Advances in Information Retrieval: 45th European Conference on Information Retrieval, ECIR 2023, Dublin, Ireland, April 2–6, 2023, Proceedings, Part I

Preface
Organization
Keynotes
	Personalization at Spotify
	On A Few Responsibilities of (IR) Researchers: Fairness, Awareness, and Sustainability
	2022 Karen Spärck Jones Award Lecture Large Language Models for Question Answering: Challenges and Opportunities
	Contents – Part I
	Contents – Part II
	Contents – Part III
Full Papers
Self-supervised Contrastive BERT Fine-tuning for Fusion-Based Reviewed-Item Retrieval
	1 Introduction
	2 Background
		2.1 IR
		2.2 Fusion
		2.3 Contrastive Representation Learning
	3 Proposed Fusion-based Methods for RIR
		3.1 CLFR: Contrastive Learning for Late Fusion RIR
		3.2 CEFR: Contrastive Learning for Early Fusion RIR
	4 Experiments
		4.1 Reviewed-Item Retrieval Dataset (RIRD)
		4.2 Experimental Setup
		4.3 Baselines
		4.4 Evaluation Metrics
		4.5 Results and Discussion
	5 Conclusion
	References
User Requirement Analysis for a Real-Time NLP-Based Open Information Retrieval Meeting Assistant
	1 Introduction
	2 Related Work
		2.1 Meeting Assistants
		2.2 General Guidelines Concerning Recommender Systems
		2.3 User Experience of Recommender Systems
	3 Method
		3.1 User-Centered Design Approach
		3.2 Participants
		3.3 Study Material
		3.4 Study Procedure
	4 Results
		4.1 Prior Experience with Recommender Systems
		4.2 Participants' Experience with the Meeting Assistant
		4.3 The Presenters' Experience with the Meeting Assistant
		4.4 Envisioned Use Cases for the Meeting Assistant
	5 Discussion and Recommendations
		5.1 Introduce the System to Users
		5.2 Annotate Visual Material with Titles and Keywords
		5.3 Cater to User Preferences
		5.4 Add Interactivity Options
		5.5 Companion Style
	6 Limitations and Future Work
	7 Conclusion
	References
Auditing Consumer- and Producer-Fairness in Graph Collaborative Filtering
	1 Introduction and Motivations
	2 Nodes Representation and Neighborhood Exploration in Graph Collaborative Filtering: A Formal Taxonomy
		2.1 Preliminaries
		2.2 Updating Node Representation Through Message-Passing
		2.3 Weighting the Importance of Graph Edges
		2.4 Going Beyond Message-Passing
		2.5 A Taxonomy of Graph CF Approaches
	3 Taxonomy-aware Evaluation
	4 Trade-off Analysis
	5 Conclusion and Future Work
	A  Experimental Settings and Protocols
	References
Exploiting Graph Structured Cross-Domain Representation for Multi-domain Recommendation
	1 Introduction
	2 Related Work
	3 Methodology
	4 Experiments
	5 Conclusions and Future Work
	References
Injecting the BM25 Score as Text Improves BERT-Based Re-rankers
	1 Introduction
	2 Related Work
	3 Methods
		3.1 First Stage Ranker: BM25
		3.2 CECAT: Cross-Encoder Re-rankers Without BM25 Injection
		3.3 CEBM25CAT: Cross-Encoder Re-rankers with BM25 Injection
		3.4 Linear Interpolation Ensembles of BM25 and CECAT
	4 Experimental Design
	5 Results
		5.1 Main Results: Addressing Our Research Questions
		5.2 Analysis of the Results
	6 Conclusion and Future Work
	References
Quantifying Valence and Arousal in Text with Multilingual Pre-trained Transformers*-12pt
	1 Introduction
	2 Related Work
	3 Models for Predicting Valence and Arousal from Text
	4 Resources
	5 Experimental Evaluation
		5.1 Results with Different Models and Loss Functions
		5.2 Results per Language and Dataset
		5.3 Results in Zero-Shot Settings
	6 Conclusions and Future Work
	References
A Knowledge Infusion Based Multitasking System for Sarcasm Detection in Meme
	1 Introduction
	2 Related Work
	3 Dataset
	4 Methods
		4.1 Feature Extraction Layer
		4.2 Multimodal Fusion
		4.3 Knowledge Infusion (KI)
		4.4 Classification
	5 Results
	6 Analysis
	7 Conclusion
	References
Multilingual Detection of Check-Worthy Claims Using World Languages and Adapter Fusion
	1 Introduction
	2 Related Work
		2.1 Identifying Check-Worthy Claims
		2.2 Adapters
