TY - GEN
T1 - Designing the next mobile app recommender system for the globe
AU - Yasin, Affan
AU - Liu, Lin
AU - Fatima, Rubia
AU - Jianmin, Wang
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/11/27
Y1 - 2017/11/27
N2 - Innovative mobile applications bring radical changes to people's life around the globe. With its unique characteristics of anywhere, anytime accessibility, thousands of mobile apps are developed, distributed, and executed over the Internet. To understand the selection criteria for different end users when facing a mobile application, this paper quests for an evaluation framework for mobile apps based statistical data analysis and survey. Firstly, user's ratings on 1500+ mobile applications from Google Play were analyzed to elicit different users' preferences on mobile apps. The data was extracted twice, first at the end 2015, then early 2017, and the data are from four different locations: The UK, USA, Netherland, and Pakistan. Secondly, the survey was conducted to collect university students' rationale when making selections and downloading decisions of a mobile app. Furthermore, the knowledge gathered from data and survey is used to propose a systematic evaluation framework. Finally, the proposed framework is used to develop a recommender system for the mobile app markets. The implementation of the recommender system is introduced, and which was further verified by an example case.
AB - Innovative mobile applications bring radical changes to people's life around the globe. With its unique characteristics of anywhere, anytime accessibility, thousands of mobile apps are developed, distributed, and executed over the Internet. To understand the selection criteria for different end users when facing a mobile application, this paper quests for an evaluation framework for mobile apps based statistical data analysis and survey. Firstly, user's ratings on 1500+ mobile applications from Google Play were analyzed to elicit different users' preferences on mobile apps. The data was extracted twice, first at the end 2015, then early 2017, and the data are from four different locations: The UK, USA, Netherland, and Pakistan. Secondly, the survey was conducted to collect university students' rationale when making selections and downloading decisions of a mobile app. Furthermore, the knowledge gathered from data and survey is used to propose a systematic evaluation framework. Finally, the proposed framework is used to develop a recommender system for the mobile app markets. The implementation of the recommender system is introduced, and which was further verified by an example case.
KW - App design
KW - App user behavior
KW - Categorization
KW - Mobile application
KW - Preference Elicitation
KW - Recommender system
KW - User requirements
KW - User specifications
UR - http://www.scopus.com/inward/record.url?scp=85048369037&partnerID=8YFLogxK
U2 - 10.1109/ISPAN-FCST-ISCC.2017.44
DO - 10.1109/ISPAN-FCST-ISCC.2017.44
M3 - Conference Proceeding
AN - SCOPUS:85048369037
T3 - Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017
SP - 491
EP - 500
BT - Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017
Y2 - 21 June 2017 through 23 June 2017
ER -