The generativity and complexity of human thought stem in large part from the ability to represent relations among concepts and form propositions. The current study reveals how a given object such as rabbit is neurally encoded differently and identifi...
OBJECTIVE: Electronic medical records (EMRs) are increasingly repurposed for activities beyond clinical care, such as to support translational research and public policy analysis. To mitigate privacy risks, healthcare organizations (HCOs) aim to remo...
Neural networks : the official journal of the International Neural Network Society
Mar 16, 2016
It is desirable for robots to be able to linguistically understand human actions during human-robot interactions. Previous research has developed frameworks for encoding human full body motion into model parameters and for classifying motion into spe...
Computational intelligence and neuroscience
Mar 16, 2016
Grounded language acquisition is an important issue, particularly to facilitate human-robot interactions in an intelligent and effective way. The evolutionary and developmental language acquisition are two innovative and important methodologies for t...
BACKGROUND: Coreference resolution is an essential task in information extraction from the published biomedical literature. It supports the discovery of complex information by linking referring expressions such as pronouns and appositives to their re...
Speculations represent uncertainty toward certain facts. In clinical texts, identifying speculations is a critical step of natural language processing (NLP). While it is a nontrivial task in many languages, detecting speculations in Chinese clinical ...
In this paper, we investigate the effect of neighbourhood density (ND) on vocabulary size in a computational model of vocabulary development. A word has a high ND if there are many words phonologically similar to it. High ND words are more easily lea...
The purpose of the study is to examine the effect of subliminal priming in terms of the perception of images influenced by words with positive, negative, and neutral emotional content, through electroencephalograms (EEGs). Participants were instructe...
Long Short Term Memory (LSTM) Recurrent Neural Networks (RNNs) have recently outperformed other state-of-the-art approaches, such as i-vector and Deep Neural Networks (DNNs), in automatic Language Identification (LID), particularly when dealing with ...
Computational intelligence and neuroscience
Jan 21, 2016
The discordance between expressions interpretable by a natural language interface (NLI) system and those answerable by a knowledge base is a critical problem in the field of NLIs. In order to solve this discordance problem, this paper proposes a meth...