Neural network models have been widely used in the field of natural language processing
(NLP). Recurrent neural networks (RNNs), which have the ability to process sequences of …

In this paper, we survey the methods and concepts developed for the evaluation of dialogue
systems. Evaluation, in and of itself, is a crucial part during the development process. Often …

Recurrent neural networks for session-based recommendation have attracted a lot of
attention recently because of their promising performance. repeat consumption is a common …

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 …

This paper shows the modeling and performance in deep learning computation for an
Assistant Conversational Agent (Chatbot). The utilization of Tensorflow software library …

Accurate and timely traffic flow prediction is crucial for intelligent transportation systems
(ITS). Recent advances in graph-based neural networks have achieved promising prediction …

Glaucoma is one of the leading causes of blindness in the world and there is no cure for it
yet. But it is very meaningful to detect it early as earlier detection makes it possible to stop …

Traffic flow prediction is an important functional component of Intelligent Transportation
Systems (ITS). In this paper, we propose a hybrid deep learning approach, called graph and …

Recommendation systems, prevalent in many applications, aim to surface to users the right
content at the right time. Recently, researchers have aspired to develop conversational …

Fact-centric information needs are rarely one-shot; users typically ask follow-up questions to
explore a topic. In such a conversational setting, the user's inputs are often incomplete, with …