.png){kind=icon}
.png){kind=icon}
Return
Pull-based recommendations in mobile environments
.png){kind=icon}
PRE
AI
DOI：10.1016/j.csi.2015.08.002.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In the field of Context-Aware Recommendation Systems (CARS), only static contextual information is usually considered. However, the dynamic contextual information would very helpful in mobile computing scenarios. Despite this interest, the design and implementation of flexible and generic frameworks to support an easy development of context-aware mobile recommendation systems have been relatively unexplored. In this paper, we describe a framework that facilitates the development of CARS for mobile environments. We mainly focus on the development of the elements needed to support pull-based recommendations and the experimental evaluation of the proposed system. (C) 2015 Elsevier B.V. All rights reserved.
Keywords:
Context-awareness
Recommendation systems
Mobile computing
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
C
IF:
3.1
Papers:
2.3K
Citations:
2.0K