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" Knowledge graph and semantic computing : "
Jun Zhao, Frank van Harmelen, Jie Tang, Xianpei Han, Quan Wang, Xianyong Li (eds.).
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BL
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| Record Number
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891431
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| Main Entry
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CCKS (Conference)(3rd :2018 :, Tianjin, China)
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| Title & Author
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Knowledge graph and semantic computing : : knowledge computing and language understanding : third China Conference, CCKS 2018, Tianjin, China, August 14-17, 2018, Revised selected papers /\ Jun Zhao, Frank van Harmelen, Jie Tang, Xianpei Han, Quan Wang, Xianyong Li (eds.).
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| Publication Statement
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Singapore :: Springer,, 2019.
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| Series Statement
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Communications in computer and information science,; 957
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| Page. NO
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1 online resource (xvi, 143 pages) :: illustrations (some color)
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| ISBN
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9789811331466
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: 9789811331473
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: 9811331464
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: 9811331472
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9789811331459
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9811331456
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| Notes
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Includes author index.
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| Contents
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Intro; Preface; Organization; Contents; Towards Answering Geography Questions in Gaokao: A Hybrid Approach; 1 Introduction; 2 Challenges and Related Work; 3 Overview of the Approach; 4 Detailed Implementation; 4.1 Question Parsing; 4.2 Knowledge Graph Construction; 4.3 Semantic Matching; 4.4 Spreading Activation and Answer Generation; 5 Evaluation; 5.1 Evaluation of the Entire Approach; 5.2 Evaluation of Components; 6 Future Directions; References; Distant Supervision for Chinese Temporal Tagging; Abstract; 1 Introduction; 2 Related Works; 3 Methodology; 3.1 Task Description
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3 Problem Formulation and Model Overview3.1 Problem Formulation; 3.2 Overview of STBNet; 4 Method; 4.1 Semantic Embedding; 4.2 Text Embedding for Ontology Stream; 4.3 Semantic Prediction; 5 Experiments; 5.1 Dataset and Setup; 5.2 Training and Evaluation; 5.3 Experiment Results; 6 Conclusion and Future Work; References; DSKG: A Deep Sequential Model for Knowledge Graph Completion; 1 Introduction; 2 Related Work; 2.1 TransE-Like Models; 2.2 Other Models; 3 Methodology; 3.1 RNN and Its Multi-layer Version; 3.2 The Proposed Deep Sequential Model; 3.3 Type-Based Sampling
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3.2 Train Set Construction3.3 Sequence Labeling Model; 4 Experiments and Analysis; 4.1 Model Settings; 4.2 Experiment Grouping; 4.3 Results and Analysis; 5 Conclusion and Future Work; References; Convolutional Neural Network-Based Question Answering Over Knowledge Base with Type Constraint; Abstract; 1 Introduction; 2 Related Work; 3 Approach; 3.1 Model Description; 3.2 Training; 4 Experiments; 4.1 Data and Evaluation Metric; 4.2 Experimental Settings; 4.3 Results; 4.4 Error Analysis; 5 Conclusion; Acknowledgements; References
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3.4 Enhancing Entity Prediction with Relation Prediction4 Experiments; 4.1 Datasets and Experiment Settings; 4.2 Entity Prediction; 4.3 Triple Prediction; 5 Analysis; 5.1 Comparison with Alternative Models; 5.2 Influence of Layer Number; 5.3 Influence of Embedding Size; 6 Conclusion and Future Work; References; Pattern Learning for Chinese Open Information Extraction; 1 Introduction; 2 Related Work; 3 Issues and Solutions; 3.1 Trans-Classed Word; 3.2 Light Verb Construction; 4 PLCOIE System; 4.1 Pattern Learning; 4.2 Relation Candidates Extraction; 4.3 Computing the Confidence
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MMCRD: An Effective Algorithm for Deploying Monitoring Point on Social Network1 Introduction; 2 Related Work; 3 Problem Formulation; 3.1 Deploy Monitoring Points on Social Network; 3.2 Set Cover Problem Formulation; 4 MMCRD for Monitoring Point Deployment; 5 Experiment and Evaluation; 5.1 Dataset Description; 5.2 Experiments; 6 Conclusion and Future Work; References; Deep Learning for Knowledge-Driven Ontology Stream Prediction; 1 Introduction; 2 Related Work; 2.1 Ontology Stream Learning Problems; 2.2 Text Stream Learning; 2.3 Time Series Forecasting Models
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| Abstract
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This book constitutes the refereed proceedings of the Third China Conference on Knowledge Graph and Semantic Computing, CCKS 2018, held in Tianjin, China, in August 2018. The 27 revised full papers and 2 revised short papers presented were carefully reviewed and selected from 101 submissions. The papers cover wide research fields including the knowledge graph, information extraction, knowledge representation and reasoning, linked data.
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| Subject
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Big data, Congresses.
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Knowledge representation (Information theory), Congresses.
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Semantic computing, Congresses.
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Big data.
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Knowledge representation (Information theory)
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Semantic computing.
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| Dewey Classification
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006
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| LC Classification
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QA76.5913
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| Added Entry
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Han, Xianpei
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Li, Xianyong
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Tang, Jie, (Computer scientist)
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Van Harmelen, Frank
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Wang, Quan
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Zhao, Jun, (College teacher)
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| Parallel Title
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CCKS 2018
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