Zobrazeno 1 - 10
of 80
pro vyhledávání: '"Jesús Bobadilla"'
Publikováno v:
International Journal of Interactive Multimedia and Artificial Intelligence, Vol 8, Iss 6, Pp 15-23 (2024)
Matrix factorization models are the core of current commercial collaborative filtering Recommender Systems. This paper tested six representative matrix factorization models, using four collaborative filtering datasets. Experiments have tested a varie
Externí odkaz:
https://doaj.org/article/ef6ec8c4f8064e9299f963f5714b556c
Publikováno v:
International Journal of Interactive Multimedia and Artificial Intelligence, Vol 7, Iss 4, Pp 18-26 (2022)
Neural collaborative filtering is the state of art field in the recommender systems area; it provides some models that obtain accurate predictions and recommendations. These models are regression-based, and they just return rating predictions. This p
Externí odkaz:
https://doaj.org/article/e467100e964d44858e0089463b157060
Publikováno v:
International Journal of Interactive Multimedia and Artificial Intelligence, Vol 6, Iss 6, Pp 86-94 (2021)
The lack of bias management in Recommender Systems leads to minority groups receiving unfair recommendations. Moreover, the trade-off between equity and precision makes it difficult to obtain recommendations that meet both criteria. Here we propose a
Externí odkaz:
https://doaj.org/article/670b6b09ec0c4f73835caa406f366771
Publikováno v:
International Journal of Interactive Multimedia and Artificial Intelligence, Vol 6, Iss 1, Pp 68-77 (2020)
This paper proposes a scalable and original classification-based deep neural architecture. Its collaborative filtering approach can be generalized to most of the existing recommender systems, since it just operates on the ratings dataset. The learnin
Externí odkaz:
https://doaj.org/article/fff5823df401443392cace17205d0179
Publikováno v:
Applied Sciences, Vol 12, Iss 9, p 4168 (2022)
Visual representation of user and item relations is an important issue in recommender systems. This is a big data task that helps to understand the underlying structure of the information, and it can be used by company managers and technical staff. C
Externí odkaz:
https://doaj.org/article/7417ba4f029149a8b4b24ca3b5febda4
Publikováno v:
Revista Española de Documentación Científica, Vol 42, Iss 1, Pp e228-e228 (2019)
La investigación en el campo de la documentación científica nos lleva hacia un procesamiento automático de grandes cantidades de información proveniente de los trabajos publicados por la comunidad científica. Resulta necesario explicar estos pr
Externí odkaz:
https://doaj.org/article/5d68d85a69b047e7a698e86f80d4cadf
Publikováno v:
Sensors, Vol 20, Iss 16, p 4628 (2020)
Internet of Things (IoT) projects are increasing in size over time, and some of them are growing to reach the whole world. Sensor arrays are deployed world-wide and their data is sent to the cloud, making use of the Internet. These huge networks can
Externí odkaz:
https://doaj.org/article/59f4793c0d0d4eaf839541cef1d9e958
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:
Applied Sciences, Vol 10, Iss 2, p 675 (2020)
Recommender systems aim to estimate the judgment or opinion that a user might offer to an item. Matrix-factorization-based collaborative filtering typifies both users and items as vectors of factors inferred from item rating patterns. This method fin
Externí odkaz:
https://doaj.org/article/98f9b6df6672452ba21c1957ef4f29a7
Autor:
de Jesús Bobadilla Munive, Jhonatan1,2 jhonatanbobadilla@gmail.com
Publikováno v:
Journal of the Colombian Society of Psychoanalysis / Revista de la Sociedad Colombiana de Psicoanálisis. dec2022, Vol. 47 Issue 2, p239-266. 28p.