Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Remigio Hurtado"'
Publikováno v:
IEEE Access, Vol 7, Pp 7522-7534 (2019)
Recommender system (RS) clustering is an important issue, both for the improvement of the collaborative filtering (CF) accuracy and to obtain analytical information from their high sparse datasets. RS items and users usually share features belonging
Externí odkaz:
https://doaj.org/article/6dd38bbc3c1c4bfe8671e03b9e6f7317
Publikováno v:
IEEE Access, Vol 6, Pp 3549-3564 (2018)
Recommender Systems present a high-level of sparsity in their ratings matrices. The collaborative filtering sparse data makes it difficult to: 1) compare elements using memory-based solutions; 2) obtain precise models using model-based solutions; 3)
Externí odkaz:
https://doaj.org/article/71d9341692aa42b0a8854890ccceea17
Publikováno v:
IEEE Access, Vol 6, Pp 39745-39761 (2018)
Recommendation to a group of users is a big challenge for collaborative filtering. The recommendations to groups of users arise from the convenience of being able to recommend a group of users about products or services that satisfy the entire group.
Externí odkaz:
https://doaj.org/article/89ae760fff7e4d1b8b124f0b87d7bd1d
Publikováno v:
IEEE Access, Vol 6, Pp 48543-48555 (2018)
The existing scientific documentation-based recommender systems focus on exploiting the citations and references information included in each research paper and also the lists of co-authors. In this way, it can be addressed the recommendation of rela
Externí odkaz:
https://doaj.org/article/d1a773798887499198dc46453b9eee9b
Publikováno v:
IEEE Access, Vol 6, Pp 49935-49954 (2018)
In this paper, we propose a collaborative filtering method designed to improve the current memory-based prediction times without worsening and even improving the existing accuracy results. The accuracy improvement is achieved by combining the numeric
Externí odkaz:
https://doaj.org/article/dddef494c823447785f05bae7d93fb57
Publikováno v:
International Journal of Interactive Multimedia and Artificial Intelligence, Vol 6, Iss 2, p 11 (2020)
In the collaborative filtering recommender systems (CFRS) field, recommendation to group of users is mainly focused on stablished, occasional or random groups. These groups have a little number of users: relatives, friends, colleagues, etc. Our propo
Externí odkaz:
https://doaj.org/article/7aa07c2d36e247d0b34fbc6852762842
Publikováno v:
2022 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6bb5b134b969d41e80df60fd6c101dc7
https://doi.org/10.1109/ropec55836.2022.10018741
https://doi.org/10.1109/ropec55836.2022.10018741
Publikováno v:
2022 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb0633121e4b28fb45fdff8b3b67e044
https://doi.org/10.1109/ropec55836.2022.10018807
https://doi.org/10.1109/ropec55836.2022.10018807
Publikováno v:
Artificial Intelligence and Social Computing.
First of all, one of the applications of artificial intelligence is the prediction of diseases, including hepatitis. Hepatitis has been a recurring disease over the years as it seriously affects the population, increasing by 125,000 deaths per year.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::30cc69ae0fb55e350f6ab1fceba4f710
https://doi.org/10.54941/ahfe1001449
https://doi.org/10.54941/ahfe1001449
Publikováno v:
Artificial Intelligence and Social Computing.
Diabetic Retinopathy is a public health disease worldwide, which shows that around one percent of the population suffers from this disease. Likewise, another one percent of patients in the population suffer from this disease, but it is not diagnosed.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5a98c179ddba1d8a312084a9d6d3305
https://doi.org/10.54941/ahfe1001450
https://doi.org/10.54941/ahfe1001450