A Research Review of Mobile Application Review Mining

[Purpose/significance] User reviews are helpful for developers to realize mobile application innovation. This paper summarizes the literature related to mobile application review mining and provides references for mobile application development and review mining. [Method/process] This study reviewed...

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Autores principales:	Zhang Ji, Kang Lele, Li Bo
Formato:	article
Lenguaje:	ZH
Publicado:	LIS Press 2021
Materias:	mobile application Bibliography. Library science. Information resources Z
Acceso en línea:	https://doaj.org/article/6866f07e8a1f403dbf395c1e3bfd300f
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id	oai:doaj.org-article:6866f07e8a1f403dbf395c1e3bfd300f
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spelling	oai:doaj.org-article:6866f07e8a1f403dbf395c1e3bfd300f2021-11-24T07:22:11ZA Research Review of Mobile Application Review Mining10.13266/j.issn.2095-5472.2021.0322095-5472https://doaj.org/article/6866f07e8a1f403dbf395c1e3bfd300f2021-11-01T00:00:00Zhttp://kmf.ac.cn/p/266/https://doaj.org/toc/2095-5472[Purpose/significance] User reviews are helpful for developers to realize mobile application innovation. This paper summarizes the literature related to mobile application review mining and provides references for mobile application development and review mining. [Method/process] This study reviewed the researches related to mobile application review mining into three key themes of review classification, review clustering and review feature extraction by using the text analysis method, and expounded on the development status of this field according to this framework. [Result/conclusion] At present, the methods of review classification have begun to evolve from machine learning to deep learning; review clustering mainly uses K-Means and DBSCAN; feature extraction is still focused on the explicit features of APP reviews. In the future, there are still three issues worth exploring in mobile application review mining: domain dependence, multi-source information fusion and review value evaluation.Zhang JiKang LeleLi BoLIS Pressarticlemobile applicationBibliography. Library science. Information resourcesZZHZhishi guanli luntan, Vol 6, Iss 6, Pp 0-0 (2021)
institution	DOAJ
collection	DOAJ
language	ZH
topic	mobile application Bibliography. Library science. Information resources Z
spellingShingle	mobile application Bibliography. Library science. Information resources Z Zhang Ji Kang Lele Li Bo A Research Review of Mobile Application Review Mining
description	[Purpose/significance] User reviews are helpful for developers to realize mobile application innovation. This paper summarizes the literature related to mobile application review mining and provides references for mobile application development and review mining. [Method/process] This study reviewed the researches related to mobile application review mining into three key themes of review classification, review clustering and review feature extraction by using the text analysis method, and expounded on the development status of this field according to this framework. [Result/conclusion] At present, the methods of review classification have begun to evolve from machine learning to deep learning; review clustering mainly uses K-Means and DBSCAN; feature extraction is still focused on the explicit features of APP reviews. In the future, there are still three issues worth exploring in mobile application review mining: domain dependence, multi-source information fusion and review value evaluation.
format	article
author	Zhang Ji Kang Lele Li Bo
author_facet	Zhang Ji Kang Lele Li Bo
author_sort	Zhang Ji
title	A Research Review of Mobile Application Review Mining
title_short	A Research Review of Mobile Application Review Mining
title_full	A Research Review of Mobile Application Review Mining
title_fullStr	A Research Review of Mobile Application Review Mining
title_full_unstemmed	A Research Review of Mobile Application Review Mining
title_sort	research review of mobile application review mining
publisher	LIS Press
publishDate	2021
url	https://doaj.org/article/6866f07e8a1f403dbf395c1e3bfd300f
work_keys_str_mv	AT zhangji aresearchreviewofmobileapplicationreviewmining AT kanglele aresearchreviewofmobileapplicationreviewmining AT libo aresearchreviewofmobileapplicationreviewmining AT zhangji researchreviewofmobileapplicationreviewmining AT kanglele researchreviewofmobileapplicationreviewmining AT libo researchreviewofmobileapplicationreviewmining
_version_	1718415916838944768

A Research Review of Mobile Application Review Mining

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