Name
Title | ||
|---|---|---|
A new framework for increasing user engagement in mobile applications using machine learning techniques |
Abstract | ||
|---|---|---|
In this paper, it is proposed to build a new framework which anticipates mobile user status and behavior characteristics with the aim of increasing user engagement and provide stickiness in mobile applications (iOS-Android) by using machine learning techniques. Motivation of this study is based on the idea of collecting data from users by non-survey methods because data collection from surveys may mislead the system model according to the literature researches on user experience. User behavior includes forecasting next usage time of the user, user motivation type, user mastery level and current context of the user. In order to find relevant patterns, usage data is obtained from pilot mobile applications at first and then they are processed according to the chosen machine learning algorithm. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-39253-5_72 | HCI (12) |
Keywords | Field | DocType |
data collection,user motivation type,usage data,user experience,new framework,user behavior,mobile user status,mobile application,pilot mobile application,user mastery level,user engagement | User experience design,Computer science,Human–computer interaction,User modeling,Artificial intelligence,Computer user satisfaction,Mobile search,User interface design,User interface,User requirements document,Multimedia,Machine learning,User journey | Conference |
Citations | PageRank | References |
2 | 0.39 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Merve Gençer | 1 | 3 | 0.74 |
| Gökhan Bilgin | 2 | 62 | 13.18 |
| Özgür Zan | 3 | 3 | 0.74 |
| Tansel Voyvodaoğlu | 4 | 2 | 0.39 |