Paper Info
Title
Preference, context and communities: a multi-faceted approach to predicting smartphone app usage patterns
Abstract
Reliable smartphone app prediction can strongly benefit both users and phone system performance alike. However, real-world smartphone app usage behavior is a complex phenomena driven by a number of competing factors. In this pa- per, we develop an app usage prediction model that leverages three key everyday factors that affect app usage decisions -- (1) intrinsic user app preferences and user historical patterns; (2) user activities and the environment as observed through sensor-based contextual signals; and, (3) the shared aggregate patterns of app behavior that appear in various user communities. While rapid progress has been made recently in smartphone app prediction, existing prediction models tend to focus on only one of these factors. We evaluate a multi-faceted approach to prediction using (1) a 3-week 35-user field trial, along with (2) analysis of app usage logs of 4,606 smartphone users worldwide. We find our app usage model can not only produce more robust app predictions than conventional techniques, but it can also enable significant smartphone system optimizations.
Year
DOI
Venue
2013
10.1145/2493988.2494333
ISWC
Keywords
Field
DocType
app usage prediction model,app behavior,intrinsic user app preference,smartphone app prediction,real-world smartphone app usage,robust app prediction,app usage log,app usage model,app usage decision,smartphone app usage pattern,reliable smartphone app prediction,multi-faceted approach,mobile communication
World Wide Web,Computer science,Phone,Predictive modelling,Usage model,Mobile telephony
Conference
Citations 
PageRank 
References 
44
1.32
23
Authors
8
Name
Order
Citations
PageRank
Ye Xu127514.97
Mu Lin222910.94
Hong Lu32730150.65
Giuseppe Cardone444423.49
Nicholas D. Lane54247248.15
Zhenyu Chen647025.35
Andrew T. Campbell78958759.66
Tanzeem Choudhury84137306.53