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
T2 - 8th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2016
Y2 - 19 December 2016 through 21 December 2016
ER -