The three-volume set LNCS 13980, 13981 and 13982 constitutes the refereed proceedings of the 45th European Conference on IR Research, ECIR 2023, held in Dublin, Ireland, during April 2-6, 2023.
The 65 full papers, 41 short papers, 19 demonstration papers, and 12 reproducibility papers, 10 doctoral consortium papers were carefully reviewed and selected from 489 submissions. The accepted papers cover the state of the art in information retrieval focusing on user aspects, system and foundational aspects, machine learning, applications, evaluation, new social and technical challenges, and other topics of direct or indirect relevance to search.
Full Papers.- Self-Supervised Contrastive BERT Fine-tuning for
Fusion-based Reviewed-Item Retrieval.- User Requirement Analysis for a
Recommender System-Based Meeting Assistant.- Auditing Consumer- and
Producer-Fairness in Graph Collaborative Filtering.- Exploiting Graph
Structured Cross-Domain Representation for Multi-Domain Recommendation.-
Injecting the BM25 Score as Text Improves BERT-Based Re-rankers.- Quantifying
Valence and Arousal in Text with Multilingual Pre-trained Transformers.- A
Knowledge Infusion based Multitasking System for Sarcasm Detection in Meme.-
Multilingual Detection of Check-Worthy Claims using World Languages and
Adapter Fusion.- Market-Aware Models for Efficient Cross Market
Recommendation.- TourismNLG: A Multi-lingual Generative Benchmark for the
Tourism Domain.- An Interpretable Knowledge Representation Framework for
Natural Language Processing with Cross-Domain Application.- Graph-based
Recommendation for Sparse and Heterogeneous User Interactions.- Its Just a
Matter of Time: Detecting Depression with Time-Enriched Multimodal
Transformers.- Recommendation Algorithm Based on Deep Light Graph Convolution
Network in Knowledge Graph.- Query Performance Prediction for Neural IR: Are
We There Yet?.- Item Graph Convolutional Collaborative Filtering for
Inductive Recommendations.- CoLISA: Inner Interaction via Contrastive
Learning for Multi-Choice Reading Comprehension.- Viewpoint Diversity in
Search Results.- COILCR: Efficient Semantic Matching in Contextualized Exact
Match Retrieval.- Bootstrapped nDCG Estimation in the Presence of Unjudged
Documents.- Predicting the Listening Contexts of Music Playlists Using
Knowledge Graphs.- Keyword Embeddings for Query Suggestion.- Domain-driven
and Discourse-guided Scientific Summarisation.- Injecting Temporal-aware
Knowledge in Historical Named Entity Recognition.- A Mask-based Logic Rules
Dissemination Method for Sentiment Classifiers.- Contrasting Neural Click
Models and Pointwise IPS Rankers.- Sentence Retrieval for Open-Ended Dialogue
using Dual Contextual Modeling.- Temporal Natural Language Inference:
Evidence-based Evaluation of Temporal Text Validity.- Theoretical Analysis on
the Efficiency of Interleaved Comparisons.- Intention-aware Neural Networks
for Question Paraphrase Identification.- Automatic and Analytical Field
Weighting for Structured Document Retrieval.- An Experimental Study on
Pretraining Transformers from Scratch for IR.- Neural Approaches to
Multilingual Information Retrieval.- CoSPLADE: Contextualizing SPLADE for
Conversational Information Retrieval.- SR-CoMbEr: Heterogeneous Network
Embedding using Community Multi-view Enhanced Graph Convolutional Network for
Automating Systematic Reviews.- Multimodal Inverse Cloze Task for
Knowledge-based Visual Question Answering.- A Transformer-based Framework for
POI-level Social Post Geolocation.- Document-Level Relation Extraction with
Distance-dependent Bias Network and Neighbors Enhanced Loss.- Investigating
Conversational Agent Action in Legal Case Retrieval.- MS-Shift: An Analysis
of MS MARCO Distribution Shifts on Neural Retrieval.- Listwise Explanations
for Ranking Models using Multiple Explainers.- Improving video retrieval
using multilingual knowledge transfer.- Service is good, very good or
excellent? Towards Aspect based Sentiment Intensity Analysis.- Effective
Hierarchical Information Threading using Network Community Detection.- HADA:
A Graph-based Amalgamation Framework in Image-Text Retrieval.
Biežāk uzdotie jautājumi par e-grāmatām