Name
Title | ||
|---|---|---|
Predictability of Off-line to On-line Recommender Measures via Scaled Fuzzy Implicators |
Abstract | ||
|---|---|---|
This paper introduces fuzzy Challenge Response Framework, designed to understand the relationship between the model of a real-world situation and some real observations, based on scaled fuzzy Implicators between them. This general framework is applied to a particular case in recommender systems: the prediction of on-line performance given off-line evaluation results. We perform an empirical evaluation with real data from a Czech travel agency, comparing different recommender algorithms, different metrics for on-line and offline evaluations, and different implication operators. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/FUZZ48607.2020.9177682 | 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) |
Keywords | DocType | ISSN |
fuzzy web intelligence,recommender systems,fuzzy decision support systems,on-line vs. off-line evaluation | Conference | 1544-5615 |
ISBN | Citations | PageRank |
978-1-7281-6933-0 | 0 | 0.34 |
References | Authors | |
10 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ladislav Peska | 1 | 83 | 19.95 |
| Peter Vojtás | 2 | 336 | 33.41 |