Intro
Preface
Organization
Contents
A Chemical Domain Knowledge-Aware Framework for Multi-view Molecular Property Prediction
1 Introduction
2 Related Work
2.1 Supervised MRL
2.2 Self-supervised MRL
2.3 Domain Knowledge Based MRL
3 Our Approach
3.1 KPGT
3.2 Functional Group Embedding
3.3 Knowledge Graph Embedding
4 Experiments
4.1 Dataset
4.2 Parameter Settings
4.3 Results
4.4 Discussion
5 Conclusion
References
A Coarse Pipeline to Solve Hierarchical Multi-answer Questions with Conditions
1 Introduction
2 Method

2.1 Answer Span Detection
2.2 Relation Classification
2.3 Additional Strategies
3 Experiments
3.1 Data Processing
3.2 Experiments of Answer Span Detection
3.3 Experiments of Relation Classification
3.4 Online Result
4 Discussion
4.1 First Attempt
4.2 Second Attempt
4.3 Third Attempt
4.4 Fourth Attempt
4.5 Future Work
References
A Pipeline-Based Multimodal Military Event Argument Extraction Framework
1 Introduction
2 Method
2.1 Global Pointer Model for Named Entity Recognition
2.2 Yolo Model for Object Detection
2.3 Multimodal Matcher

3 Experiment
3.1 Dataset
3.2 Implementation
3.3 Main Result
4 Conclusion
References
A Search-Enhanced Path Mining and Ranking Method for Cross-lingual Knowledge Base Question Answering
1 Introduction
2 Task Description
3 Method
3.1 Question Classification
3.2 Principal Entity Extraction
3.3 Search-Enhanced Candidate Path Mining
3.4 Path Ranking
4 Experiment Result
4.1 Question Classification
4.2 Principal Entity Extraction
4.3 Search-Enhanced Candidate Path Mining
4.4 Path Ranking
4.5 End-To-End Evaluation Result
5 Conclusion

2.4 Condition-Answer Relation Classification
2.5 Post-classification Processing
3 Experiment
3.1 Model Effect Evaluation
3.2 End-To-End Effect Evaluation
4 Conclusion
References
Compound Property Prediction Based on Multiple Different Molecular Features and Ensemble Learning
1 Introduction
2 Related Work
2.1 Molecular Descriptor
2.2 SMILES
2.3 Molecular Graph Representation
3 Method
3.1 Molecular Vector Representation
3.2 AutoEncoder Model
3.3 Ensemble Model
4 Experiment
4.1 Data Introduction
4.2 Experimental Setup