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Aspect Extraction using Informative Data from Mobile App Data Review

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Budi Eko Prasetyo, Divi Galih Prasetyo Putri, Endang Wahyu Pamungkas
10.5120/ijca2017915422

Budi Eko Prasetyo, Divi Galih Prasetyo Putri and Endang Wahyu Pamungkas. Aspect Extraction using Informative Data from Mobile App Data Review. International Journal of Computer Applications 173(9):28-32, September 2017. BibTeX

@article{10.5120/ijca2017915422,
	author = {Budi Eko Prasetyo and Divi Galih Prasetyo Putri and Endang Wahyu Pamungkas},
	title = {Aspect Extraction using Informative Data from Mobile App Data Review},
	journal = {International Journal of Computer Applications},
	issue_date = {September 2017},
	volume = {173},
	number = {9},
	month = {Sep},
	year = {2017},
	issn = {0975-8887},
	pages = {28-32},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume173/number9/28362-2017915422},
	doi = {10.5120/ijca2017915422},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

User review of mobile application is an valuable data that can be used by developer to improve their application or to build similar application. User can give feedback such as reporting errors, asking for new or improved feature, explain their experience of using certain feature and also praise or dispraise. User review or opinion data is very large in amount and difficult to analyze. It is time consuming and labour expensive to do it manually. Recent study has tried to extract product feature using word collocation. In this work, we try to improve the aspect extraction process by using only informative data. We took user opinion of 3 mobile application from application distribution platform. The experiment result indicate that our approach is able to improve the performance of collocation finding method.

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Keywords

Aspect extraction; aspect-based sentiment analysis; collocation; naive bayes;