Advances in Information Retrieval

Name: Advances in Information Retrieval | 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10-14, 2022, Proceedings, Part I
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44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10-14, 2022, Proceedings, Part I

Matthias Hagen Suzan Verberne Craig MacDonald Christin Seifert Krisztian Balog Kjetil Nørvåg Vinay Setty(Herausgeber*in)

Springer (Verlag)

Erschienen am 5. April 2022

XXXII, 705 Seiten

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978-3-030-99736-6 (ISBN)

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Inhalt

Intro
Preface
Organization
Contents - Part I
Contents - Part II
Full Papers
Supercalifragilisticexpialidocious: Why Using the ``Right'' Readability Formula in Children's Web Search Matters
1 Introduction
2 Background and Related Work
3 The Fit of Readability Formulas on Web Text
4 The Effect of Readability on Web Search for Children
5 Conclusion and Future Work
References
PARM: A Paragraph Aggregation Retrieval Model for Dense Document-to-Document Retrieval
1 Introduction
2 Related Work
3 Paragraph Aggregation Retrieval Model (PARM)
3.1 Workflow
3.2 Vector-Based Aggregation with Reciprocal Rank Fusion Weighting (VRRF)
3.3 Training Strategies
4 Experiment Design
4.1 Training and Test Collections
4.2 Baselines
5 Results and Analysis
5.1 RQ1: VRRF Aggregation for PARM
5.2 RQ2: PARM VRRF vs Document-Level Retrieval
5.3 RQ3: Paragraph-Level vs Document-level Labelled Training
5.4 Analysis of Paragraph Relations
6 Conclusion
References
Recommendation of Compatible Outfits Conditioned on Style
1 Introduction
2 Methodology
2.1 Style Encoder Network
2.2 Style classifier
2.3 SCA Net
2.4 Outfit Generation
3 Experimental Evaluation
3.1 Compatibility Experiment
3.2 Style Experiments
4 Conclusion
References
Why Did You Not Compare with That? Identifying Papers for Use as Baselines
1 Introduction
2 Related Work
3 Dataset for Baseline Classification
3.1 Observations and Characteristics of the Dataset
4 Multi-module Attention Based Baseline Classifier
5 Empirical Results and Discussions
6 Conclusions
References
Exploring Entities in Event Detection as Question Answering
1 Introduction
2 Related Work
3 Event Question Answering Model with Entity Positions, Types, and Argument Roles
4 Experiments
5 Discussion
5.1 Trigger Ambiguity Analysis
5.2 Evaluation on Unseen Event Types
6 Conclusions and Perspectives
References
Validating Simulations of User Query Variants
1 Introduction
2 Related Work
3 Approach
3.1 Query Simulation
3.2 Evaluation Framework
3.3 Datasets and Implementation Details
4 Experimental Results
5 Discussion
6 Conclusion
A Appendix
References
Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models
1 Introduction
2 Related Work
3 Method
3.1 Hybrid Retrieval Model
3.2 Lexical Retrieval Model
3.3 Deep Retrieval Model
4 Experimental Setup
4.1 Datasets
4.2 Data Processing and Benchmarking
5 Evaluation
5.1 Generalization of the Deep Retrieval Model
5.2 Utility of Query and Document Expansion
5.3 Complementarity of Lexical and Deep Retrieval Models
5.4 Effectiveness of the Proposed Hybrid Model
6 Discussion
7 Conclusion
References
Incorporating Ranking Context for End-to-End BERT Re-ranking
1 Introduction
2 Related Work
3 Method
3.1 Overview
3.2 End-to-End Groupwise Scorer
3.3 Light-Weight Pseudo Relevance Feedback
3.4 End-to-End Training of the Model
4 Experiment Setup
4.1 Dataset and Metrics
4.2 Baselines and Co-BERT Variants
4.3 Model Training and Inference
5 Results
5.1 Overall Performance of Co-BERT
5.2 Study of Groupwise Ranking
5.3 Study of Light-Weight PRF Calibrator
5.4 Effectiveness on TREC DL
6 Conclusion
References
WANDS: Dataset for Product Search Relevance Assessment
