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StaResGRU-CNN with CMedLMs: a stacked residual GRU-CNN with pre-trained biomedical language models for predictive intelligence
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Machine Learning approaches for Topic and Sentiment Analysis in multilingual opinions and low-resource languages: From English to Guarani
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Brazilian Portuguese verbal databases ; Bases lexicais verbais do português brasileiro
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In: Domínios de Lingu@gem; Ahead of Print ; 1980-5799 (2022)
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Representation learning of natural language and its application to language understanding and generation
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Detecting weak and strong Islamophobic hate speech on social media
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An Empirical Study of Factors Affecting Language-Independent Models
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Abstract:
Scaling existing applications and solutions to multiple human languages has traditionally proven to be difficult, mainly due to the language-dependent nature of preprocessing and feature engineering techniques employed in traditional approaches. In this work, we empirically investigate the factors affecting language-independent models built with multilingual representations, including task type, language set and data resource. On two most representative Natural Language Processing tasks --- sentence classification and sequence labeling, we show that language-independent models can be comparable to or even outperforms the models trained using monolingual data, and they are generally more effective on sentence classification. We experiment language-independent models with many different languages and show that they are more suitable for typologically similar languages. We also explore the effects of different data sizes when training and testing language-independent models, and demonstrate that they are not only suitable for high-resource languages, but also very effective in low-resource languages.
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Keyword:
Analytics Technologies for Industry Platforms; Business Intelligence; Case studies of Artificial Intelligence; case study; multilingual ai; natural language processing; transfer learning
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URL: https://doi.org/10.24251/HICSS.2022.149 http://hdl.handle.net/10125/79481
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Using Geolocated Text to Quantify Location in Real Estate Appraisal
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TSM: Measuring the Enticement of Honeyfiles with Natural Language Processing
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Modeling Phishing Decision using Instance Based Learning and Natural Language Processing
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What to prioritize? Natural Language Processing for the Development of a Modern Bug Tracking Solution in Hardware Development
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Eine agentenbasierte Architektur für Programmierung mit gesprochener Sprache
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Um método adaptativo para análise sintática do Português Brasileiro. ; An adaptive method for syntactic analysis of Brazilian Portuguese.
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Padovani, Djalma. - : Biblioteca Digital de Teses e Dissertações da USP, 2022. : Universidade de São Paulo, 2022. : Escola Politécnica, 2022
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Multitask Pointer Network for Multi-Representational Parsing
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