
Information Retrieval
Description
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The 8 full papers presented were carefully reviewed and selected from numerous submissions. The papers provide a wide range of research results in information retrieval area.
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Content
- Intro
- Preface
- Organization
- Contents
- A Position-Aware Word-Level and Clause-Level Attention Network for Emotion Cause Recognition
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 3.1 The Definition of Emotion Cause Recognition
- 3.2 Position-Aware Word-Level and Clause-Level Attention Network for Emotion Cause Recognition
- 3.3 Model Training
- 4 Experiment
- 4.1 Experimental Settings
- 4.2 Experimental Results
- 4.3 Qualitative Analysis
- 5 Conclusion and Future Work
- References
- ID-Agnostic User Behavior Pre-training for Sequential Recommendation
- 1 Introduction
- 2 Preliminaries
- 3 Methodology
- 3.1 ID-Agnostic User Behavior Pre-training
- 3.2 Fine-Tuning for Recommendation
- 4 Experiments
- 4.1 Experimental Setup
- 4.2 Experimental Results
- 5 Related Work
- 6 Conclusion
- References
- Enhance Performance of Ad-hoc Search via Prompt Learning
- 1 Introduction
- 2 Related Work
- 2.1 Ad Hoc Search with PTM
- 2.2 Prompt Learning
- 3 Preliminary
- 3.1 Ad hoc Search
- 3.2 Prompt Learning
- 4 Methodology
- 5 Experiments
- 5.1 Dataset and Metric
- 5.2 Experimental Setup
- 5.3 Result and Analysis
- 5.4 Case Study
- 6 Conclusion
- References
- Syntax-Aware Transformer for Sentence Classification
- 1 Introduction
- 2 Syntax-Aware Transformer
- 2.1 Syntactic Subnetwork
- 2.2 Semantic Subnetwork
- 2.3 Merging Layer
- 3 Experiments
- 3.1 Datasets
- 3.2 Experimental Settings
- 3.3 Baseline Models
- 3.4 Results and Discussion
- 3.5 Case Study
- 4 Conclusions
- References
- Evaluation of Deep Reinforcement Learning Based Stock Trading
- 1 Introduction
- 2 Related Works
- 3 RL Modeling of Stock Trading
- 3.1 Problem Description
- 3.2 Mathematical Presentation
- 3.3 Trading Details
- 3.4 Feasibility Analysis of RL-Based Stock Trading
- 4 Experiments
- 4.1 Stock Dataset
- 4.2 Methodology
- 4.3 Results
- 5 Conclusion and Future Works
- References
- InDNI: An Infection Time Independent Method for Diffusion Network Inference
- 1 Introduction
- 2 Related Work
- 3 Problem Statement
- 4 InDNI Algorithm
- 4.1 Node Representation Learning
- 4.2 Similarity Measure
- 4.3 Filtering Candidate Node Pairs
- 4.4 Network Inference
- 5 Experiments
- 5.1 Experimental Setup
- 5.2 Results and Discussion
- 6 Conclusion and Future Work
- References
- Beyond Precision: A Study on Recall of Initial Retrieval with Neural Representations
- 1 Introduction
- 2 Related Work
- 2.1 Initial Retrieval
- 2.2 Neural Representations for IR
- 3 Our Approach
- 3.1 Symbolic Index
- 3.2 Neural Index
- 3.3 Parallel Search Scheme
- 3.4 Sequential Search Scheme
- 3.5 Discussions
- 4 Experiments
- 4.1 Baselines and Experimental Settings
- 4.2 Evaluation Methodology
- 4.3 Retrieval Performance and Analysis
- 4.4 Analysis on Retrieved Relevant Documents
- 5 Conclusions
- References
- A Learnable Graph Convolutional Neural Network Model for Relation Extraction
- 1 Introduction
- 2 Related Work
- 3 Model
- 3.1 Input Representation Layer
- 3.2 Fusion Module
- 3.3 Classification Module
- 4 Experiments
- 4.1 Datasets
- 4.2 Hyper-parameter Setting
- 4.3 Overall Performance
- 4.4 Ablation Study
- 4.5 Effect of Length of Each Part
- 5 Conclusion and Future Work
- References
- Author Index
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