Chinese Computational Linguistics : 18th China National Conference, CCL 2019, Kunming, China, October 18-20, 2019, Proceedings /: 18th China National Conference, CCL 2019, Kunming, China, October 18-20, 2019, Proceedings. (2019)
- Record Type:
- Book
- Title:
- Chinese Computational Linguistics : 18th China National Conference, CCL 2019, Kunming, China, October 18-20, 2019, Proceedings /: 18th China National Conference, CCL 2019, Kunming, China, October 18-20, 2019, Proceedings. (2019)
- Main Title:
- Chinese Computational Linguistics : 18th China National Conference, CCL 2019, Kunming, China, October 18-20, 2019, Proceedings
- Other Titles:
- CCL 2019
- Further Information:
- Note: Maosong Sun, Xuanjing Huang, Heng Ji, Zhiyuan Liu, Yang Liu (eds.).
- Other Names:
- Sun, Maosong
Huang, Xuanjing
Ji, Heng
Liu, Zhiyuan
Liu, Yang
CCL (Conference), 18th - Contents:
- Intro; Preface; Organization; Contents; Linguistics and Cognitive Science; Colligational Patterns in China English: The Case of the Verbs of Communication; Abstract; 1 Introduction; 2 Literature Review; 3 Methods; 3.1 Source of the Data; 3.2 Procedures; 4 Results; 4.1 Number of Occurrences of the Three Verbs; 4.2 Colligational Patterns of Discuss; 4.3 Colligational Patterns of Communicate; 4.4 Colligational Patterns of Negotiate; 5 Discussion; 6 Conclusion; Acknowledgements; References; Testing the Reasoning Power for NLI Models with Annotated Multi-perspective Entailment Dataset 1 Introduction2 Related Works; 3 Categories; 3.1 Lexical and Phrasal Level (LP); 3.2 Syntactic Structure (SS); 3.3 Commonsense Reasoning (CR); 4 Data Annotations; 4.1 Data Selection; 4.2 Multi-perspective Entailment Category Labeling System; 4.3 Data Collection; 4.4 Data Annotation Results; 5 Experiments; 5.1 Experimental Setup; 5.2 Results and Analysis; 6 Conclusion; References; Enhancing Chinese Word Embeddings from Relevant Derivative Meanings of Main-Components in Characters; 1 Introduction; 2 Main-Component Word Embedding Models; 2.1 MCWE-SA; 2.2 MCWE-HA 2.3 Update Rules for Relevant Derivative Meanings3 Experiments and Analysis; 3.1 Experimental Settings; 3.2 Word Similarity; 3.3 Syntactic Analogy; 3.4 The Impacts of Corpus Size; 4 Conclusion; References; Association Relationship Analyses of Stylistic Syntactic Structures; 1 Introduction; 2 Algorithms; 2.1 Pearson Correlation Coefficient; 2.2Intro; Preface; Organization; Contents; Linguistics and Cognitive Science; Colligational Patterns in China English: The Case of the Verbs of Communication; Abstract; 1 Introduction; 2 Literature Review; 3 Methods; 3.1 Source of the Data; 3.2 Procedures; 4 Results; 4.1 Number of Occurrences of the Three Verbs; 4.2 Colligational Patterns of Discuss; 4.3 Colligational Patterns of Communicate; 4.4 Colligational Patterns of Negotiate; 5 Discussion; 6 Conclusion; Acknowledgements; References; Testing the Reasoning Power for NLI Models with Annotated Multi-perspective Entailment Dataset 1 Introduction2 Related Works; 3 Categories; 3.1 Lexical and Phrasal Level (LP); 3.2 Syntactic Structure (SS); 3.3 Commonsense Reasoning (CR); 4 Data Annotations; 4.1 Data Selection; 4.2 Multi-perspective Entailment Category Labeling System; 4.3 Data Collection; 4.4 Data Annotation Results; 5 Experiments; 5.1 Experimental Setup; 5.2 Results and Analysis; 6 Conclusion; References; Enhancing Chinese Word Embeddings from Relevant Derivative Meanings of Main-Components in Characters; 1 Introduction; 2 Main-Component Word Embedding Models; 2.1 MCWE-SA; 2.2 MCWE-HA 2.3 Update Rules for Relevant Derivative Meanings3 Experiments and Analysis; 3.1 Experimental Settings; 3.2 Word Similarity; 3.3 Syntactic Analogy; 3.4 The Impacts of Corpus Size; 4 Conclusion; References; Association Relationship Analyses of Stylistic Syntactic Structures; 1 Introduction; 2 Algorithms; 2.1 Pearson Correlation Coefficient; 2.2 Hierarchical Cluster; 2.3 LassoCV Algorithm; 2.4 Relative Definition; 3 Dataset and Statistic Information; 3.1 Datasets; 3.2 Syntactic Structures; 4 Association Relationship Mining; 4.1 Parts of Speech (POS) Collocation Mining 4.2 Positive and Negative Correlation Mining4.3 Linear and Nonlinear Correlation Mining; 5 Linguistic Relevance Analyses; 6 Conclusion; References; Fundamental Theory and Methods of Computational Linguistics; Adversarial Domain Adaptation for Chinese Semantic Dependency Graph Parsing; 1 Introduction; 2 Related Work; 2.1 Semantic Dependency Graph Parsing; 2.2 Domain Adaptation; 3 Method; 3.1 Deep Biaffine Network for Single Domain CSGD Parsing; 3.2 Cross-Domain CSDG Parsing Method; 3.3 Jointly Training; 4 CCSD Dataset; 4.1 Corpus Collection; 4.2 Dataset Construction and Statistics 5 Experiments5.1 Setup; 5.2 Overall Results; 6 Conclusions; References; Information Retrieval and Question Answering; Encoder-Decoder Network with Cross-Match Mechanism for Answer Selection; Abstract; 1 Introduction; 2 Related Work; 3 Model; 3.1 Cross-Match Mechanism; 3.2 Encoder Layer; 3.3 Decoder Layer; 4 Experimental Setup; 4.1 Datasets and Evaluation Metric; 4.2 Implementation Details; 4.3 Experimental Results; 4.4 Ablation Analysis; 5 Conclusion; Acknowledgements; References; BB-KBQA: BERT-Based Knowledge Base Question Answering; 1 Introduction; 2 BB-KBQA Model; 2.1 Models; 2.2 Modules … (more)
- Publisher Details:
- Cham : Springer
- Publication Date:
- 2019
- Extent:
- 1 online resource (719 pages)
- Subjects:
- 006.3/5
Chinese language -- Data processing -- Congresses
Natural language processing (Computer science) -- Congresses
Computational linguistics -- Congresses
Big data -- Congresses
Big data
Chinese language -- Data processing
Computational linguistics
Natural language processing (Computer science)
Electronic books
Conference papers and proceedings - Languages:
- English
- ISBNs:
- 9783030323813
3030323811 - Related ISBNs:
- 9783030323806
- Notes:
- Note: Print version record.
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