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Titlebook: Advances in Information Retrieval; 41st European Confer Leif Azzopardi,Benno Stein,Djoerd Hiemstra Conference proceedings 2019 Springer Nat

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发表于 2025-3-21 19:53:32 | 显示全部楼层 |阅读模式
期刊全称Advances in Information Retrieval
期刊简称41st European Confer
影响因子2023Leif Azzopardi,Benno Stein,Djoerd Hiemstra
视频videohttp://file.papertrans.cn/149/148355/148355.mp4
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Advances in Information Retrieval; 41st European Confer Leif Azzopardi,Benno Stein,Djoerd Hiemstra Conference proceedings 2019 Springer Nat
影响因子.This two-volume set LNCS 11437 and 11438 constitutes the refereed proceedings of the 41st European Conference on IR Research, ECIR 2019, held in Cologne, Germany, in April 2019.. The 48 full papers presented together with 2 keynote papers, 44 short papers, 8 demonstration papers, 8 invited CLEF papers, 11 doctoral consortium papers, 4 workshop papers, and 4 tutorials were carefully reviewed and selected from 365 submissions. They were organized in topical sections named: Modeling Relations; Classification and Search; Recommender Systems; Graphs; Query Analytics; Representation; Reproducibility (Systems); Reproducibility (Application); Neural IR; Cross Lingual IR; QA and Conversational Search; Topic Modeling; Metrics; Image IR; Short Papers; Demonstration Papers; CLEF Organizers Lab Track; Doctoral Consortium Papers; Workshops; and Tutorials..
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0302-9743 oducibility (Systems); Reproducibility (Application); Neural IR; Cross Lingual IR; QA and Conversational Search; Topic Modeling; Metrics; Image IR; Short Papers; Demonstration Papers; CLEF Organizers Lab Track; Doctoral Consortium Papers; Workshops; and Tutorials..978-3-030-15718-0978-3-030-15719-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Personal Experiences of Six Patients,ults on the New York Times Annotated corpus with ROUGE-L F1-score 24.84 and ROUGE-2 F1-score 13.48. We also present the new RIA corpus and reach ROUGE-L F1-score 36.81 and ROUGE-2 F1-score 22.15 on it.
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https://doi.org/10.1007/978-3-031-12863-9oles - Trajector, Landmark and Spatial Indicator. Our approach outperforms the task submission results and other state-of-the-art results on these datasets. We also include a discussion on the explainability of our model.
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Joannes Rosa and His Commentary on the ,,ur experiments on the human-generated abstractive sentence compression datasets and evaluate our system on several newly proposed Machine Translation (.) evaluation metrics. Our experiments demonstrate that the methods bring significant improvements over the state-of-the-art methods across different metrics.
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The , in the Renaissance: A General Survey,nd help further boost the tagger’s performance. Our experiments with this architecture have shown to improve state-of-the-art F1 score on 3 widely used biomedical corpora for NER. We also perform analysis to understand the specific cases where our contextualized model is superior to a strong baseline.
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