	3 Datasets
		3.1 Task Datasets
		3.2 Topical Evaluation Dataset
	4 Methodology
		4.1 World Language Adapter Fusion
		4.2 Implementation Details
	5 Baselines
	6 Results and Discussion
	7 Further Analysis
	8 Conclusion and Future Work
	References
Market-Aware Models for Efficient Cross-Market Recommendation
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Market-Unaware Models
		3.2 Market-Aware Models
	4 Experimental Setup
	5 Results and Discussion
		5.1 Pairwise Experiments
		5.2 Global Experiments
	6 Conclusions and Future Work
	References
TourismNLG: A Multi-lingual Generative Benchmark for the Tourism Domain
	1 Introduction
	2 Related Work
		2.1 Data Science in Tourism
		2.2 Domain-specific Pretrained Models
	3 TourismNLG Benchmark
		3.1 TourismNLG Datasets
		3.2 TourismNLG Tasks
	4 Baseline Models for TourismNLG
		4.1 Model Selection
		4.2 Pre-Training and Finetuning
		4.3 Metrics
		4.4 Implementation Details for Reproducibility
	5 Experiments and Results
	6 Conclusions
	References
An Interpretable Knowledge Representation Framework for Natural Language Processing with Cross-Domain Application
	1 Introduction
	2 Related Work
	3 Data Representation Framework
		3.1 Tsetlin Machine
		3.2 Data Representation
	4 Experiments and Results
		4.1 Datasets
		4.2 Implementation Details
		4.3 Baselines
		4.4 Results and Analysis
		4.5 Visualization
		4.6 Concluding Remarks
	5 A Case Study: Interpretability
	6 Application: Domain Adaptation
	7 Conclusion
	References
Graph-Based Recommendation for Sparse and Heterogeneous User Interactions
	1 Introduction
	2 Related Work
	3 Approach
		3.1 Heterogeneous Graph Representation of User Interactions
		3.2 Generating Recommendations Using Random Walks
		3.3 Optimizing Edge Weights Using Genetic Algorithm
	4 Experiments
		4.1 Use Cases and Datasets
		4.2 Evaluation Procedure
		4.3 Baselines, Implementation, and Hyperparameters
		4.4 Results
	5 Conclusions and Future Work
	References
It's Just a Matter of Time: Detecting Depression with Time-Enriched Multimodal Transformers
	1 Introduction
	2 Related Work
	3 Method
	4 Experiments
		4.1 Datasets
		4.2 Experimental Settings
		4.3 Comparison Models
		4.4 Training and Evaluation Details
	5 Results
		5.1 Performance Comparison with Prior Works
		5.2 Ablation Study
		5.3 Error Analysis
		5.4 Limitations and Ethical Considerations
	6 Conclusion
	References
Recommendation Algorithm Based on Deep Light Graph Convolution Network in Knowledge Graph
	1 Introduction
	2 Related Work
		2.1 Problem Formulation
		2.2 Recent Work
	3 Method
		3.1 Overall Structure of KDL-GCN
		3.2 User-Entity Bipartite Graph Method
		3.3 Deep Light Graph Convolution Network
		3.4 Node Embedding Fusion and Rating Prediction
		3.5 Optimization
		3.6 Time Complexity Analysis
	4 Experiments
		4.1 Experiment Setup
		4.2 Performance Comparison
		4.3 Ablation Analysis
	5 Conclusion
	References
Query Performance Prediction for Neural IR: Are We There Yet?*-12pt
	1 Introduction
	2 Related Work
	3 Methodology
	4 Experimental Setup
	5 Experimental Results
		5.1 QPP Models Performance
		5.2 ANOVA Analysis
	6 Conclusion and Future Work
	References
Item Graph Convolution Collaborative Filtering for Inductive Recommendations
	1 Introduction
	2 Preliminaries and Related Work
		2.1 GCN-Based Recommender
		2.2 Item-Based Recommender
	3 Methodology
		3.1 Graph Projection Module
		3.2 Item Embedding Module
		3.3 User Embedding Module
		3.4 Model Training
	4 Experiments
		4.1 Datasets
		4.2 Baselines
		4.3 Transductive Performance
		4.4 Inductive Performance
		4.5 Ablation Study
	5 Conclusion and Future Work
	References
CoLISA: Inner Interaction via Contrastive Learning for Multi-choice Reading Comprehension
	1 Introduction
	2 Task Formulation
	3 Methodology
		3.1 DPR-Based Retriever
		3.2 In-Sample Attention Mechanism
		3.3 Contrastive Learning for Inner Interaction
	4 Experimentation
		4.1 Experimental Settings
