Attention has arguably become one of the most important concepts in the deep learning
field. It is inspired by the biological systems of humans that tend to focus on the distinctive …

For machine reading comprehension, the capacity of effectively modeling the linguistic
knowledge from the detail-riddled and lengthy passages and getting ride of the noises is …

To recommend the next item to a user in a transactional context is practical yet challenging
in applications such as marketing campaigns. Transactional context refers to the items that …

With the rapid development and popularization of Internet and mobile communication
technologies, text data mining has attracted much attention. In particular, with the wide use …

Learning attention functions requires large volumes of data, but many NLP tasks simulate
human behavior, and in this paper, we show that human attention really does provide a …

A lack of corpora has so far limited advances in integrating human gaze data as a
supervisory signal in neural attention mechanisms for natural language processing (NLP) …

Understanding human language is one of the key themes of artificial intelligence. For
language representation, the capacity of effectively modeling the linguistic knowledge from …

Abstract Knowledge resources, eg knowledge graphs, which formally represent essential
semantics and information for logic inference and reasoning, can compensate for the …

Decoding human brain activities based on linguistic representations has been actively
studied in recent years. However, most previous studies exclusively focus on word-level …

Determining the similarity between short texts plays an important role in natural language
processing applications such as search, query suggestion and automatic summary, which …