With the rapid growth of the scientific literature, manually selecting appropriate citations for a paper is becoming increasingly challenging and time-consuming.
This paper introduces a Vietnamese text-based conversational agent architecture on specific knowledge domain which is integrated in a question answering system.
Question answering systems aim to produce exact answers to users' questions instead of a list of related documents as used by current search engines.
To the best of our knowledge, this is the first work that applies deep learning based approach to dialog act segmentation.
In this paper, we propose a new approach to construct a system of transformation rules for the Part-of-Speech (POS) tagging task.