Results 51 to 60 of about 3,494,638 (328)
GoEmotions: A Dataset of Fine-Grained Emotions [PDF]
Annual Meeting of the Association for Computational Linguistics, 2020 Understanding emotion expressed in language has a wide range of applications, from building empathetic chatbots to detecting harmful online behavior.
Dorottya Demszky +5 more
semanticscholar +1 more source
About Evaluation of F1 Score for RECENT Relation Extraction System
, 2023 This document contains a discussion of the F1 score evaluation used in the article 'Relation Classification with Entity Type Restriction' by Shengfei Lyu, Huanhuan Chen published on Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021.
openaire +2 more sources
End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures [PDF]
Annual Meeting of the Association for Computational Linguistics, 2016 We present a novel end-to-end neural model to extract entities and relations between them. Our recurrent neural network based model captures both word sequence and dependency tree substructure information by stacking bidirectional tree-structured LSTM ...
Makoto Miwa, Mohit Bansal
semanticscholar +1 more source
Transfer learning and sentence level features for named entity recognition on tweets [PDF]
, 2017 We present our system for the WNUT 2017 Named Entity Recognition challenge on Twitter data. We describe two modifications of a basic neural network architecture for sequence tagging.
Cieliebak, Mark, von Däniken, Pius
core +1 more source
Prediction of the Fundus Tessellation Severity With Machine Learning Methods
Frontiers in Medicine, 2022 PurposeTo predict the fundus tessellation (FT) severity with machine learning methods.MethodsA population-based cross-sectional study with 3,468 individuals (mean age of 64.6 ± 9.8 years) based on Beijing Eye Study 2011.
Lei Shao +11 more
doaj +1 more source
chrF: character n-gram F-score for automatic MT evaluation
WMT@EMNLP, 2015 We propose the use of character n-gram F-score for automatic evaluation of machine translation output. Character ngrams have already been used as a part of more complex metrics, but their individual potential has not been investigated yet.
Maja Popovic
semanticscholar +1 more source
CoQA: A Conversational Question Answering Challenge [PDF]
Transactions of the Association for Computational Linguistics, 2018 Humans gather information through conversations involving a series of interconnected questions and answers. For machines to assist in information gathering, it is therefore essential to enable them to answer conversational questions. We introduce CoQA, a
Siva Reddy +2 more
semanticscholar +1 more source
Deep learning for extracting protein-protein interactions from biomedical literature
, 2017 State-of-the-art methods for protein-protein interaction (PPI) extraction are primarily feature-based or kernel-based by leveraging lexical and syntactic information.
Lu, Zhiyong, Peng, Yifan
core +1 more source
Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods [PDF]
North American Chapter of the Association for Computational Linguistics, 2018 In this paper, we introduce a new benchmark for co-reference resolution focused on gender bias, WinoBias. Our corpus contains Winograd-schema style sentences with entities corresponding to people referred by their occupation (e.g.
Jieyu Zhao +4 more
semanticscholar +1 more source
Applied Computer ScienceThis study aims to evaluate and compare five algorithms in diabetes detection, namely Flower Pollination Neural Network (FPNN), Particle Swarm Optimization Neural Network (PSONN), Bat Artificial Neural Network (BANN), Stochastic Gradient Descent (SGD ...
Yulianto Triwahyuadi POLLY +5 more
doaj +1 more source