		4.2 Main Results
		4.3 Analysis
	5 Related Work
	6 Conclusion
	References
Viewpoint Diversity in Search Results*-12pt
	1 Introduction
	2 Related Work
	3 Evaluating Viewpoint Diversity in Search Results
		3.1 Measuring Polarity, Stance, and Logic Bias
		3.2 Normalized Discounted Viewpoint Bias
	4 Case Study: Evaluating, Fostering Viewpoint Diversity
		4.1 Materials
		4.2 Viewpoint Diversity Evaluation Results
		4.3 Viewpoint Diversification
	5 Discussion
	6 Conclusion
	References
COILcr: Efficient Semantic Matching in Contextualized Exact Match Retrieval*-12pt
	1 Introduction
	2 Related Work
	3 COILCR: Contextualized Inverted Lists with Canonical Representations
		3.1 Term Score Factorization
		3.2 Approximate Term Semantic Interaction
	4 Experimental Methodology
	5 Experiments
		5.1 Passage Retrieval Effectiveness
		5.2 Balancing Model Efficiency
		5.3 Canonical Representation Analysis
	6 Conclusion and Future Work
	References
Bootstrapped nDCG Estimation in the Presence of Unjudged Documents*-12pt
	1 Introduction
	2 Background and Related Work
	3 Bootstrapping nDCG Scores
		3.1 Preparatory Theoretical Considerations
		3.2 Our Bootstrapped nDCG Estimation Approach
		3.3 Conceptual Comparison
	4 Evaluation
		4.1 Experimental Setup
		4.2 Evaluation Results
	5 Conclusion
	References
Predicting the Listening Contexts of Music Playlists Using Knowledge Graphs*-12pt
	1 Introduction
	2 Related Work
	3 Method
		3.1 Matrix Factorisation-Based
		3.2 Convolutional Neural Network-Based
		3.3 Knowledge Graph-Based
		3.4 Hybrid
		3.5 Implementation Details
	4 Experiments
		4.1 Dataset
		4.2 Metrics
		4.3 Results
	5 Conclusions and Future Work
	References
Keyword Embeddings for Query Suggestion*-12pt
	1 Introduction
	2 Related Work
	3 Proposal
	4 Experimental Setup
		4.1 Datasets
		4.2 Baselines
		4.3 Evaluation
		4.4 Experimental Settings
	5 Results
	6 Conclusions
	References
Domain-Driven and Discourse-Guided Scientific Summarisation
	1 Introduction
	2 Related Work
	3 Method
		3.1 Salient Section Determination
		3.2 Rhetorical Content Modelling
		3.3 Centrality-based Summariser
	4 Experimental Setup
	5 Experimental Results
		5.1 Structural Discourse Analyses
		5.2 Abstract Generation
	6 Conclusions
	References
Injecting Temporal-Aware Knowledge in Historical Named Entity Recognition
	1 Introduction
	2 Related Work
	3 Datasets
	4 Temporal Knowledge-based Contexts for Named Entity Recognition
		4.1 Temporal Information Integration
		4.2 Context Retrieval
		4.3 Named Entity Recognition Architecture
	5 Experimental Setup
		5.1 Results
		5.2 Impact of Time Intervals
		5.3 Impact of Digitization Errors
		5.4 Limitations
	6 Conclusions & Future Work
	References
A Mask-based Logic Rules Dissemination Method for Sentiment Classifiers
	1 Introduction
	2 Related Work
		2.1 Implicit Methods to Construct Neural-Symbolic Systems
		2.2 Explicit Methods to Construct Neural-Symbolic Systems
	3 Methodology
		3.1 Sources of Logic Rules
		3.2 Rule-Mask Mechanism to Disseminate Logical Information
	4 Covid-19 Twitter Dataset
		4.1 Sentiment Labels
		4.2 Rule Labels
		4.3 Contrast Labels
		4.4 Constructed Dataset
	5 Experimental Results
		5.1 Dataset Preparation
		5.2 Sentiment Classifiers
		5.3 Metrics
		5.4 Results
	6 Conclusion
	References
Contrasting Neural Click Models and Pointwise IPS Rankers
	1 Introduction
	2 Related Work
	3 Background
	4 Methods
		4.1 Comparing Unbiasedness
		4.2 A Difference in Loss Magnitude
	5 Experimental Setup
	6 Results and Analysis
		6.1 Main Findings
		6.2 Further Analyses
	7 Conclusion
	References
Sentence Retrieval for Open-Ended Dialogue Using Dual Contextual Modeling*-12pt
	1 Introduction
	2 Related Work
	3 Retrieval Framework for Open Dialogues
		3.1 Sentence Retrieval Methods
	4 Experimental Setting
	5 Results
	6 Conclusions and Future Work
	References
Temporal Natural Language Inference: Evidence-Based Evaluation of Temporal Text Validity