1 Introduction
2 Related Work
3 Annotation Guidelines Design
3.1 Design Principles
3.2 Query-Product Annotation
4 Annotation Process
4.1 Query Sampling
4.2 Constructing the Product Pool
4.3 Iterative Product Mining for Dataset Completeness
5 Dataset
6 Experimental Evaluation
7 Discussion
7.1 Effectiveness of Sampling Sources
7.2 Iterative Product Mining for Dataset Completeness Step
8 Conclusions and Future Work
References
Searching, Learning, and Subtopic Ordering: A Simulation-Based Analysis
1 Introduction
2 Related Work
3 Subtopic-Aware Complex Searcher Model (SACSM)
4 Experimental Method
4.1 Fixed SACSM Components
4.2 Variable SACSM Components
4.3 Simulation Setup
5 Results
6 Conclusions
References
Immediate Text Search on Streams Using Apoptosic Indexes
1 Introduction
2 Background
3 Apoptosic Structures
3.1 Text Search
4 Experiments
5 Conclusions
References
Influence-Based Deep Network for Next POIs Prediction
1 Introduction
2 Problem Definition
3 Methodology
3.1 User Representation
3.2 Group Representation
3.3 The Interaction Learning Module
4 Experimental Evaluation
5 Conclusion
References
A Dependency-Aware Utterances Permutation Strategy to Improve Conversational Evaluation
1 Introduction
2 Related Work
3 Methodology
3.1 RQ1: A Dependence-Aware Utterance Permutation Strategy
3.2 RQ3: Exploiting Permuted Conversation Utterances
4 Experimental Analysis
4.1 Conversational Models
4.2 RQ1: Permuting Conversations
4.3 RQ2: Conversational Systems Performance on Permuted Conversations
4.4 RQ3: Comparing Systems via ANOVA
5 Conclusions and Future Works
References
Sentiment Guided Aspect Conditioned Dialogue Generation in a Multimodal System
1 Introduction
2 Related Work
3 Methodology
4 Dataset
5 Experiments
6 Results and Analysis
7 Conclusion and Future Work
References
An Analysis of Variations in the Effectiveness of Query Performance Prediction
1 Introduction
2 Related Work
3 Anatomy of a QPP Evaluation Framework
4 Experimental Setup
5 Results
5.1 RQ1: Variations in QPP Evaluations
5.2 RQ2: Variations in the Relative Ranks of QPP Methods
6 Concluding Remarks
References
Search Clarification Selection via Query-Intent-Clarification Graph Attention
1 Introduction
2 Related Work
2.1 Conversational Search
2.2 Asking Clarifications
3 Our Proposed Framework
3.1 Model Architecture
3.2 Loss Function
4 Experiments
4.1 Dataset
4.2 Baselines
4.3 Evaluation Metrics
4.4 Implementation Details
4.5 Experimental Results
5 Conclusion
References
Continual Learning of Long Topic Sequences in Neural Information Retrieval
1 Introduction
2 Related Works
3 Research Design for Continual Learning in IR
3.1 Continual Learning Setting and Metrics
3.2 Neural Ranking Models and Learning
4 MSMarco Continual Learning Corpus
4.1 RQ1: Modeling the Long Topic Sequence
4.2 Evaluating the Long Topic Sequence
4.3 IR-Driven Controlled Stream-Based Scenario
5 Model Performance and Learning Behavior on Long Topic Sequences
5.1 RQ2: Performances on the MSMarco Long Topic Sequence
5.2 Fine-Grained Analysis
5.3 RQ3: Behavior on IR-Driven Controlled Settings
6 Conclusion and Future Work
References
Ensemble Model Compression for Fast and Energy-Efficient Ranking on FPGAs
1 Introduction
2 Related Work
3 Using Programmable Logic for Ranking
4 Ranking Model Compression
5 Experiments
5.1 Effectiveness Assessment
5.2 Efficiency Assessment
5.3 Data Transfer Assessment
5.4 Energy Consumption Assessment
6 Conclusions and Future Work
References
Local Citation Recommendation with Hierarchical-Attention Text Encoder and SciBERT-Based Reranking
1 Introduction
2 Related Work
3 Proposed Dataset
4 Approach
4.1 Prefetching Model
4.2 Reranking Model
4.3 Loss Function
5 Experiments
6 Results and Discussion
