Predictability of Off-line to On-line Recommender Measures via Scaled Fuzzy Implicators
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10416938" target="_blank" >RIV/00216208:11320/20:10416938 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/FUZZ48607.2020.9177682" target="_blank" >https://doi.org/10.1109/FUZZ48607.2020.9177682</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/FUZZ48607.2020.9177682" target="_blank" >10.1109/FUZZ48607.2020.9177682</a>
Alternative languages
Result language
angličtina
Original language name
Predictability of Off-line to On-line Recommender Measures via Scaled Fuzzy Implicators
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GJ19-22071Y" target="_blank" >GJ19-22071Y: Flexible models for known-item search in large video collections</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
ISBN
978-1-72816-932-3
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
1-8
Publisher name
IEEE
Place of publication
Neuveden
Event location
Glasgow, United Kingdom, United Kingdom
Event date
Jul 19, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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