Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence

Name: Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence | Second China Conference, CCKS 2017, Chengdu, China, August 26-29, 2017, Revised Selected Papers
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Second China Conference, CCKS 2017, Chengdu, China, August 26-29, 2017, Revised Selected Papers

Juanzi Li Ming Zhou Guilin Qi Ni Lao Tong Ruan Jianfeng Du(Editor)

Springer (Publisher)

Published on 18. January 2018

XIV, 173 pages

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978-981-10-7359-5 (ISBN)

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Content

Intro
Preface
Organization
Contents
Knowledge Base Completion by Learning to Rank Model
1 Introduction
2 Learning to Rank Model
3 Experiments
4 Related Work
5 Conclusion
References
Path-Based Learning for Plant Domain Knowledge Graph
Abstract
1 Introduction
2 Approach
2.1 TransE Model
2.2 PTA Model
2.3 PTA (Path-Based TransE for Attributes)
2.4 Model Formulation
3 Experiments
3.1 Setup
3.2 Evaluation
4 Conclusion
References
A Graph-Based Approach to Incremental Classification in OWL 2 QL Ontology
1 Introduction
2 Preliminaries
2.1 OWL 2 QL
2.2 Graph Theory Notions
2.3 Digraph Representation of OWL QL 2 Ontologies
3 Mapping Ontologies Direct Graphs
4 Identifying Affected Paths and Updating Transitive Closure
5 Optimization
6 Implementation and Evaluation
7 Discussions
References
Tensor-Based Representation and Reasoning of Horn-SHOIQ Ontologies
1 Introduction
2 Ontology and Tensor Operations
3 A Tensor-Based Representation for Ontologies
4 Materialization via Tensor Operations
5 Conclusions and Future Work
References
Attention-Based Event Relevance Model for Stock Price Movement Prediction
1 Introduction
2 Related Works
3 Methodology
3.1 Problem Formulation
3.2 Attention-Based Event Relevance Model
3.3 Model Training
4 Experiments and Results
4.1 Dataset Construction
4.2 Implementation and Hyper-Parameter Setting
4.3 Stock Price Movement Prediction Experiments
4.4 Short-Term, Medium-Term, Long-Term Influence
5 Conclusion and Future Work
References
A Survey on Relation Extraction
Abstract
1 Introduction
2 Datasets for Relation Extraction
3 Mainstream Methods
3.1 Rule-Based Approaches
3.2 Statistic-Based Approaches
4 Open Information Extraction (OIE)
5 Challenges and Directions
6 Conclusion
Acknowledgment
References
A Sentiment and Topic Model with Timeslice, User and Hashtag for Posts on Social Media
1 Introduction
2 Sentiment Topic Model for Posts
3 Experiment
3.1 Dataset Description and Parameter Settings
3.2 Topic Coherence
3.3 Topic Visualization
4 Conclusion and Future Work
References
Collective Entity Linking Based on DBpedia
Abstract
1 Introduction
2 Relate Work
3 Preliminary
4 Method Description
4.1 Candidate Entity Generation
4.2 Candidate Entity Selection
5 Evaluation
5.1 Dataset Description
5.2 Evaluation Criteria
5.3 Experimental Results
6 Conclusion and Future Work
Acknowledgements
References
A CWTM Model of Topic Extraction for Short Text
Abstract
1 Introduction
2 Related Work
3 A Novel Topic Modeling
3.1 Couple Word
3.2 Our Approach
4 Experiments and Results
5 Conclusions and Future Work
References
Micro-blog User Community Detection by Focusing on Micro-blog Content and Community Structure
1 Introduction
2 Related Work
3 Establish the Micro-blog Network
4 Detect the Objects' Clustering Directions
5 Detect Community
6 Experiments
6.1 Evaluate by the Interest Cohesion
6.2 Evaluate by the Community Structure
7 Conclusion and Future Work
References
Embedding Syntactic Tree Structures into CNN Architecture for Relation Classification
Abstract
1 Introduction
2 Related Work
3 Our Method
3.1 Feature Extraction
3.1.1 Syntactic Parsing Tree Embedding Features
3.1.2 Lexical Level Features
3.1.3 Entities Parsing Tree Embedding Features
3.2 Convolution Operation
3.3 Max-pooling Operation
3.4 Linear Transformation
3.5 Output
3.6 Dropout Operation
3.7 Training Procedure
4 Experiments
5 Conclusions
Acknowledgements
References
Tracking Topic Trends for Short Texts
1 Introduction
2 Related Work
3 Topic Trend Detection (TTD) Model
3.1 Pre-process Stage
3.2 An Optimized Topic Model
3.3 Auxiliary Word Embeddings
4 Experiments
4.1 Datasets
4.2 Experimental Setup
4.3 Evaluation by Topic Coherence
4.4 Trend Detection in Microblog
5 Conclusion and Future Work
References
BSBM+: Extending BSBM to Evaluate Annotated RDF Features on Graph Databases
1 Introduction
2 Related Work
2.1 Annotated RDF
2.2 Benchmarks
2.3 Temporal and Geospatial Operators
3 Data Model
3.1 Annotation
3.2 Annotated RDF
3.3 Extended SPARQL and Extended Graph Engines
4 Benchmark Workflow
5 Dataset
5.1 Distribution of Annotation Type and Annotation Number
5.2 Distribution of the Annotation Values
6 Experiment
6.1 Metrics
6.2 Graph Engines Chosen and Experiment Circumstance
6.3 Engine Extension Module
6.4 SPARQL Extension Module
7 Results
7.1 Engine Extension Module
7.2 SPARQL Extension Module
8 Conclusion and Future Work
References
Detecting Spammers in Sina Micro-blog Based on Multiple Features
Abstract
1 Introduction
2 Related Work
3 Advertising Spammers Detecting Model
3.1 Basic Definitions
3.2 Similarity Detection
4 Experiment and Analysis on Dataset
4.1 Dataset and Preprocessing
4.2 Evaluation Criterion
5 Conclusions and Future Work
References
A Hybrid Method to Sentiment Analysis for Chinese Microblog
1 Introduction
2 Related Work
2.1 Lexicon-Based
2.2 Machine Leaning Method
3 A Hybrid Method to the Sentiment Analysis for Chinese Microblog (SAFCM)
3.1 Construction of Sentiment Lexicon
3.2 Word Embedding
3.3 Clustering
4 Experiments
4.1 Data Sets
4.2 Experiment Results
5 Conclusion and Future Work
References
A User Personality-Similarity Model for Personalized Followee Recommendation in SINA Microblog
1 Introduction
2 Related Work
3 Our Method
3.1 User-Based Factor
3.2 Personality-Based Factors
4 Experiment
4.1 Results
5 Conclusions
References
CrowdGeoKG: Crowdsourced Geo-Knowledge Graph
1 Introduction
2 Technical Framework
2.1 Schema Design
2.2 Data Transformation and Linking
3 Dataset Exploitation
4 Conclusion and Future Work
References
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Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence

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