6.1 Prefetching Results
6.2 Reranking Results
6.3 Performance of Entire Recommendation Pipeline
7 Conclusion
References
Extending CLIP for Category-to-Image Retrieval in E-Commerce
1 Introduction
2 Related Work
3 Approach
4 Experimental Setup
5 Experimental Results
6 Error Analysis
7 Conclusion
References
WIDAR - Weighted Input Document Augmented ROUGE
1 Introduction
2 Related Works
3 WIDAR Evaluation Metric
3.1 Weighted ROUGE
3.2 Combining Weighted ROUGE with Input Document Similarity
4 Experiments
4.1 Dataset
4.2 Evaluation of Evaluation Metric
4.3 Experimental Settings
5 Results and Discussions
5.1 Computational Time Analysis
5.2 Ablation Study
5.3 Study of Human Judgement Scores
6 Conclusion
References
Bi-granularity Adversarial Training for Non-factoid Answer Retrieval
1 Introduction
2 Related Work
3 Methodology
3.1 Task Definition
3.2 Basic Answer Retrieval Model (Baseline)
3.3 Adversarial Examples Generation Strategy
3.4 Self-adaptive Adversarial Training
4 Experimentation
4.1 Data and Evaluation
4.2 Hyperparameter Settings and Ranking Scenario
5 Results and Discussion
5.1 Utility of Token-Level Adversarial Examples
5.2 Effect of Bi-granularity Adversarial Training (BAT)
5.3 Comparison to State of the Art
5.4 Statistical and Practical Significance Test
6 Conclusion
References
RATE: A Reliability-Aware Tester-Based Evaluation Framework of User Simulators
1 Introduction
2 Tester-Based Evaluation (TBE)
3 Reliability-Aware Tester-Based Evaluation (RATE)
3.1 Reliability of a Tester
3.2 Reliability of User Simulator
4 Evaluation
4.1 Experiment Design
4.2 Experiment Results
5 Conclusion
References
HC4: A New Suite of Test Collections for Ad Hoc CLIR
1 Introduction
2 Related Work
3 Collection Development Methodology
3.1 Topic Development
3.2 Relevance Judgments
3.3 Contemporaneous Reports
4 Collection Details
4.1 Development and Annotation Time
4.2 Inter-assessor Agreement
5 Baseline Runs
6 Conclusion
References
Did I See It Before? Detecting Previously-Checked Claims over Twitter
1 Introduction
2 Related Work
3 The Proposed Pipeline
3.1 Preprocessing
3.2 Initial Retrieval
3.3 Reranking
4 Experimental Setup
5 Experimental Evaluation
5.1 Initial Retrieval with Preprocessing ([rqspspreprocessing]RQ1)
5.2 MonoBERT for Reranking ([rqspstunespsdepth]RQ2)
5.3 Leveraging Verified Claim Fields ([rqspsfields]RQ3)
5.4 Performance on Arabic Data ([rqspsarabic]RQ4)
6 Conclusion and Future Work
References
Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models
1 Introduction
2 Related Work
3 ColBERT-X
3.1 CLIR Training Strategies
3.2 Retrieval
4 Experiments
5 Detailed Analysis
5.1 Effect of Machine Translation
5.2 Effect of Multilingual Language Models
5.3 Pseudo-Relevance Feedback
5.4 Effect of Longer Queries
5.5 Indexing Footprint
6 Conclusion
References
Evaluating the Robustness of Retrieval Pipelines with Query Variation Generators
1 Introduction
2 Related Work
3 Automatic Query Variations
3.1 UQV Taxonomy
3.2 Query Generators
4 Experimental Setup
5 Results
6 Conclusions
References
Exploiting Document-Based Features for Clarification in Conversational Search
1 Introduction
2 Related Work
3 Methodology
3.1 Feature Extraction from Retrieved Documents
3.2 Facet Extraction
3.3 Facet-Based Question Generation
4 Evaluation Setting
4.1 Evaluation Dataset
4.2 Evaluation of Document-Level Features
4.3 Evaluation of Facet Extraction
4.4 Evaluation of the Usefulness of Facet-Based Clarifying Questions
5 Results and Discussion
5.1 Precision and Recall of Extracted Feature Sets
5.2 Facet-Based Retrieval
5.3 Usefulness of Clarifying Questions
6 Conclusions
References
Adversarial Multi-task Model for Emotion, Sentiment, and Sarcasm Aided Complaint Detection
1 Introduction
2 Related Work
