Comprehensive Analysis for Intelligent Recommendation on Mobile Applications

Abstract

With the development of mobile devices and mobile apps, corresponding app recommendation analysis has received increasing focus in recent years. Such recommendation analysis covers aims including app evaluation, API-based app development, customer investigation, app security, etc. Meanwhile, various types of recommendation techniques are exploited in the app recommendation analysis, which continually improves the development of this direction. However, there is still a lack of a systematical study providing an overall development picture for these app recommendation efforts. Thus, it faces an obstacle for related researchers following this direction of work, and correspondingly is not conducive to the future development. To overcome the problem, in this paper, we take the first step to systematically investigate this direction of efforts. To this end, we summary the main works and techniques used in more than 35 important works in this direction. To better understand the development routines, we have analyzed the characteristics of these works from two perspectives, i.e., technology and research scenario. We have obtained some interesting conclusions within this research direction, and put forward some work suggestions according to the overall research.