An Empirical Study of Writing Feedback Analysis of Non-English Majors in China with Natural Language Processing Technologies

Author(s):  
Ming Liu ◽  
Weiwei Xu ◽  
Qiuxia Ran
Author(s):  
Yinjun Hu ◽  
Mengmeng Chen ◽  
Qian Wang ◽  
Yue Zhu ◽  
Bei Wang ◽  
...  

Abstract [Background] On January 7, 2020, the novel coronavirus named "COVID-19" aroused worldwide concern was identified by Chinese scientists. Many related research works were developed for the emerging, rapidly evolving situation of this epidemic. This study aimed to analyze the research literatures on SARS, MERS and COVID-19 to retrieve important information for virologists, epidemiologist and policy decision makers. [Methods] In this study, we collected data from multi data sources and compared bibliometrics indices among COVID-19, Severe Acute Respiratory Syndrome (SARS), and Middle East Respiratory Syndrome (MERS) up to March 25, 2020. In purpose to extract data in corresponding quantity and scale, the volume of search results will be balance with the limitation of publication years. For further analysis, we extracted 1,480 documents from 1,671 candidates with Natural Language Processing technologies. [Results] In total, 13,945 research literatures of 7 datasets were selected for analysis. Unlike other topics, research passion on epidemic may reach its peak at the first year the outbreak happens. The document type distribution of SARS, MERS and COVID-19 are nearly the same (less than 6 point difference for each type), however, there were notable growth in the research qualities during these three epidemics (3.68, 6.63 and 11.35 for Field-Weighted Citation Impact scores). Asian countries has less international collaboration (less than 35.1\%) than the Occident (more than 49.5\%), which should be noticed as same as research itself. [Conclusions] We found that research passion on epidemics may always reach its peak at the first year after outburst, however, the peak of research on MERS appeared at the third year because of its outburst of reproduction in 2015. For the research quality, although we did better in research qualities than before especially on COVID-19, research on epidemics not started from our own country should not be looked down. Another important effective strategy for enhancing epidemic prevention for China and other Asian countries is to continue strengthening international collaboration.


2018 ◽  
Vol 11 (3) ◽  
pp. 1-25
Author(s):  
Leonel Figueiredo de Alencar ◽  
Bruno Cuconato ◽  
Alexandre Rademaker

ABSTRACT: One of the prerequisites for many natural language processing technologies is the availability of large lexical resources. This paper reports on MorphoBr, an ongoing project aiming at building a comprehensive full-form lexicon for morphological analysis of Portuguese. A first version of the resource is already freely available online under an open source, free software license. MorphoBr combines analogous free resources, correcting several thousand errors and gaps, and systematically adding new entries. In comparison to the integrated resources, lexical entries in MorphoBr follow a more user-friendly format, which can be straightforwardly compiled into finite-state transducers for morphological analysis, e.g. in the context of syntactic parsing with a grammar in the LFG formalism using the XLE system. MorphoBr results from a combination of computational techniques. Errors and the more obvious gaps in the integrated resources were automatically corrected with scripts. However, MorphoBr's main contribution is the expansion in the inventory of nouns and adjectives. This was carried out by systematically modeling diminutive formation in the paradigm of finite-state morphology. This allowed MorphoBr to significantly outperform analogous resources in the coverage of diminutives. The first evaluation results show MorphoBr to be a promising initiative which will directly contribute to the development of more robust natural language processing tools and applications which depend on wide-coverage morphological analysis.KEYWORDS: computational linguistics; natural language processing; morphological analysis; full-form lexicon; diminutive formation. RESUMO: Um dos pré-requisitos para muitas tecnologias de processamento de linguagem natural é a disponibilidade de vastos recursos lexicais. Este artigo trata do MorphoBr, um projeto em desenvolvimento voltado para a construção de um léxico de formas plenas abrangente para a análise morfológica do português. Uma primeira versão do recurso já está disponível gratuitamente on-line sob uma licença de software livre e de código aberto. MorphoBr combina recursos livres análogos, corrigindo vários milhares de erros e lacunas. Em comparação com os recursos integrados, as entradas lexicais do MorphoBr seguem um formato mais amigável, o qual pode ser compilado diretamente em transdutores de estados finitos para análise morfológica, por exemplo, no contexto do parsing sintático com uma gramática no formalismo da LFG usando o sistema XLE. MorphoBr resulta de uma combinação de técnicas computacionais. Erros e lacunas mais óbvias nos recursos integrados foram automaticamente corrigidos com scripts. No entanto, a principal contribuição de MorphoBr é a expansão no inventário de substantivos e adjetivos. Isso foi alcançado pela modelação sistemática da formação de diminutivos no paradigma da morfologia de estados finitos. Isso possibilitou a MorphoBr superar de forma significativa recursos análogos na cobertura de diminutivos. Os primeiros resultados de avaliação mostram que o MorphoBr constitui uma iniciativa promissora que contribuirá de forma direta para conferir robustez a ferramentas e aplicações de processamento de linguagem natural que dependem de análise morfológica de ampla cobertura.PALAVRAS-CHAVE: linguística computacional; processamento de linguagem natural; análise morfológica; léxico de formas plenas; formação de diminutivos.


2018 ◽  
Vol 12 (02) ◽  
pp. 237-260
Author(s):  
Weifeng Xu ◽  
Dianxiang Xu ◽  
Abdulrahman Alatawi ◽  
Omar El Ariss ◽  
Yunkai Liu

Unigram is a fundamental element of [Formula: see text]-gram in natural language processing. However, unigrams collected from a natural language corpus are unsuitable for solving problems in the domain of computer programming languages. In this paper, we analyze the properties of unigrams collected from an ultra-large source code repository. Specifically, we have collected 1.01 billion unigrams from 0.7 million open source projects hosted at GitHub.com. By analyzing these unigrams, we have discovered statistical properties regarding (1) how developers name variables, methods, and classes, and (2) how developers choose abbreviations. We describe a probabilistic model which relies on these properties for solving a well-known problem in source code analysis: how to expand a given abbreviation to its original indented word. Our empirical study shows that using the unigrams extracted from source code repository outperforms the using of the natural language corpus by 21% when solving the domain specific problems.


2002 ◽  
Vol 9 (5) ◽  
pp. 131-148
Author(s):  
HIROMI ITOH OZAKU ◽  
MASAO UTIYAMA ◽  
MASAKI MURATA ◽  
KIYOTAKA UCHIMOTO ◽  
HITOSHI ISAHARA

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