3 Dataset
3.1 Data Annotation
3.2 Annotation Specifications
4 Proposed Methodology
4.1 Problem Definition
4.2 Multi-task Model for Emotion, Sentiment, and Sarcasm Aided Complaint Detection (MTLAll)
4.3 Feature Extraction
4.4 Encoding Model
4.5 Intra-model Attention
4.6 Adversarial Loss
4.7 Output Layer
5 Experiments, Results, and Analysis
5.1 Baselines
5.2 Experimental Setup
5.3 Results and Discussion
5.4 Error Analysis
6 Conclusion and Future Work
References
Joint Personalized Search and Recommendation with Hypergraph Convolutional Networks
1 Introduction
2 Related Work
3 Problem Definition
4 Method
4.1 Hypergraph Construction
4.2 HyperSaR Convolution Operation
4.3 Model Training and Inference
5 Experimental Setup
5.1 Datasets
5.2 Baselines
5.3 Hyperparameter Setting
6 Experiment Results
6.1 Evaluation on the JPSR Task
6.2 Hyperparameter Impact
7 Conclusion
References
Topic Aware Contextualized Embeddings for High Quality Phrase Extraction
1 Introduction
2 Related Work
2.1 Unsupervised Keyphrase Extraction
2.2 Contextualized Vector Representations
3 Methodology
3.1 Vector Representations for the Phrases and the Document
3.2 Graph Based Ranking
4 Experiments and Results
4.1 Datasets
4.2 Baselines and Variants of the Proposed Method
4.3 Results and Discussion
4.4 Effects of Different Hyperparameters
4.5 Keyphrase Expansion Results
5 Conclusions
References
Topic Modeling on Podcast Short-Text Metadata
1 Introduction
2 Related Work
3 Methods
3.1 Notations and Preliminaries
3.2 NE-informed Corpus Embedding (NEiCE)
4 Datasets
5 Experimental Setup
6 Results and Discussion
7 Conclusion
References
Effective Rating Prediction Using an Attention-Based User Review Sentiment Model
1 Introduction
2 Related Work
3 The SentiAttn Model
3.1 Task Definition
3.2 Review Sentiment Information Analysis
3.3 Model Architecture
4 Experimental Setup
4.1 Datasets
4.2 Baselines and Evaluation Metrics
4.3 Model Setting
5 Results
6 Conclusions
References
Goldilocks: Just-Right Tuning of BERT for Technology-Assisted Review
1 Introduction
2 Background
3 Adapting BERT for TAR
4 Experiment Setup
4.1 Data Sets
4.2 Software and Evaluation
4.3 Hardware
5 Results and Analysis
5.1 Language Model Fine-Tuning
5.2 Just-Right Varies Across Tasks
5.3 Running Time
6 Summary and Future Works
References
Multi-modal Sentiment and Emotion Joint Analysis with a Deep Attentive Multi-task Learning Model
1 Introduction
2 Related Work
2.1 Multi-modal Sentiment Analysis
2.2 Multi-modal Emotion Recognition
3 Methodology
3.1 Task Description and Overall Network
3.2 Multi-modal Encoder
3.3 External Information Extraction
3.4 Multi-head Cross-modal Attentive Fusion
3.5 Cross-task Attention Mechanism
3.6 Classification
4 Experimental Setup
4.1 Experiment Settings
4.2 Comparison Models
4.3 Comparative Analysis
4.4 STL v/s MTL Framework
4.5 Ablation Test
4.6 Misclassification Cases
5 Conclusions and Future Work
References
Reproducibility Papers
Do Lessons from Metric Learning Generalize to Image-Caption Retrieval?
1 Introduction
2 Background and Related Work
3 Do Findings from Metric Learning Extend to ICR?
4 A Method for Analyzing the Behavior of Loss Functions
5 Analyzing the Behavior of Loss Functions for ICR
6 Conclusion
References
Consumer Fairness in Recommender Systems: Contextualizing Definitions and Mitigations
1 Introduction
2 Research Methodology
2.1 Mitigation Procedures Collection
2.2 Mitigation Procedures Reproduction
2.3 Mitigation Procedures Evaluation
3 Experimental Results
3.1 Impact on Recommendation Utility (RQ1)
3.2 Impact on Group Unfairness (RQ2)
3.3 Relationships Between Representation and Unfairness (RQ3)
4 Discussion and Conclusions
References
The Power of Anchor Text in the Neural Retrieval Era
1 Introduction