	1 Introduction
	2 Related Work
		2.1 Temporal Information Retrieval and Processing
		2.2 Commonsense Reasoning
		2.3 Natural Language Inference
		2.4 Incorporation of Knowledge Bases
		2.5 Comparison with Related Tasks
	3 Task Definition
	4 Proposed Method
		4.1 Encoding Knowledge
		4.2 Combined Model
	5 Dataset
		5.1 Dataset Construction
		5.2 Dataset Statistics
	6 Experiments
		6.1 Experimental Settings
		6.2 Experiments with NLI Pre-training
		6.3 Incorporating Common-sense Knowledge
		6.4 Testing Different Knowledge Embedding Approaches
	7 Conclusion and Future Work
	References
Theoretical Analysis on the Efficiency of Interleaved Comparisons*-12pt
	1 Introduction
	2 Related Works
		2.1 User Click Behavior
		2.2 Online Evaluation
	3 Preliminary
		3.1 Interleaving Method for Analysis (IMA)
		3.2 A/B Testing
		3.3 Notation
		3.4 Definition of Efficiency
	4 Theoretical Analysis
	5 Numerical Analysis
	6 User Simulation
		6.1 Datasets
		6.2 User Behavior
		6.3 Results
	7 Conclusion
	References
Intention-Aware Neural Networks for Question Paraphrase Identification
	1 Introduction
	2 Related Work
	3 Preliminary
		3.1 VAE, CVAE and MVAE
		3.2 Heuristic Intention Extraction
	4 Approach
		4.1 CVAE-Based Intention-Aware QPI
		4.2 MVAE-Based Intention-Aware QPI
	5 Experimentation
		5.1 Corpora and Evaluation Metrics
		5.2 Hyperparameter Settings
		5.3 Main Results
		5.4 Ablation Experiments
		5.5 Effectiveness Analysis
		5.6 Case Study
	6 Conclusion
	References
Automatic and Analytical Field Weighting for Structured Document Retrieval
	1 Introduction
	2 Background
	3 Information Content Field Weighting (ICFW)
		3.1 Model Specification
		3.2 Setting the Scale Parameter Lambda
		3.3 Approximating Appropriate Values for Lambda Threshold
		3.4 Optimising ICFW
	4 Experimentation and Analysis
		4.1 Data Collections
		4.2 Baselines and Methodology
		4.3 RQ1: The Effect of Term Frequency Saturation on Performance
		4.4 RQ2: Estimating Lambda Analytically
		4.5 RQ3: Optimized ICFW Performance
	5 Conclusion
	A Scale Parameter Threshold
	References
An Experimental Study on Pretraining Transformers from Scratch for IR
	1 Introduction
	2 Related Work
	3 Pretraining from Scratch
		3.1 Pretraining
	4 Experiments
		4.1 RQ1: Are Models Fully Trained on MSMARCO as Good as Models Pretrained on a Diverse Collection Set?
		4.2 RQ2: Do Models Pretrained in MSMARCO Generalize Well on Other Collections?
		4.3 RQ3: Can We Take Advantage of that Pretraining from Scratch in Collections of Specialized Domains/Languages
		4.4 RQ4: Impact of Architectures
	5 Conclusion
	References
Neural Approaches to Multilingual Information Retrieval*-12pt
	1 Introduction
	2 Background
	3 Fine-Tuning MPLMs for MLIR
		3.1 English Training (ET)
		3.2 Multilingual Translate Training (MTT)
