Advances in Information Retrieval : 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part III

• Autore: Goharian Nazli
• Pubblicazione: Cham : , : Springer, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (528 pages)
• Disciplina: 025.524
• Altri autori: TonellottoNicola HeYulan LipaniAldo McDonaldGraham MacdonaldCraig OunisIadh
• Nota di contenuto: Intro -- Preface -- Organization -- Contents - Part III -- Full Papers -- Knowledge Graph Cross-View Contrastive Learning for Recommendation -- 1 Introduction -- 2 Related Work -- 3 Model Architecture -- 3.1 Problem Formulation -- 3.2 Local-Level Learning -- 3.3 Global-Level Learning -- 3.4 Cross-View Contrastive Learning -- 4 Experiments -- 4.1 Datasets and Evaluation Protocol -- 4.2 Baselines -- 4.3 Performance Comparison with Baselines (RQ1) -- 4.4 Ablation Study (RQ2) -- 4.5 Sensitivity Analysis (RQ3) -- 5 Conclusions -- References -- Mu2STS: A Multitask Multimodal Sarcasm-Humor-Differential Teacher-Student Model for Sarcastic Meme Detection -- 1 Introduction -- 2 Related Works -- 3 Meme Corpus Creation -- 4 Methodology -- 4.1 Problem Formulation -- 4.2 Encoding of Meme -- 4.3 Multimodal Multisegment Multihead Fusion with Cross-Modal Understanding (M3F-CmU) Module -- 4.4 Humor-Aware Sarcasm Synced Teacher Training (HuS-STT) Module -- 4.5 Sarcasm-Illuminator Student Model Training (SaI-SMT) Module -- 5 Results and Analysis -- 5.1 Experimental Details -- 5.2 Comparison with Baselines -- 5.3 Ablation Study -- 5.4 Detailed Analysis -- 5.5 Cross-Lingual Generalization -- 5.6 Comparison with the State-of-the-Art (SOTA) Models -- 6 Error Analysis and Limitations -- 7 Conclusion and Future Work -- References -- Robustness in Fairness Against Edge-Level Perturbations in GNN-Based Recommendation -- 1 Introduction -- 2 Related Work -- 2.1 Attacks and Robustness in Recommendation -- 2.2 Fairness in Recommendation -- 2.3 Robustness and Beyond-Accuracy Aspects -- 3 Methodology -- 3.1 Perturbation Task in Graph-Based Recommendation -- 3.2 Graph Perturbation Mechanism -- 3.3 Fairness Notion and Operationalization -- 4 Experimental Evaluation -- 4.1 Evaluation Setting -- 4.2 RQ1: Impact on Robustness in Fairness. ; 4.3 RQ2: Robustness in Fairness Under Incremental Perturbations -- 4.4 RQ3: Edge Perturbations Influence on Groups -- 5 Conclusions -- References -- Is Google Getting Worse? A Longitudinal Investigation of SEO Spam in Search Engines -- 1 Introduction -- 2 Related Work -- 3 Data and Feature Extraction -- 4 SEO Spam in Product Reviews -- 5 Temporal Analysis of Product Reviews -- 6 Conclusion -- References -- GLAD: Graph-Based Long-Term Attentive Dynamic Memory for Sequential Recommendation -- 1 Introduction -- 2 Methodology -- 2.1 Interaction Sequence Encoder -- 2.2 Dynamic Graph Based Memory -- 2.3 Output Gating -- 2.4 Attentive Reading of Graph Memory -- 2.5 End-to-End Training -- 3 Related Work -- 4 Experiments -- 4.1 Discussion -- 5 Conclusion -- References -- Effective Adhoc Retrieval Through Traversal of a Query-Document Graph -- 1 Introduction -- 2 Related Work -- 3 Query-Document Graph -- 3.1 Query Population -- 3.2 Ranking Neighbours -- 4 QDG in an Adaptive Retrieval Framework -- 4.1 Reverted Adaptive Retrieval -- 4.2 Resource Selection -- 5 Experiments -- 5.1 Experimental Setup -- 5.2 Results -- 6 