2 Related Work
3 The Webis MS MARCO Anchor Text 2022 Dataset
4 Properties of Anchor Texts, Queries, and Documents
5 Anchor Text and Retrieval Effectiveness
5.1 Navigational Queries for MS MARCO
5.2 Retrieval Models and Training
5.3 Evaluation
6 Conclusion
References
Automation of Citation Screening for Systematic Literature Reviews Using Neural Networks: A Replicability Study
1 Introduction
2 Related Work
3 Experiment Setup
3.1 Models
3.2 Data
3.3 Evaluation
3.4 Code
4 Results and Discussion
4.1 Replicability Study
4.2 Impact of Input Features
4.3 Training Time
4.4 Precision@95%recall
5 Conclusions
References
Improving Query Representations for Dense Retrieval with Pseudo Relevance Feedback: A Reproducibility Study
1 Introduction
2 Related Work
3 Improving Query Representations for Dense Retrievers with Pseudo Relevance Feedback
4 Experimental Settings
4.1 Datasets
4.2 Models
4.3 Inference and Training
4.4 Evaluation Metrics
4.5 Research Questions
5 Results and Analysis
5.1 RQ1: Reproduce ANCE-PRF Inference
5.2 RQ2: Replicate ANCE-PRF Training
5.3 RQ3: Generalisability of ANCE-PRF Beyond ANCE
6 Conclusion
References
Another Look at DPR: Reproduction of Training and Replication of Retrieval
1 Introduction
2 Methods
2.1 Retriever
2.2 Reader
2.3 Final Evidence Fusion
3 Experimental Setup
4 Results
4.1 Reproduction of Training
4.2 Replication of Retrieval
4.3 Replication of End-to-End QA
5 Conclusion
References
Reproducing Personalised Session Search Over the AOL Query Log
1 Introduction
2 Background
3 Reconstructing the AOL Document Corpus
4 Comparing AOLIA with AOL17
5 Reproduction and Replication
5.1 Methods
5.2 Experimental Settings
5.3 Results
6 Limitations
7 Conclusions
References
Revisiting Popularity and Demographic Biases in Recommender Evaluation and Effectiveness
1 Introduction
2 Related Work
3 Demographics and Popularity
4 Method
4.1 Datasets
4.2 Model
4.3 Experiment Protocol
5 Results
5.1 Impact on Age
5.2 Impact on Gender
5.3 Impact on Country
6 Discussion and Conclusion
References
Squeezing Water from a Stone: A Bag of Tricks for Further Improving Cross-Encoder Effectiveness for Reranking
1 Introduction
2 Related Work
2.1 Cross-Encoders
2.2 Bi-Encoders
2.3 Hard Negatives
2.4 Pretrained Transformers for Cross-Encoders
3 Loss Functions
3.1 Cross Entropy and Hinge Loss
3.2 Localized Contrastive Estimation
4 Experimental Setup
4.1 Data
4.2 Training and Inference
5 Results and Discussion
5.1 Loss Functions
5.2 In-distributional Training Example and Hard Negative
5.3 LCE Group Size
6 Conclusion
References
An Evaluation Study of Generative Adversarial Networks for Collaborative Filtering
1 Introduction
2 Collaborative Filtering Generative Adversarial Networks
3 CFGAN Theoretical and Methodological Questions
3.1 Real Profiles as Condition Vectors
3.2 No Random Noise
3.3 Methodological Questions
4 Experimental Methodology
4.1 Methodology for the Replicability of CFGAN
4.2 Methodology for the Reproducibility of CFGAN
5 Experiments Results and Discussion
5.1 RQ1: CFGAN Replicability and Numerical Stability
5.2 RQ2: Impact of Theoretical and Methodological Concerns
5.3 RQ3: Reproducibility Evaluation Against Properly Tuned Baselines
6 Conclusions
References
Seed-Driven Document Ranking for Systematic Reviews: A Reproducibility Study
1 Introduction
2 Replicating SDR
2.1 Document Representation
2.2 Term Weighting
2.3 Document Scoring
2.4 Multi-SDR
3 Experimental Setup
3.1 Datasets
3.2 Baselines
3.3 Evaluation Measures
3.4 Document Pre-processing
4 Results
4.1 Generalisability of SDR
4.2 Effect of Multiple Seed Studies
4.3 Variability of Seed Studies on Effectiveness
5 Related Work
6 Conclusions
References
Author Index

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