Question answering, serving as one of important tasks in natural language processing,
enables machines to understand questions in natural language and answer the questions …

Machine Reading Comprehension (MRC) is a challenging task and hot topic in Natural
Language Processing. The goal of this field is to develop systems for answering the …

The proliferation of massive open online courses (MOOCs) demands an effective way of
personalized course recommendation. The recent attention-based recommendation models …

Multi-task learning (MTL) has become increasingly popular in natural language processing
(NLP) because it improves the performance of related tasks by exploiting their …

This paper tackles the problem of open domain factual Arabic question answering (QA)
using Wikipedia as our knowledge source. This constrains the answer of any question to be …

Rapid progress has been made in the field of reading comprehension and question
answering, where several systems have achieved human parity in some simplified settings …

Open-domain textual question answering (QA), which aims to answer questions from large
data sources like Wikipedia or the web, has gained wide attention in recent years. Recent …

This study investigates the internality of managerial responses (MRs) to online reviews on
the responded customers'(ie, customers who have posted an initial review and then being …

Machine reading comprehension (MRC) aims to teach machines to read and comprehend
human languages, which is a long-standing goal of natural language processing (NLP) …

Community question answering (CQA) gains increasing popularity in both academy and
industry recently. However, the redundancy and lengthiness issues of crowdsourced …