Qualitative Analysis -- 7 Conclusions -- References -- How to Forget Clients in Federated Online Learning to Rank? -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Preliminary -- 3.2 Unlearning in FOLTR -- 3.3 Efficiency Analysis -- 3.4 Evaluating Unlearning -- 4 Experimental Setup -- 5 Results and Analysis -- 5.1 Validation of Evaluation Methodology -- 5.2 Effectiveness of Unlearning -- 5.3 Hyper-parameters Analysis -- 6 Conclusion -- References -- An Adaptive Feature Selection Method for Learning-to-Enumerate Problem -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 4 Experiments -- 4.1 Experimental Result -- 4.2 Analysis on Why AdaFeaSE Works -- 4.3 Lasso with Initial Weight Values Being 1 -- 4.4 Scalability of the Algorithm. ; 5 Conclusions -- References -- A Transformer-Based Object-Centric Approach for Date Estimation of Historical Photographs -- 1 Introduction -- 2 Related Work -- 3 DEW-B Dataset -- 4 Method -- 4.1 Single Image Date Estimation Model -- 4.2 Leveraging Object Detection for Date Estimation -- 4.3 DEXPERT Architecture -- 5 Experiments -- 6 Conclusions -- A Implementation details -- References -- Shallow Cross-Encoders for Low-Latency Retrieval -- 1 Introduction -- 2 Efficiency/Effectiveness Tradeoffs in Cross-Encoders -- 3 Training Shallow Cross-Encoders with gBCE -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 RQ1. Efficiency/Effectiveness Tradeoffs -- 4.3 RQ2. Effect of the Training Scheme -- 4.4 RQ3. CPU Inference -- 5 Conclusion -- A Effect of gBCE Training Scheme on Tiny BERT-Based Cross-Encoder on the MS MARCO Dev Set -- References -- Asking Questions Framework for Oral History Archives -- 1 Introduction -- 2 Speech Recognition for Oral Archives -- 3 Asking Questions Framework -- 3.1 Asking Questions Model -- 3.2 Semantic Continuity Model -- 4 Experimental Evaluation -- 4.1 Semantic Continuity Model Evaluation -- 4.2 AQ Models Comparison -- 5 Asking Questions Demonstrator -- 6 Conclusion and Future Work -- References -- Improved Learned Sparse Retrieval with Corpus-Specific Vocabularies -- 1 Introduction -- 2 Background and Related Work -- 3 Corpus-Specific Vocabularies -- 3.1 Vocabulary Selection -- 3.2 Pre-training Objectives -- 3.3 Sparse Retrieval Models -- 3.4 Document Expansion -- 3.5 Distillation-Based Training -- 4 Experiments -- 4.1 Setup -- 4.2 Vocabulary Selection and Index Statistics -- 4.3 Retrieval Quality -- 4.4 Query Latency -- 4.5 Pre-training Cost and Model Size -- 5 Conclusion and Future Work -- References -- Interactive Topic Tagging in Community Question Answering Platforms -- 1 Introduction -- 2 Related Work. ; 3 Proposed Method -- 3.1 Problem Definition -- 3.2 Question and Tag Embedding -- 3.3 Question Tagging Model -- 3.4 Feedback-Aware Question Tagging -- 4 Experiments -- 4.1 Dataset -- 4.2 Baselines -- 4.3 Evaluation Strategy -- 4.4 Results and Findings -- 5 Concluding Remarks -- References -- Yes, This Is What I Was Looking For! Towards Multi-modal Medical Consultation Concern Summary Generation -- 1 Introduction -- 2 Related Works -- 3 Dataset -- 3.1 Data Collection and Annotation -- 3.2 Qualitative Aspects -- 4 Methodology -- 4.1 Multi-modal Feature Extraction -- 4.2 Contextualized M-Modality Fusion -- 4.3 MMCS Generation -- 4.4 Experimental Details -- 5 Result and Discussion -- 5.1 