Working Paper Review Version 1 This version is not peer-reviewed

Datasets for Machine Reading Comprehension: A Literature Review

Version 1 : Received: 5 October 2019 / Approved: 8 October 2019 / Online: 8 October 2019 (10:40:09 CEST)

A peer-reviewed article of this Preprint also exists.

Journal reference: SSRN Electronic Journal 2019
DOI: 10.2139/ssrn.3454037

Abstract

Machine reading comprehension aims to teach machines to understand a text like a human, and is a new challenging direction in Artificial Intelligence. Datasets play an important role while describing or building an algorithm for machine reading comprehension. The type of answers we required from developed algorithm depends on datasets.The datasets are classified into two types, namely datasets with extractive answers and datasets with descriptive answers. This article summarize both datasets with an example of each type to get better insight of datasets in machine reading comprehension and which datasets to use depending the requirements.

Subject Areas

Reading Comprehensio; Descriptive Answer; Extractive answer; Multiple-choice answers; Datasets

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