Accurately discovering user intents from their written or spoken language plays a critical role
in natural language understanding and automated dialog response. Most existing research …

In order to obtain high quality and large‐scale labelled data for information security
research, we propose a new approach that combines a generative adversarial network with …

Detecting and identifying user intent from text, both written and spoken, plays an important
role in modelling and understand dialogs. Existing research for intent discovery model it as a …

Target-based sentiment analysis (TBSA) is one of the most important NLP research topics
for widespread applications. However, the task is challenging, especially when the targets …

Abstract “Traditional Chinese Medicine (TCM) is a natural, safe, and effective therapy that
has spread and been applied worldwide. The unique TCM diagnosis and treatment system …

Knowledge Graph (KG) contains entities and the relations between entities. Due to its
representation ability, KG has been successfully applied to support many …

Mining large-scale medical entities and entity relationships from electronic medical record
(EMR) is of great significance for the construction of medical knowledge graph, medical …

O tratamento da informação textual torna-se cada vez mais relevante para muitos domínios.
Nesse sentido, uma das primeira tarefas para Extração de Informações a partir de textos é o …

Abstract Traditional Chinese Medicine (TCM) is a natural, safe, and effective therapy that
has spread and been applied worldwide. The unique TCM diagnosis and treatment system …

Recently, neural networks have shown promising results for named entity recognition (NER),
which needs a number of labeled data to for model training. When meeting a new domain …