Name
Abstract | ||
|---|---|---|
User behaviour analytics (UBA) systems offer sophisticated models that capture users' behaviour over time with an aim to identify fraudulent activities that do not match their profiles. Motivated by the challenges in the interpretation of UBA models, this paper presents a visual analytics approach to help analysts gain a comprehensive understanding of user behaviour at multiple levels, namely individual and group level. We take a user-centred approach to design a visual analytics framework supporting the analysis of collections of users and the numerous sessions of activities they conduct within digital applications. The framework is centred around the concept of
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hierarchical user profiles</italic>
that are built based on features derived from sessions, as well as on user tasks extracted using a topic modelling approach to summarise and stratify user behaviour. We externalise a series of analysis goals and tasks, and evaluate our methods through use cases conducted with experts. We observe that with the aid of interactive visual hierarchical user profiles, analysts are able to conduct exploratory and investigative analysis effectively, and able to understand the characteristics of user behaviour to make informed decisions whilst evaluating suspicious users and activities. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TVCG.2019.2934609 | IEEE transactions on visualization and computer graphics |
Keywords | Field | DocType |
Task analysis,Data visualization,Feature extraction,Visual analytics,Analytical models,Buildings | Use case,Computer science,Visual analytics,Theoretical computer science,Human–computer interaction,Analytics | Journal |
Volume | Issue | ISSN |
26 | 1 | 1077-2626 |
Citations | PageRank | References |
5 | 0.40 | 15 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Phong H. Nguyen | 1 | 80 | 7.37 |
| Rafael Henkin | 2 | 5 | 1.75 |
| Siming Chen | 3 | 125 | 14.34 |
| Natalia Andrienko | 4 | 2922 | 192.14 |
| Gennady Andrienko | 5 | 3106 | 208.19 |
| Olivier Thonnard | 6 | 230 | 19.56 |
| Cagatay Turkay | 7 | 287 | 22.63 |