Common but innovative: Learning features from apps in different domains

Abstract

With the popularity of Apps, the products in one domain become more and more similar to each other, and developers start to find the break from other domains. However, facing the large-scale data resource in App stores, it is difficult to identify the related domains, let alone gain useful features from the products in them. In this paper, we propose an approach to help developers learn information of features related to their App from the products in different domains. Firstly, we provide the method to extract features as well as their relationships from App descriptions to describe one domain. Then, the similar features shared by different domains are identified as the bridges for searching the potential information which may be re-used by the developers. Finally, we provide the framework of an interactive recommendation system to let developers gain and understand the information easily. To evaluate our approach, we conducted experiments based on the dataset on Google Play. The results show that the average precision of our approach for finding similar features between different domains can reach 82.38%, and the survey on developers indicate that the information recommended by our approach is useful for updating Apps and inspiring developers generate innovative ideas.