	4 Experiments
		4.1 Neural Retrieval Models
		4.2 Evaluation
	5 Results
		5.1 Multilingual Batching for Fine-Tuning
		5.2 Effectiveness Relative to Baselines
		5.3 Preprocessing and Indexing Time
	6 Analysis
		6.1 Language Bias
		6.2 Example Queries
	7 Conclusion and Future Work
	A MTT Implementation Details
	References
CoSPLADE: Contextualizing SPLADE for Conversational Information Retrieval*-12pt
	1 Introduction
	2 Related Works
	3 Model
		3.1 First Stage
		3.2 Reranking
	4 Experimental Protocol
		4.1 Datasets
		4.2 Metrics and Baselines
	5 Results
		5.1 First-Stage Ranking Effectiveness
		5.2 Second-Stage Ranking Effectiveness
		5.3 Effectiveness Compared to TREC CAsT Participants
		5.4 Efficiency
	6 Conclusion
	References
SR-CoMbEr: Heterogeneous Network Embedding Using Community Multi-view Enhanced Graph Convolutional Network for Automating Systematic Reviews
	1 Introduction
	2 Preliminaries
		2.1 Heterogeneous Information Network
		2.2 Graph Convolutional Networks
	3 Related Works
	4 SR-CoMbEr
		4.1 Heterogeneous Community Detection
		4.2 Community Multi-view Learning
		4.3 Global Consensus
	5 Experimental Design
		5.1 Dataset
		5.2 Baselines
		5.3 Evaluation Metrics
		5.4 Implementation Details
	6 Experimental Results
		6.1 Systematic Review
		6.2 Ablation Study
	7 Conclusion
	References
Multimodal Inverse Cloze Task for Knowledge-Based Visual Question Answering
	1 Introduction
	2 Related Work
	3 Methods
		3.1 Information Retrieval Framework
		3.2 Models
		3.3 Training Stages
		3.4 Inference
		3.5 Implementation Details
	4 Results
		4.1 Information Retrieval
		4.2 Reading Comprehension
	5 Generic vs. Specialized Image Representations
	6 Conclusion and Perspectives
	References
A Transformer-Based Framework for POI-Level Social Post Geolocation
	1 Introduction
	2 Related Work
		2.1 Post Geolocation
		2.2 Hierarchical Geolocation
	3 Method
		3.1 Problem Formulation
		3.2 Method Overview
		3.3 Feature Representation
		3.4 Feature Fusion
		3.5 Hierarchical Prediction
	4 Experimental Setting
		4.1 Datasets
		4.2 Evaluation Metrics
		4.3 Parameter Setting
		4.4 Baselines
	5 Experimental Results
		5.1 Baseline Comparison
		5.2 Representation Combination Selection
		5.3 Ablation Study
		5.4 Coarse-Level Geolocation
	6 Conclusion
	References
Document-Level Relation Extraction with Distance-Dependent Bias Network and Neighbors Enhanced Loss
	1 Introduction
	2 Methodology
		2.1 Crossing-Distance Calculation
		2.2 SDBN
		2.3 Bias Network
		2.4 Neighbors Enhanced Loss
	3 Experiment
		3.1 Datasets
		3.2 Implementation Details
		3.3 Compared Methods
		3.4 Main Results
		3.5 Ablation Study
		3.6 Robustness Analysis
		3.7 Hyper-parameter Analysis
		3.8 Case Study
	4 Related Work
	5 Conclusion
	References
