Predicting mobile application ratings using artificial neural network

Mehul Smriti Raje

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents and evaluates neural network models for predicting the ratings of mobile applications. It is shown that the information available to the developer at the time of releasing the application alone, can be used to make the predictions. The results of evaluation of 50,000 applications, available on a popular application store, is reported. It is seen that the prediction accuracy varies from 58.15% to 93.5% for different cases.

Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2016
PublisherSpringer Verlag
Pages86-93
Number of pages8
ISBN (Print)9783319606170
DOIs
Publication statusPublished - 01-01-2018
Externally publishedYes
Event8th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2016 - Vellore, India
Duration: 19-12-201621-12-2016

Publication series

NameAdvances in Intelligent Systems and Computing
Volume614
ISSN (Print)2194-5357

Conference

Conference8th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2016
CountryIndia
CityVellore
Period19-12-1621-12-16

Fingerprint

Neural networks

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Raje, M. S. (2018). Predicting mobile application ratings using artificial neural network. In Proceedings of the 8th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2016 (pp. 86-93). (Advances in Intelligent Systems and Computing; Vol. 614). Springer Verlag. https://doi.org/10.1007/978-3-319-60618-7_9
Raje, Mehul Smriti. / Predicting mobile application ratings using artificial neural network. Proceedings of the 8th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2016. Springer Verlag, 2018. pp. 86-93 (Advances in Intelligent Systems and Computing).
@inproceedings{7957256f4fd149e9972de729a21f317b,
title = "Predicting mobile application ratings using artificial neural network",
abstract = "This paper presents and evaluates neural network models for predicting the ratings of mobile applications. It is shown that the information available to the developer at the time of releasing the application alone, can be used to make the predictions. The results of evaluation of 50,000 applications, available on a popular application store, is reported. It is seen that the prediction accuracy varies from 58.15{\%} to 93.5{\%} for different cases.",
author = "Raje, {Mehul Smriti}",
year = "2018",
month = "1",
day = "1",
doi = "10.1007/978-3-319-60618-7_9",
language = "English",
isbn = "9783319606170",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "86--93",
booktitle = "Proceedings of the 8th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2016",
address = "Germany",

}

Raje, MS 2018, Predicting mobile application ratings using artificial neural network. in Proceedings of the 8th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2016. Advances in Intelligent Systems and Computing, vol. 614, Springer Verlag, pp. 86-93, 8th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2016, Vellore, India, 19-12-16. https://doi.org/10.1007/978-3-319-60618-7_9

Predicting mobile application ratings using artificial neural network. / Raje, Mehul Smriti.

Proceedings of the 8th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2016. Springer Verlag, 2018. p. 86-93 (Advances in Intelligent Systems and Computing; Vol. 614).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Predicting mobile application ratings using artificial neural network

AU - Raje, Mehul Smriti

PY - 2018/1/1

Y1 - 2018/1/1

N2 - This paper presents and evaluates neural network models for predicting the ratings of mobile applications. It is shown that the information available to the developer at the time of releasing the application alone, can be used to make the predictions. The results of evaluation of 50,000 applications, available on a popular application store, is reported. It is seen that the prediction accuracy varies from 58.15% to 93.5% for different cases.

AB - This paper presents and evaluates neural network models for predicting the ratings of mobile applications. It is shown that the information available to the developer at the time of releasing the application alone, can be used to make the predictions. The results of evaluation of 50,000 applications, available on a popular application store, is reported. It is seen that the prediction accuracy varies from 58.15% to 93.5% for different cases.

UR - http://www.scopus.com/inward/record.url?scp=85028586843&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85028586843&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-60618-7_9

DO - 10.1007/978-3-319-60618-7_9

M3 - Conference contribution

AN - SCOPUS:85028586843

SN - 9783319606170

T3 - Advances in Intelligent Systems and Computing

SP - 86

EP - 93

BT - Proceedings of the 8th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2016

PB - Springer Verlag

ER -

Raje MS. Predicting mobile application ratings using artificial neural network. In Proceedings of the 8th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2016. Springer Verlag. 2018. p. 86-93. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-319-60618-7_9