The brain capacity of human ancestors underwent two phase transitions, which were supported by preadaptations during the animal protolanguage period, resulting in the emergence of human language. The transitions were (1) the emergence of the primate ...
With the increase in the amount of text information in different real-life applications, automatic text-summarization systems become more predominant in extracting relevant information. In the current study, we formulated the problem of extractive te...
BACKGROUND: There is an increasing amount of unstructured medical data that can be analysed for different purposes. However, information extraction from free text data may be particularly inefficient in the presence of spelling errors. Existing appro...
Comics are complex documents whose reception engages cognitive processes such as scene perception, language processing, and narrative understanding. Possibly because of their complexity, they have rarely been studied in cognitive science. Modeling th...
Clinical named entity recognition (CNER), which intends to automatically detect clinical entities in electronic health record (EHR), is a committed step for further clinical text mining. Recently, more and more deep learning models are used to Chines...
Named entity recognition is a fundamental and crucial task in medical natural language processing problems. In medical fields, Chinese clinical named entity recognition identifies boundaries and types of medical entities from unstructured text such a...
This paper describes the process of adapting the Stanford Coreference resolution module to the Basque language, taking into account the characteristics of the language. The module has been integrated in a linguistic analysis pipeline obtaining an end...
Neural networks : the official journal of the International Neural Network Society
Aug 6, 2019
Learning document representation is important in applying machine learning algorithms for sentiment analysis. Distributed representation learning models of words and documents, one of neural language models, have overcome some limits of vector space ...
Computational intelligence and neuroscience
Aug 1, 2019
We explored several approaches to incorporate context information in the deep learning framework for text classification, including designing different attention mechanisms based on different neural network and extracting some additional features fro...
BACKGROUND: Manual chart review is labor-intensive and requires specialized knowledge possessed by highly trained medical professionals. The cost and infrastructure challenges required to implement this is prohibitive for most hospitals. Natural lang...
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