Investigating Conversational Agent Action in Legal Case Retrieval
	1 Introduction
	2 Related Work
	3 User Study
		3.1 Conversational Legal Case Retrieval
		3.2 Tasks and Participants
		3.3 Procedure
	4 Results
		4.1 Analysis on Conversational Agent Action
		4.2 Conversational Agent Action Prediction
	5 Conclusion
	References
MS-Shift: An Analysis of MS MARCO Distribution Shifts on Neural Retrieval
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Distribution Shifts
		3.2 Evaluation Procedure
	4 Experimental Setup
	5 Results and Analysis
		5.1 Performance Evaluation on Distribution Shifts
		5.2 Train/Test Distribution Similarity
	6 Conclusion
	References
Listwise Explanations for Ranking Models Using Multiple Explainers*-12pt
	1 Introduction
	2 Related Work
	3 Background and Preliminaries
		3.1 Explainers for Ranking
		3.2 Explanations to a Ranking Model
		3.3 Problem Statement
	4 Generalized Preference Coverage
		4.1 The Preference Coverage Framework
		4.2 Optimizing PC for Multiple Explainers
	5 Experimental Setup
		5.1 Datasets and Ranking Models
		5.2 Baseline and Competitors
		5.3 Metrics
	6 Evaluation Results
		6.1 Effectiveness of Explanations
		6.2 Utility of Explanations
	7 Conclusion and Outlook
	References
Improving Video Retrieval Using Multilingual Knowledge Transfer
	1 Introduction
	2 Related Work
		2.1 Video Retrieval
		2.2 Multilingual Training
	3 MKTVR: Multilingual Knowledge Transfer for Video Retrieval
		3.1 Problem Statement
		3.2 Approach
	4 Experiments
		4.1 Datasets
		4.2 Metrics
		4.3 Implementation Details
	5 Results and Discussion
		5.1 Evaluation on English Video Retrieval Datasets
		5.2 Evaluation on Multilingual Video Retrieval Datasets
		5.3 Ablation Studies
	6 Conclusion
	References
Service Is Good, Very Good or Excellent? Towards Aspect Based Sentiment Intensity Analysis
	1 Introduction
	2 Resource Creation
	3 Methodology
		3.1 Seq2Seq Generation
		3.2 Model Explainability
	4 Experiments and Analysis
		4.1 Experimental Results
		4.2 Detailed Analysis
	5 Conclusion
	References
Effective Hierarchical Information Threading Using Network Community Detection*-12pt
	1 Introduction
	2 Related Work
	3 Proposed Approach: HINT
	4 Experimental Setup
	5 Offline Evaluation
		5.1 Results
		5.2 Ablation Study
	6 User Study
		6.1 Results
	7 Identifying Incremental Threads
	8 Conclusions
	References
HADA: A Graph-Based Amalgamation Framework in Image-Text Retrieval
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Revisit State-of-the-Art Models
		3.2 Create Graph Structure
		3.3 Graph Neural Network
		3.4 Training Tasks
	4 Experiment
		4.1 Dataset and Evaluation Metrics
		4.2 Implementation Details
		4.3 Baselines
		4.4 Comparison to Baseline
		4.5 HADA with Other Input Models
	5 Conclusion
	References
Author Index