A software popularity recommendation method based on evaluation model

Yan Wang, Pei Xiang Bai, De yu Yang, Xiao yu Song

Abstract:

The software sharing platform in the Internet provides great convenience for the promotion, application and communication of software (especially source software). But there inevitably exists the problem of software quality on the open Internet platform. How the users choose software to download and use becomes a new challenge for software sharing platforms. Aimed at the above problems and
challenges, the internal relations between the data collected on platform and experience of user are analyzed. And then a software popularity recommendation method based on evaluation model is presented. The method constructs two evaluation indexes based on the collected data on the platform, including attention-degree and satisfaction-degree; solves the problem of small sample data’s influence on the accuracy of evaluation model by using the Wilson interval model and makes a tradeoff between the recommendation results of old
and new software by using Newton cooling law. The experimental results show that the software popularity recommendation method based on evaluation model helps users to screen for software, which can effectively improve the service performance of software sharing platform.