paper-with-me

홈 › Papers

Systèmes du LIA à DEFT'13

2017-02-21 · Xavier Bost, Ilaria Brunetti, Luis Adrián Cabrera-Diego, Jean-Valère Cossu, Andréa Linhares, Mohamed Morchid, Juan-Manuel Torres-Moreno, Marc El-Bèze, Richard Dufour

The 2013 D\'efi de Fouille de Textes (DEFT) campaign is interested in two types of language analysis tasks, the document classification and the information extraction in the specialized domain of cuisine recipes. We present the systems that the LIA has used in DEFT 2013. Our systems show interesting results, even though the complexity of the proposed tasks.

📄 PDF Abstract BibTeX arXiv:1702.06478

Code (0)

등록된 구현이 없습니다.

Tasks

Document ClassificationGeneral Classification

Similar Papers 제목 키워드 기반

Concat\'enation de r\'eseaux de neurones pour la classification de tweets, DEFT2018 (Concatenation of neural networks for tweets classification, DEFT2018 )

2018-05-01 · JEPTALNRECITAL 2018 5 · Damien Sileo, Tim Van De Cruys, Philippe Muller, Camille Pradel

Nous pr{\'e}sentons le syst{\`e}me utilis{\'e} par l{'}{\'e}quipe Melodi/Synapse D{\'e}veloppement dans la comp{\'e}tition DEFT2018 portant sur la classification de th{\'e}matique ou de sentiments de tweets en fran{\c{c}…

ClassificationGeneral Classification

CLaC @ DEFT 2018: Sentiment analysis of tweets on transport from \^Ile-de-France

2018-05-01 · JEPTALNRECITAL 2018 5 · Simon Jacques, Farhood Farahnak, Leila Kosseim

CLaC @ DEFT 2018: Analysis of tweets on transport on the {\^I}le-de-France This paper describes the system deployed by the CLaC lab at Concordia University in Montreal for the DEFT 2018 shared task. The competition consi…

Sentiment AnalysisTask 2

DOING@DEFT : utilisation de lexiques pour une classification efficace de cas cliniques (In this paper, we present our participation to the DEFT 2021 task 1)

2021-06-01 · JEP/TALN/RECITAL 2021 6 · Nicolas Hiot, Anne-Lyse Minard, Flora Badin

Nous présentons dans cet article notre participation à la tâche 1 de la campagne d’évaluation francophone DEFT 2021, sur l’identification du profil clinique du patient. Nous proposons une méthode évolutive et efficace en…

DeFTA: A Plug-and-Play Decentralized Replacement for FedAvg

2022-04-06 · Yuhao Zhou, Minjia Shi, Yuxin Tian, Qing Ye 외

Federated learning (FL) is identified as a crucial enabler for large-scale distributed machine learning (ML) without the need for local raw dataset sharing, substantially reducing privacy concerns and alleviating the iso…

Federated Learning

Aprentissage non-supervis\'e pour l'appariement et l'\'etiquetage de cas cliniques en fran\ccais - DEFT2019 (Unsupervised learning for matching and labelling of french clincal cases - DEFT2019 )

2019-07-01 · JEPTALNRECITAL 2019 7 · Damien Sileo, Tim Van De Cruys, Philippe Muller, Camille Pradel

Nous pr{\'e}sentons le syst{\`e}me utilis{\'e} par l{'}{\'e}quipe Synapse/IRIT dans la comp{\'e}tition DEFT2019 portant sur deux t{\^a}ches li{\'e}es {\`a} des cas cliniques r{\'e}dig{\'e}s en fran{\c{c}}ais : l{'}une d{…