GimmeHop: A recommender system for mobile devices using ontology reasoners and fuzzy logic
Resumen: This paper describes GimmeHop, a beer recommender system for Android mobile devices using fuzzy ontologies to represent the relevant knowledge and semantic reasoners to infer implicit knowledge. GimmeHop use fuzzy quantifiers to deal with incomplete data, fuzzy hedges to deal with the user context, and aggregation operators to manage user preferences. The results of our evaluation measure empirically the data traffic and the running time in the case of remote reasoning, the size of the ontologies that can be locally dealt with in a mobile device in the case of local reasoning, and the quality of the automatically computed linguistic values supported in the user queries.
Idioma: Inglés
DOI: 10.1016/j.fss.2019.12.001
Año: 2020
Publicado en: Fuzzy Sets and Systems 401 (2020), 55-77
ISSN: 0165-0114

Factor impacto JCR: 3.343 (2020)
Categ. JCR: COMPUTER SCIENCE, THEORY & METHODS rank: 23 / 110 = 0.209 (2020) - Q1 - T1
Categ. JCR: STATISTICS & PROBABILITY rank: 20 / 125 = 0.16 (2020) - Q1 - T1
Categ. JCR: MATHEMATICS, APPLIED rank: 18 / 265 = 0.068 (2020) - Q1 - T1

Factor impacto SCIMAGO: 0.902 - Logic (Q1) - Artificial Intelligence (Q1)

Financiación: info:eu-repo/grantAgreement/ES/AEI-FEDER/TIN2016-78011-C4-3-R
Financiación: info:eu-repo/grantAgreement/ES/UZ/JIUZ-2018-TEC-02
Tipo y forma: Article (PostPrint)
Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)

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Exportado de SIDERAL (2025-10-17-14:13:24)


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Articles > Artículos por área > Lenguajes y Sistemas Informáticos



 Record created 2025-01-28, last modified 2025-10-17


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