Experimental Results -- 5.2 Findings to Research Questions -- 6 Analysis -- 7 Conclusion -- 8 Ethical Consideration -- References -- Mitigating Data Sparsity via Neuro-Symbolic Knowledge Transfer -- 1 Introduction -- 2 Related Works -- 3 Background -- 3.1 Notation -- 3.2 Matrix Factorization -- 3.3 Factorization Machine -- 3.4 Logic Tensor Networks -- 4 Method -- 4.1 Real Logic Knowledge Base -- 4.2 Grounding of Symbols -- 4.3 Learning of the LTN -- 5 Experiments -- 5.1 Datasets -- 5.2 Experimental Setting -- 5.3 Training Details -- 6 Results -- 7 Conclusions and Future Works -- References -- InDi: Informative and Diverse Sampling for Dense Retrieval -- 1 Introduction -- 2 Preliminaries and Notation -- 3 Methods -- 3.1 Informative and Diverse Sampling -- 3.2 In-Batch Deduplication -- 4 Experimental Setup -- 5 Results -- 5.1 Main Results -- 5.2 Fine-Grained Topical Understanding -- 5.3 Additional Dataset -- 5.4 Diversity and Informativeness Importance -- 5.5 Diversity and Informativeness Measures -- 5.6 Ablation -- 5.7 Cross Encoder Filtering with InDi -- 5.8 Computational Surplus -- 6 Related Work -- 6.1 Retrieval -- 6.2 Negative Selection for Dense Retrieval. ; 6.3 Active Learning -- 7 Conclusions -- References -- Short Papers -- Enhancing Legal Named Entity Recognition Using RoBERTa-GCN with CRF: A Nuanced Approach for Fine-Grained Entity Recognition -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Methodology -- 5 Experimental Setup -- 6 Results -- 7 Conclusion -- References -- A Novel Multi-Stage Prompting Approach for Language Agnostic MCQ Generation Using GPT -- 1 Introduction and Background -- 2 Method -- 3 Experiments -- 4 Conclusion and Future Work -- References -- An Adaptive Framework of Geographical Group-Specific Network on O2O Recommendation -- 1 Introduction -- 2 Method -- 2.1 Framework -- 2.2 Implementation of Group-Specification -- 2.3 Algorithm -- 3 Experiment -- 3.1 Experimental Configurations -- 3.2 Offline Experiment and Sensitivity Analysis -- 3.3 Online A/B Test and Ablation Test -- 4 Conclusion -- References -- A Study on Hierarchical Text Classification as a Seq2seq Task -- 1 Introduction -- 2 Analysis Framework -- 2.1 Sequence Modeling -- 2.2 Decoding Strategies -- 2.3 Proposed Metrics -- 3 Experiment and Datasets -- 3.1 Datasets and Implementation Details -- 3.2 Results -- 4 Conclusion -- References -- Improving the Robustness of Dense Retrievers Against Typos via Multi-Positive Contrastive Learning -- 1 Introduction -- 2 Methodology -- 2.1 Dense Retriever with Self-supervised Contrastive Learning -- 2.2 Dense Retriever with Dual Learning -- 2.3 Dense Retriever with Dual Learning and Self-Teaching -- 3 Experimental Setup -- 4 Results -- 5 Conclusions -- References -- Learning-to-Rank with Nested Feedback -- 1 Introduction and Related Work -- 2 Modeling Nested Ranking Signals -- 3 Experimental Validation -- 3.1 Offline Training and Experiment Results -- 3.2 Online A/B Experimentation -- 4 Discussion and Future Work -- References. ; MMCRec: Towards Multi-modal Generative AI in Conversational Recommendation.
• Titolo autorizzato: Advances in Information Retrieval
• ISBN: 3-031-56063-9
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996589544003316
• Lo trovi qui: Univ. di Salerno
• Serie: Lecture Notes in Computer Science Series