Name
Abstract | ||
|---|---|---|
Users preferences evolve over the time. This socalled dynamics is a serious challenge which is widely researched in several domains. In these domains, users are usually active for a long period of time and they tend to interact with a wide range of items. To make it more complicated, users preferences are likely to evolve only in some aspects while others remain untouched. In this paper we present an analysis of user behavior dynamics in a fashion e-shop. We identified four typical user behaviors, i.e., classes. Moreover, we explored typical user behavior before and after the purchase. As a result, such knowledge can improve various tasks dealing with short-term dynamics, mainly in session-based recommender systems. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/SMAP.2019.8864802 | 2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) |
Keywords | Field | DocType |
user modelling,user behavior,concept drift,preference dynamics,fashion,session based recommendation | Recommender system,Task analysis,Computer science,Clothing,Human–computer interaction,Semantics | Conference |
ISBN | Citations | PageRank |
978-1-7281-3635-6 | 0 | 0.34 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miroslav Rac | 1 | 0 | 0.68 |
| Michal Kompan | 2 | 0 | 0.34 |
| Mária Bieliková | 3 | 968 | 124.82 |