Question answering over knowledge graphs (KG-QA) is a vital topic in IR. Questions with
temporal intent are a special class of practical importance, but have not received much …

This article provides a comprehensive and comparative overview of question answering
technology. It presents the question answering task from an information retrieval perspective …

The automatic scoring of English composition is an inevitable trend of the rapid development
of computer technology and artificial intelligence technology. This makes the research on …

Question Answering (QA) is undoubtedly a growing field of current research in Artificial
Intelligence. Question classification, a QA subtask, aims to associate a category to each …

Question answering over knowledge bases (KB-QA) poses challenges in handling complex
questions that need to be decomposed into sub-questions. An important case, addressed …

Semantic Question Answering (QA) is a crucial technology to facilitate intuitive user access
to semantic information stored in knowledge graphs. Whereas most of the existing QA …

To bridge the gap between the capabilities of the state-of-the-art in factoid question
answering (QA) and what users ask, we need large datasets of real user questions that …

Interpreting Motion presents an integrated perspective on how language structures constrain
concepts of motion and how the world shapes the way motion is linguistically expressed …

Question answering over knowledge base (KBQA) is a powerful tool to extract answers from
graph-like knowledge bases. Here, we present ComQA-a three-phase KBQA framework by …

Temporal expressions are words or phrases that describe a point, duration or recurrence in
time. Automatically annotating these expressions is a research goal of increasing interest …