Name
Title | ||
|---|---|---|
Layered Evaluation for Data Discovery and Recommendation Systems: An Initial Set of Principles |
Abstract | ||
|---|---|---|
This paper examines how a layered evaluation framework proposed for adaptive systems (AS) can be applied in the case of recommender systems (RecSys). Our analysis indicates that implementing a layered-based evaluation has the potential to facilitate a more detailed and informed evaluation of RecSys, allowing researchers and developers to better understand how to improve them. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICALT.2014.152 | Advanced Learning Technologies |
Keywords | Field | DocType |
recommender systems, layered evaluation, adaptive systems,recommender systems,predictive models,measurement,adaptive systems,recommendation systems,data mining | Recommender system,Data discovery,World Wide Web,Computer science,Adaptive system,Multimedia | Conference |
ISSN | Citations | PageRank |
2161-3761 | 3 | 0.39 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nikos Manouselis | 1 | 638 | 46.80 |
| Charalampos Karagiannidis | 2 | 155 | 26.08 |
| Demetrios G. Sampson | 3 | 1310 | 247.68 |