Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Raudel Hernández León"'
Publikováno v:
Advances in Computational Intelligence ISBN: 9783031194955
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3bf9c78fc2bc918231c5a36673b3a651
https://doi.org/10.1007/978-3-031-19496-2_24
https://doi.org/10.1007/978-3-031-19496-2_24
Publikováno v:
Computers & Electrical Engineering, 101
We live in a world that is being driven by data. This leads to challenges of extracting and analyzing knowledge from large volumes of data. An example of such a challenge is intrusion detection. Intrusion detection data sets are characterized by huge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8eee640b107eb8633c2a1dbd85346bb4
http://resolver.tudelft.nl/uuid:b7474843-2bca-48bd-b1f6-a2dc9b68a661
http://resolver.tudelft.nl/uuid:b7474843-2bca-48bd-b1f6-a2dc9b68a661
Autor:
Raudel Hernández-León, Lázaro Bustio-Martínez, Claudia Feregrino-Uribe, René Cumplido, Alfredo Muñoz-Briseño
Publikováno v:
Pattern Recognition Letters. 125:241-248
Data streams are modern data sources that are gaining attention as a consequence of their many practical applications (they can be found in data transmission, eCommerce, and intrusion detection system among others). Nevertheless, the efforts to obtai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::222b16dc47daacc5a7983fd1761e83da
https://doi.org/10.1016/j.patrec.2019.05.003
https://doi.org/10.1016/j.patrec.2019.05.003
Autor:
José M. Bande-Serrano, Lázaro Bustio-Martínez, Martin Letras-Luna, René Cumplido, Raudel Hernández-León, Claudia Feregrino-Uribe
Publikováno v:
Journal of Parallel and Distributed Computing. 125:58-71
Frequent Itemsets Mining is a Data Mining technique that has been employed to extract useful knowledge from datasets and, more recently, also from data streams. Data streams are unbounded and infinite flows of data arriving at high rates which cannot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::894b864b289d719e569da207a63fb567
https://doi.org/10.1016/j.jpdc.2018.11.002
https://doi.org/10.1016/j.jpdc.2018.11.002
Publikováno v:
Knowledge-Based Systems, 227
Every day the number of devices interacting through telecommunications networks grows resulting into an increase in the volume of data and information generated. At the same time, a growing number of information security incidents is being observed i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a0f6d5d8dd7bbbde58b4c638fe2846f6
https://doi.org/10.1016/j.knosys.2021.107264
https://doi.org/10.1016/j.knosys.2021.107264
Autor:
Raudel Hernández-León, Vitali Herrera-Semenets, Andrés Gago-Alonso, Osvaldo Andrés Pérez-García
Publikováno v:
Intelligent Data Analysis. 21:1141-1154
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c414c55fcf787e32ae265b53fd4a8230
https://doi.org/10.3233/ida-163137
https://doi.org/10.3233/ida-163137
Autor:
Raudel Hernández-León, Lázaro Bustio-Martínez, René Cumplido, José M. Bande-Serrano, Claudia Feregrino-Uribe
Publikováno v:
Journal of Intelligent Information Systems. 50:415-440
Frequent Itemsets Mining has been applied in many data processing applications with remarkable results. Recently, data streams processing is gaining a lot of attention due to its practical applications. Data in data streams are transmitted at high ra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9756a1cdcfbf4df84a450b6793197f6
https://doi.org/10.1007/s10844-017-0461-8
https://doi.org/10.1007/s10844-017-0461-8
Autor:
Raudel Hernández-León, Claudia Feregrino-Uribe, Lázaro Bustio-Martínez, Martin Letras, René Cumplido
Publikováno v:
Expert Systems with Applications. 157:113440
Algorithms for Frequent Itemsets Mining have proved their effectiveness for extracting frequent sets of patterns in datasets. However, in some specific cases, they do not obtain the expected results in an acceptable time. For this reason, Field Progr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::522116924c2e373e214ca69e18def862
https://doi.org/10.1016/j.eswa.2020.113440
https://doi.org/10.1016/j.eswa.2020.113440
Autor:
Raudel Hernández-León, Osvaldo Andrés Pérez-García, Andrés Gago-Alonso, Vitali Herrera-Semenets
Publikováno v:
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications ISBN: 9783319751924
CIARP
CIARP
The presence of useless information and the huge amount of data generated by telecommunication services can affect the efficiency of traditional Intrusion Detection Systems (IDSs). This fact encourage the development of data preprocessing strategies
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::932876c9f8a8635132bf8cca5afedabe
https://doi.org/10.1007/978-3-319-75193-1_35
https://doi.org/10.1007/978-3-319-75193-1_35
Autor:
Lázaro Bustio-Martínez, Claudia Feregrino Uribe, René Cumplido, Martin Letras-Luna, José M. Bande-Serrano, Raudel Hernández-León
Publikováno v:
LASCAS
Frequent Itemsets Mining is a Data Mining technique that has been employed to extract useful knowledge from datasets; and recently, from data streams. Data streams are an unbounded and infinite flow of data arriving at high rates; therefore, traditio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::13d9d0564452f336fed0ff2251432676
https://doi.org/10.1109/lascas.2017.7948076
https://doi.org/10.1109/lascas.2017.7948076