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DeLFT and entity-fishing : Tools for CLEF HIPE 2020 Shared Task
DeLFT and entity-fishing : Tools for CLEF HIPE 2020 Shared Task
International audience; This article presents an overview of approaches and results during our participation in the CLEF HIPE 2020 NERC-COARSE-LIT and EL-ONLY tasks for English and French. For these two tasks, we use two systems: 1) DeLFT, a Deep Learning framework for text processing; 2) entity-fishing, generic named entity recognition and disambiguation service deployed in the technical framework of INRIA.
Entity recognition, Entity linking, [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], Machine learning, [INFO.INFO-DL]Computer Science [cs]/Digital Libraries [cs.DL], Deep learning, [INFO.INFO-DL] Computer Science [cs]/Digital Libraries [cs.DL], [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
Entity recognition, Entity linking, [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], Machine learning, [INFO.INFO-DL]Computer Science [cs]/Digital Libraries [cs.DL], Deep learning, [INFO.INFO-DL] Computer Science [cs]/Digital Libraries [cs.DL], [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!- French Institute for Research in Computer Science and Automation France
- Université Paris Diderot France
- INRIA
- National Institute for Research in Digital Science and Technology (INRIA), France France
- National Institute for Research in Computer Science and Control France
- INRIX (United Kingdom) United Kingdom
- Inpria (United States) United States
- INRIA
- INRIA RENNES - BRETAGNE ATLANTIQUE
- INRAE France
- Inria
- INRAT
- INRAE
- INIA Spain
- INIA
- INRA
- INRIA - Rhône-Alpes
- INRAA
- INRAD United States
- INRAD (United States) United States
- INRIA
- INRIA -(INRIA CENTRE SOPHIA-ANTIPOLIS MEDITERRANNEE)
- INRIA -(INRIA CENTRE SOPHIA-ANTIPOLIS)
- Invicro (United States) United States
- INRIA France
- INRIA INRIA
- Inria Grenoble Rhône-Alpes
- INRA
- INRIA France
- INRIA France
- INRA France
International audience; This article presents an overview of approaches and results during our participation in the CLEF HIPE 2020 NERC-COARSE-LIT and EL-ONLY tasks for English and French. For these two tasks, we use two systems: 1) DeLFT, a Deep Learning framework for text processing; 2) entity-fishing, generic named entity recognition and disambiguation service deployed in the technical framework of INRIA.