Over the last couple of decades, community question‐answering sites (CQAs) have been a
topic of much academic interest. Scholars have often leveraged traditional machine learning …

Recent years have witnessed a substantial increase in the use of deep learning to solve
various natural language processing (NLP) problems. Early deep learning models were …

Aspect-based sentiment analysis aims to analyze the sentiment polarity of a given aspect.
The graph convolutional neural network model is widely used. However, most existing …

Word embeddings that consider context have attracted great attention for various natural
language processing tasks in recent years. In this paper, we utilize contextualized word …

Stock price prediction has always been a hot but challenging task due to the complexity and
randomness in stock market. Investors and researchers usually derive a great number of …

Aspect-based Sentiment analysis (ABSA) accomplishes a fine-grained analysis that defines
the aspects of a given document or sentence and the sentiments conveyed regarding each …

In the task of text sentiment analysis, the main problem that we face is that the traditional
word vectors represent lack of polysemy, the Recurrent Neural Network cannot be trained in …

With the proliferation of social networks, group activities have become an essential
ingredient of our daily life. A growing number of users share their group activities online and …

With the development of location-acquisition technologies, there are a huge number of
mobile trajectories generated and accumulated in a variety of domains. However, due to the …

Aspect-level sentiment classification is an interesting but challenging research problem,
namely, the prediction of the sentiment polarity toward a specific aspect term of an …