Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (6A): 267-271.doi: 10.11896/jsjkx.210700123

• Big Data & Data Science • Previous Articles     Next Articles

Recommendation of Android Application Services via User Scenarios

WANG Yi, LI Zheng-hao, CHEN Xing   

  1. College of Mathematics and Computer Science,Fuzhou University,Fuzhou 350108,China
    Fujian Key Laboratory of Network Computing and Intelligent Information Processing(Fuzhou University),Fuzhou 350108,China
  • Online:2022-06-10 Published:2022-06-08
  • About author:WANG Yi,born in 1996,postgraduate.His main research interests include Android application service generation and Android application service adaptation.
    CHEN Xing,born in 1985,Ph.D,professor,Ph.D supervisor,is a member of China Computer Federation.His main research interests include system software,software self-adaptation and cloud computing.
  • Supported by:
    National Key R & D Program of China(2018YFB1004800) and Natural Science Foundation of Fujian Province for Distinguished Young Scholars(2020J06014).

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Abstract: With the development of mobile hardware and 5G communication technologies,smart applications are booming,which has penetrated into all the aspects of our life and work.A large number of Android applications not only meet the needs of people's daily life,but also make people need to spend more time to find the applications they want to start.In order to let users quickly find the application they want to start and perform the target function,this paper proposes a method of Android application service recommendation based on user scenarios.Specifically,this paper first analyzes the user scenarios,and extracts the text information in the user scenarios through the Accessibility API.Then,the label corresponding to the text information is calculated based on the method of knowledge base.Finally,through similarity calculation,the services related to user scenarios in the service library are searched,and the most relevant similar services and complementary services are recommended to users.This paper evaluates 300 Android application services of 10 popular apps in Android App store Wandoujia,and verifies the feasibility and effectiveness of the method.

Key words: Android application, Service recommendation, Similarity calculation, User scenario analysis

CLC Number: 

  • TP311
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