Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Mondher Maddouri"'
Publikováno v:
Future Generation Computer Systems
Future Generation Computer Systems, 2022, 134, pp.334-347. ⟨10.1016/j.future.2022.04.013⟩
Future Generation Computer Systems, 2022, 134, pp.334-347. ⟨10.1016/j.future.2022.04.013⟩
International audience; Graph clustering is one of the key techniques to understand structures that are presented in networks. In addition to clusters, bridges and outliers detection is also a critical task as it plays an important role in the analys
Publikováno v:
International Journal of Artificial Intelligence and Machine Learning. 11:38-62
Knowledge discovery data (KDD) is a research theme evolving to exploit a large data set collected every day from various fields of computing applications. The underlying idea is to extract hidden knowledge from a data set. It includes several tasks t
Autor:
Mondher Maddouri, Ali Jaoua
Publikováno v:
Industrial and Engineering Applications of Artificial Intelligence and Expert Systems ISBN: 9780429332111
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cc5a27b575c987c2c24a1ef1ac4afca7
https://doi.org/10.1201/9780429332111-52
https://doi.org/10.1201/9780429332111-52
Autor:
Mondher Maddouri, Nida Meddouri
Publikováno v:
International Journal of Artificial Intelligence and Machine Learning. 10:79-98
Knowledge discovery in databases (KDD) aims to exploit the large amounts of data collected every day in various fields of computing application. The idea is to extract hidden knowledge from a set of data. It gathers several tasks that constitute a pr
Publikováno v:
Journal of Computational Biology. 26:561-571
Studying protein structures is a major asset for understanding the molecular mechanisms of life. The number of publicly available protein structures has increasingly become extremely large. Yet, the classification of a protein structure remains a dif
Publikováno v:
KES
Ionizing-radiation-resistant bacteria (IRRB) could be used for bioremediation of radioactive wastes and in the therapeutic industry. Limited computational works are available for the prediction of bacterial ionizing radiation resistance (IRR). In thi
Publikováno v:
Frontiers in Artificial Intelligence and Applications (FAIA)
International Conference on Machine Learning and Intelligent Systems
International Conference on Machine Learning and Intelligent Systems, Jong-Ha Lee, Prof, Oct 2020, Seoul, South Korea
MLIS
International Conference on Machine Learning and Intelligent Systems
International Conference on Machine Learning and Intelligent Systems, Jong-Ha Lee, Prof, Oct 2020, Seoul, South Korea
MLIS
International audience; Classification is a data mining task and which is a two-phase process: learning and classification. The learning phase consists of constructing a classifier or a model from a labeled set of objects. The classification phase co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99d5519cbec313b279ed94a556e8c0be
https://hal.archives-ouvertes.fr/hal-02935480
https://hal.archives-ouvertes.fr/hal-02935480
Autor:
Mondher Maddouri, Ali Jaoua
Publikováno v:
Industrial and Engineering Applications of Artificial Intelligence and Expert Systems ISBN: 9780429332197
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8836c5fc68ad6e44919e9801d2da4f0f
https://doi.org/10.1201/9780429332197-32
https://doi.org/10.1201/9780429332197-32
Publikováno v:
KES
The high dimension of data makes difficult to train and test many classification methods. This work aims to present a new filter Feature Selection Method, called H-Ratio, which can identify pertinent features from data. This method improves results o
Graph clustering is one of the key techniques to understand the structures present in the graph data. In addition to cluster detection, the identification of hubs and outliers is also a critical task as it plays an important role in the understanding
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2885::2556a45c931bbbd920ca74e496cd188d
https://hal.inria.fr/hal-02190913v2/document
https://hal.inria.fr/hal-02190913v2/document