Zobrazeno 1 - 10
of 143
pro vyhledávání: '"Maria-Amparo Vila"'
Publikováno v:
IEEE Access, Vol 11, Pp 65891-65905 (2023)
Over the last few years, the ability of recommender systems to help us in different environments has been increasing. Several systems try to offer solutions in highly complex environments such as nutrition, housing, or traveling. In this paper, we pr
Externí odkaz:
https://doaj.org/article/1aa06d6ff1d2493f801061b40de1e38a
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 6, Iss 1 (2013)
We present a new multidimensional model with textual dimensions based on a knowledge structure extracted from the texts, where any textual attribute in a database can be processed, and not only XML texts. This dimension allows to treat the textual da
Externí odkaz:
https://doaj.org/article/41efe60ec5034c7bbe351aa3ba5e1376
Autor:
Alberto S. Ortega-Calvo, Roberto Morcillo-Jimenez, Carlos Fernandez-Basso, Karel Gutiérrez-Batista, Maria-Amparo Vila, Maria J. Martin-Bautista
Publikováno v:
Future Generation Computer Systems. 143:248-264
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1dc28fd89d82d5598eab43e09c13f00
https://doi.org/10.1016/j.future.2023.02.002
https://doi.org/10.1016/j.future.2023.02.002
Autor:
Carlos Fernandez-Basso, Karel Gutiérrez-Batista, Roberto Morcillo-Jiménez, Maria-Amparo Vila, Maria J. Martin-Bautista
Publikováno v:
Digibug. Repositorio Institucional de la Universidad de Granada
instname
instname
In this paper we have addressed the extraction of hidden knowledge from medical records using data mining techniques such as association rules in conjunction with fuzzy logic in a distributed environment. A significant challenge in this domain is tha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e6f7115b8e6d051217c29c32c9420a9
http://hdl.handle.net/10481/75585
http://hdl.handle.net/10481/75585
Medical records contain many terms which are difficult to process. Our aim in this study is to allow the visual exploration of the information in medical databases where the texts presents a large number of syntactic variations and abbreviations, thr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::033fab3d6f88a563cd62b10bbde3734a
https://doi.org/10.20944/preprints202107.0624.v1
https://doi.org/10.20944/preprints202107.0624.v1
Publikováno v:
Entropy
Entropy, Vol 23, Iss 1275, p 1275 (2021)
Digibug. Repositorio Institucional de la Universidad de Granada
instname
Volume 23
Issue 10
Entropy, Vol 23, Iss 1275, p 1275 (2021)
Digibug. Repositorio Institucional de la Universidad de Granada
instname
Volume 23
Issue 10
Medical records contain many terms that are difficult to process. Our aim in this study is to allow visual exploration of the information in medical databases where texts present a large number of syntactic variations and abbreviations by using an in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c08da5cd2f7ee54a261cce3814689bbf
https://pubmed.ncbi.nlm.nih.gov/34682000
https://pubmed.ncbi.nlm.nih.gov/34682000
Publikováno v:
IEEE Latin America Transactions. 17:648-653
Association Rules Mining is one of the most studied and widely applied fields in Data Mining. However, the discovery models usually result in a very large set of rules; so the analysis capability, from the user point of view, is diminishing. Hence, i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1bce3ea36ee46ef1d675160f68e85525
https://doi.org/10.1109/tla.2019.8891930
https://doi.org/10.1109/tla.2019.8891930
Publikováno v:
Informatica. 44
Association Rules Mining is one of the most studied and widely applied fields in Data Mining. However, the discovered models usually result in a very large set of rules; so the analysis capability, from the user point of view, is diminishing. Hence,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::320fa85b2b113b8c489c33e4859cf5f1
https://doi.org/10.31449/inf.v44i2.2839
https://doi.org/10.31449/inf.v44i2.2839
Publikováno v:
Expert Systems with Applications. 93:118-133
Due to the continuous growth of social networks the textual information available has increased exponentially. Data warehouses (DW) and online analytical processing (OLAP) are some of the established technologies to process and analyze structured dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f25b4056cf02f1658b530b45998e30fd
https://doi.org/10.1016/j.eswa.2017.10.012
https://doi.org/10.1016/j.eswa.2017.10.012
Publikováno v:
Applied Soft Computing
The continuous growth of social networks has made them one of the main information sources for researchers and companies, but at the same time, their pre-processing and analysis represent a great challenge. In this work, we create a Fuzzy Sentiment D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5850cc7cefa8c6cd53bdc52bad3d8e2b
https://doi.org/10.1016/j.asoc.2021.107390
https://doi.org/10.1016/j.asoc.2021.107390