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Band 12035

Advances in Information Retrieval 42nd European Conference on IR Research, ECIR 2020, Lisbon, Portugal, April 14–17, 2020, Proceedings, Part I

Aus der Reihe Lecture Notes in Computer Science

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Beschreibung

This two-volume set LNCS 12035 and 12036 constitutes the refereed proceedings of the 42nd European Conference on IR Research, ECIR 2020, held in Lisbon, Portugal, in April 2020.* 

The 55 full papers presented together with 8 reproducibility papers, 46 short papers, 10 demonstration papers, 12 invited...

Beschreibung

This two-volume set LNCS 12035 and 12036 constitutes the refereed proceedings of the 42nd European Conference on IR Research, ECIR 2020, held in Lisbon, Portugal, in April 2020.* 

The 55 full papers presented together with 8 reproducibility papers, 46 short papers, 10 demonstration papers, 12 invited CLEF papers, 7 doctoral consortium papers, 4 workshop papers, and 3 tutorials were carefully reviewed and selected from 457 submissions. They were organized in topical sections named:

Part I: deep learning I; entities; evaluation; recommendation; information extraction; deep learning II; retrieval; multimedia; deep learning III; queries; IR – general; question answering, prediction, and bias; and deep learning IV.

Part II: reproducibility papers; short papers; demonstration papers; CLEF organizers lab track; doctoral consortium papers; workshops; and tutorials.

*Due to the COVID-19 pandemic, this conference was held virtually.

Produktdetails

Einband

Taschenbuch
Erscheinungsdatum

12.04.2020
Abbildungen

XLV, 870 p. 481 illus., 149 illus. in color.
Herausgeber Joemon M. Jose + weitere

Produktdetails

Einband

Taschenbuch
Erscheinungsdatum

12.04.2020
Abbildungen

XLV, 870 p. 481 illus., 149 illus. in color.
Herausgeber
Verlag Springer
Seitenzahl

870
Maße (L/B/H)

23,5/15,5/4,9 cm
Gewicht

1358 g
Auflage

1st ed. 2020
Sprache

Englisch
ISBN

978-3-030-45438-8
Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Advances in Information Retrieval
  • Produktbild: Advances in Information Retrieval

  • Deep Learning I.- Seed-guided Deep Document Clustering.- Improving Knowledge Graph Embedding using Locally and Globally Attentive Relation Paths.- ReadNet: A Hierarchical Transformer Framework for Web Article Readability Analysis.- Variational Recurrent Sequence-to-Sequence Retrieval for Stepwise Illustration.- A Hierarchical Model for Data-to-Text Generation.- Entities.- Context-guided Learning to Rank Entities.- Graph-Embedding Empowered Entity Retrieval.- Learning Advanced Similarities and Training Features for Toponym Interlinking.- Patch-based Identification of Lexical Semantic Relations.- Joint Word and Entity Embeddings for Entity Retrieval from a Knowledge Graph.- Evaluation.- Evaluating the Effectiveness of the Standard Insights Extraction Pipeline for Bantu Languages.- Recommendation.- Axiomatic Analysis of Contact Recommendation Methods in Social Networks: an IR perspective.- Recommending Music Curators: A Neural Style-Aware Approach.- Joint Geographical and Temporal Modeling based on Matrix Factorization for Point-of-Interest Recommendation.- Semantic Modelling of Citation Contexts for Context-aware Citation Recommendation.- TransRev: Modeling Reviews as Translations from Users to Items.- Information Extraction.- Domain-independent Extraction of Scientific Concepts from Research Articles.- Leveraging Schema Labels to Enhance Dataset Search.- Moving from formal towards coherent concept analysis: why, when and how.- Beyond Modelling: Understanding Mental Disorders in Online Social Media.- Deep Learning II.- Learning based Methods for Code Runtime Complexity Prediction.- Inductive Document Network Embedding with Topic-Word Attention.- Multi-components system for automatic Arabic diacritization.- A Mixed Semantic Features Model for Chinese NER with Characters and Words.- VGCN-BERT: Augmenting BERT with Graph Embedding for Text Classification.- Retrieval.- A Computational Approach for Objectively Derived Systematic Review Search Strategies.- You Can Teach an Old Dog New Tricks: Rank Fusion applied to Coordination Level Matching for Ranking in Systematic Reviews.- Counterfactual Online Learning to Rank.- A Framework for Argument Retrieval: Ranking Argument Clusters by Frequency and Specificity.- Relevance Ranking based on Query-Aware Context Analysis.- Multimedia.- Multimodal Entity Linking for Tweets.- MEMIS: Multimodal Emergency Management Information System.- Interactive Learning for Multimedia at Large.- Visual Re-ranking via Adaptive Collaborative Hypergraph Learning for Image Retrieval.- Motion Words: A Text-like Representation of 3D Skeleton Sequences.- Deep Learning III.- Reinforced Rewards Framework for Text Style Transfer.- Recognizing Semantic Relations: Attention-Based Transformers vs. Recurrent Models.- Early detection of rumours on Twitter via stance transfer learning.- Learning to Rank Images with Cross-Modal Graph Convolutions.- Diagnosing BERT with RetrievalHeuristics.- Queries.- Generation of Synthetic Query Auto Completion Logs.- What Can Task Teach Us About Query Reformulations?.- A Regularised Intent Model for Discovering Multiple Intents in E-Commerce Tail Queries.- Utilising Information Foraging Theory for User Interaction with Image Query Auto-Completion.- Using Image Captions and Multitask Learning for Recommending Query Reformulations.- IR – general.- Curriculum Learning Strategies for IR: An Empirical Study on Conversation Response Ranking.- Accelerating Substructure Similarity Search for Formula Retrieval.- Quantum-like Structure in Multidimensional Relevance Judgements.- Question Answering, Prediction, and Bias.- Temporal Latent Space Modeling for Community Prediction.- KvGR: A Graph-Based Interface for Explorative Sequential Question Answering on Heterogeneous Information Sources.- Answering Event-Related Questions over Long-term News Article Archives.- bias goggles - Graph-based Computation of the Bias of Web Domains through the Eyes of Users.- Deep Learning IV.- Biconditional Generative Adversarial Networks for Multiview Learning with Missing Views.- Semantic Path-Based Learning for Review Volume Prediction.- An Attention Model of Customer Expectation to Improve Review Helpfulness Prediction.