Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Juan A. Recio-Garcia"'
Autor:
Cristian E. Sosa-Espadas, Mauricio G. Orozco-del-Castillo, Nora Cuevas-Cuevas, Juan A. Recio-Garcia
Publikováno v:
SoftwareX, Vol 23, Iss , Pp 101420- (2023)
Tabular datasets, collections of rows and columns, are fundamental in data analysis in basically all areas of research. Self-report questionnaires are a very common and useful tool for gathering data from users, patients, or customers. Often, experts
Externí odkaz:
https://doaj.org/article/b6f4bbb256ee4fb68c8ea6548dc63fbe
Publikováno v:
SoftwareX, Vol 21, Iss , Pp 101311- (2023)
Existing XAI libraries offer a good number of explanation and visualization methods. We refer to the combination of these XAI methods and their further customization to meet the actual needs of users as explanation strategies. The Explanation Experie
Externí odkaz:
https://doaj.org/article/8372eaa7d03f4d9785160a806197b567
Publikováno v:
IEEE Access, Vol 7, Pp 124233-124243 (2019)
The venture capital (VC) industry offers opportunities for investment in early-stage companies where uncertainty is very high. Unfortunately, the tools investors currently have available are not robust enough to reduce risk and help them managing unc
Externí odkaz:
https://doaj.org/article/30a4ed2b3b9d42669fe7fd092edfd5f8
Publikováno v:
IEEE Journal of Biomedical and Health Informatics. :1-12
Publikováno v:
Knowledge and Information Systems.
Traditionally, recommender systems use collaborative filtering or content-based approaches based on ratings and item descriptions. However, this information is unavailable in many domains and applications, and recommender systems can only tackle the
Publikováno v:
Case-Based Reasoning Research and Development ISBN: 9783031149221
Model-agnostic methods in eXplainable Artificial Intelligence (XAI) propose isolating the explanation system from the AI model architecture, typically Machine Learning or black-box models. Existing XAI libraries offer a good number of explanation met
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61c1ffef147fe8c0c995ead9b5fd70c1
https://zenodo.org/record/7797669
https://zenodo.org/record/7797669
This book constitutes the refereed proceedings of the 32nd International Conference on Case-Based Reasoning Research and Development, ICCBR 2024, held in Merida, Mexico, during July 1–4, 2024. The 29 full papers included in this book were carefu
Publikováno v:
International Journal of Interactive Multimedia and Artificial Intelligence, Vol 8, Iss 2, Pp 202-212 (2023)
Explanations in recommender systems are a requirement to improve users’ trust and experience. Traditionally, explanations in recommender systems are derived from their internal data regarding ratings, item features, and user profiles. However, this
Externí odkaz:
https://doaj.org/article/c271a0ba370f4b298b380375f02c896c
Publikováno v:
ICTAI
Classical recommender systems focus on recom- mending the most relevant items to users. An active area of research proposes to complete the recommendation process by considering additional contextual information, such as time, location, budget, weath
D1.1. Ontology requirements completed [RGU] D2.1a. Software development plan [UCM] D5.1a. Systematic review of evaluation measurements [RGU/BT] D6.1. iSee web and community network ready. [BT] D7.1a. Project Handbook [UCM] D7.2. Quality Plan [BTF] D7
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f09d5cb6e64e282fbd8ed9149e5e7a2