Name
Abstract | ||
|---|---|---|
A current problem with the research of adaptive systems is the inconsistency of evaluation applied to the adaptive systems. However, evaluating an adaptive system is a difficult task due to the complexity of such systems. Evaluators need to ensure correct evaluation methods and measurement metrics are used. This paper reviews a variety of evaluation techniques applied in adaptive and user-adaptive systems. More specifically, it focuses on the user-centred evaluation of adaptive systems such as personalised recommender systems and adaptive information retrieval systems. The review tackles the question of "ï戮聵How have user-centred evaluations of adaptive and user-adaptive systems been conducted and how can these evaluation practices be improved?' Based on the analysed results of the: (a) evaluation approaches, (b) user-centred evaluation techniques, and (c) evaluation metrics, we propose an evaluation framework for end-user experience in evaluating adaptive systems (EFEx). |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1504/IJKWI.2011.044120 | I. J. Knowledge and Web Intelligence |
Keywords | Field | DocType |
evaluation practice,evaluation metrics,user-centred evaluation,personalised information retrieval system,user-centred evaluation technique,evaluation approach,evaluation technique,evaluation framework,adaptive information retrieval system,adaptive system,correct evaluation method | Recommender system,Data mining,Information retrieval,Adaptive system,Computer science | Journal |
Volume | Issue | Citations |
2 | 2/3 | 11 |
PageRank | References | Authors |
0.66 | 30 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Catherine Mulwa | 1 | 31 | 2.29 |
| Seamus Lawless | 2 | 155 | 13.27 |
| Mary Sharp | 3 | 31 | 2.63 |
| Vincent Wade | 4 | 11 | 0.66 |