 Property Axioms
3.2 Mining Logical Rules Under OWA
4 Proposed Method
4.1 Rules of Interest
4.2 Ordering Rules
4.3 Clustering
4.4 Axiom Generation
5 Experimental Results
5.1 Datasets
5.2 Comparison with Naive Baselines
5.3 Quantitative Performance
5.4 Qualitative Performance
6 Conclusion
References
Enhancing Knowledge Graph Embedding from a Logical Perspective
1 Introduction
2 Preliminaries
2.1 OWL 2 RBox and Knowledge Graph
2.2 Translation-Based Methods in Knowledge Graph Embedding
3 Enhancements for Translation-Based Methods
4 Experiments
4.1 Data Sets
4.2 Link Prediction
4.3 Triple Classification
5 Related Work
6 Conclusions and Future Work
References
Knowledge Graphs
Cross-Lingual Taxonomy Alignment with Bilingual Knowledge Graph Embeddings
1 Introduction
2 The Proposed Approach
2.1 Candidates Identification
2.2 Acquiring Relevant Triples
2.3 Learning Vector Representations
2.4 Exact Matching
3 Preliminary Experiments
3.1 Experiment Settings
3.2 Preliminary Results
3.3 Combining BTransE with BiBTM
4 Conclusion and Future Work
References
KG-Buddhism: The Chinese Knowledge Graph on Buddhism
1 Introduction
2 Development Method
2.1 Knowledge Collection
2.2 Knowledge Fusion
2.3 Knowledge Completion
2.4 Linking to DBpedia
3 Dataset Statistics
4 Online API
5 Conclusions and Future Work
References
Semantic Graph Analysis for Federated LOD Surfing in Life Sciences
1 Introduction
2 LOD Surfer
2.1 SPARQL Builder Metadata
2.2 Merged Class Graph for LOD
3 Graph Analysis for Merged Class Graph
3.1 Cut Classes for Federated Search
4 Discussion
5 Conclusion
References
Development of Semantic Web-Based Imaging Database for Biological Morphome
1 Introduction
2 Methods
2.1 Extension of Microscopy Ontology for Morphomics Data
2.2 Microstructural Bioimaging and Image Processing
2.3 Development of Electron Microscopy Viewer and the Annotation of Phenotype Data
2.4 Construction of Metadatabase for Microstructural Imaging Data of Biotissue
3 Results and Discussion
3.1 Vocabulary Extension for Experimental Description and Morphome Data Description
3.2 Imaging Metadatabase and Comprehensive Morphome Analysis on the Semantic Web
4 Conclusions
References
Applications of Semantic Technologies
User Participatory Construction of Open Hazard Data for Preventing Bicycle Accidents
1 Introduction
2 Related Works
2.1 Environmental Sensing Methods
2.2 Behavior Recognition Methods
2.3 User Participation Methods
3 Detection System of Sudden Braking
3.1 Sensing User Data
3.2 Sudden Braking Recognition
4 Experiment Results on Sudden Braking Detection
4.1 Preliminary Experiment
4.2 Actual Experiment on Public Streets
5 RDF Construction
6 Conclusion and Future Work
References
Semantic IoT: Intelligent Water Management for Efficient Urban Outdoor Water Conservation
Abstract
1 Introduction
2 Background
2.1 Current Watering Paradigms
2.2 Factors that Influence Required Water Volume
2.3 Resident Specific Information
2.4 Related Work
3 Semantic Knowledge Base and Control Agent
4 Hardware Implementation
5 Implementation and Discussion
6 Conclusions
Appendix A
References
Semantically Enhanced Case Adaptation for Dietary Menu Recommendation of Diabetic Patients
Abstract
1 Introduction
2 Related Work
3 The Proposed Approach
3.1 Ontology Modeling
3.2 Case-Based Modeling
3.3 CBR Engine
3.4 Ontology Reasoning
3.4.1 MET Fulfillment
3.4.2 Inserting New Component
4 Discussion and Conclusion
Acknowledgement
References
Linked Urban Open Data Including Social Problems' Causality and Their Costs
1 Introduction
2 Related Work
2.1 Knowledge Graph for Solving Social Issues
2.2 Knowledge Graph for Analyzing City Indicators
2.3 Crowdsourcing and NLP for Linked Data
3 Designing a Schema of Problem Causality and Costs
4 Building LOD Based on Designed Schema
4.1 Extraction of Urban Problem Causality
4.2 Filtering Causality Words Using Crowdsourcing
4.3 Building LOD Based on the Extracted Causality Words
4.4 Building LOD Based on Budget Data of Local Government
4.5 Evaluation and Discussion
5 Use Cases for Considering Urban Problem Solutions
5.1 Querying the Causality of Homeless people
5.2 Querying the Causality of Littering
5.3 Querying the Causality of Suburbanization
6 Conclusion and Future Work
References
Erratum to: Refinement-Based OWL Class Induction with Convex Measures
Erratum to: Chapter "Refinement-Based OWL Class Induction with Convex Measures" in: Z. Wang et al. (Eds.): Semantic Technology, LNCS 10675, https://doi.org/10.1007/978-3-319-70682-5_4
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