
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Mobile App Stores such as Google, Apple have wide range of applications to suffice every need of customers in the digital platform. Customer feedback and ratings has always been one of the major metrics that can be used to review the performance and accordingly provide suitable recommendations to enhance the functionality. The Given dataset contain the feedback of the customer regarding the app used in app store. Data Set Column Details are as given below: Column name: Description: Column Name in Working Sheet Datatype Please read the Readme.docs file
Text Classification, Mobile app rate prediction, user rating classification , deep learning, MLP, Play scraper
Text Classification, Mobile app rate prediction, user rating classification , deep learning, MLP, Play scraper
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
views | 35 | |
downloads | 28 |