Deep learning approaches have achieved great success in the field of Natural Language
Processing (NLP). However, directly training deep neural models often suffer from overfitting …

Intent classification, to identify the speaker's intention, and slot filling, to label each token
with a semantic type, are critical tasks in natural language understanding. Traditionally the …

Sentiment analysis uses a series of automated cognitive methods to determine the author's
or speaker's attitudes toward an expressed object or text's overall emotional tendencies. In …

In recommender systems, cold-start issues are situations where no previous events, eg,
ratings, are known for certain users or items. In this paper, we focus on the item cold-start …

Abstract Internet of Things (IoT) based voice interaction system, as a new artificial
intelligence application, provides a new human–computer interaction mode. The more …

In task-oriented dialogue (ToD), a user holds a conversation with an artificial agent with the
aim of completing a concrete task. Although this technology represents one of the central …

This paper targets to a novel but practical recommendation problem named exact-K
recommendation. It is different from traditional top-K recommendation, as it focuses more on …

Multilingual task-oriented dialogue (ToD) facilitates access to services and information for
many (communities of) speakers. Nevertheless, its potential is not fully realized, as current …

Despite the fact that natural language conversations with machines represent one of the
central objectives of AI, and despite the massive increase of research and development …

In task-oriented dialogue systems, slot filling aims to identify the semantic slot types of each
token in user utterances. Due to the lack of sufficient supervised data in many scenarios, it is …