A Systematic Literature Review of Question Answering: Research Trends, Datasets, Methods

Abstract

Answering questions, finding the most appropriate answer to the question given by the user as input are among the important tasks of natural language processing. Many studies have been done on question answering and datasets, methods have been published. The aim of this article is to reveal the studies done in question answering and to identify the missing research topics. In this literature review, it is tried to determine the datasets, methods and frameworks used for question answering between 2000 and 2022. From the articles published between these years, 91 papers are selected based on inclusion and exclusion criteria. This systematic literature review consists of research analyzes such as research questions, search strategy, inclusion and exclusion criteria, data extraction. We see that the selected final study focuses on four topics. These are Natural Language Processing, Information Retrieval, Knowledge Base, Hybrid Based.