Machine learning and big data provide crucial insight for future biomaterials discovery and research
J Kerner, A Dogan, H von Recum - Acta Biomaterialia, 2021 - Elsevier
Abstract Machine learning have been widely adopted in a variety of fields including
engineering, science, and medicine revolutionizing how data is collected, used, and stored …
engineering, science, and medicine revolutionizing how data is collected, used, and stored …
[HTML][HTML] A survey of big data dimensions vs social networks analysis
The pervasive diffusion of Social Networks (SN) produced an unprecedented amount of
heterogeneous data. Thus, traditional approaches quickly became unpractical for real life …
heterogeneous data. Thus, traditional approaches quickly became unpractical for real life …
[HTML][HTML] A recommendation system in e-commerce with profit-support fuzzy association rule mining (p-farm)
O Dogan - Journal of Theoretical and Applied Electronic …, 2023 - mdpi.com
E-commerce is snowballing with advancements in technology, and as a result,
understanding complex transactional data has become increasingly important. To keep …
understanding complex transactional data has become increasingly important. To keep …
[HTML][HTML] A survey on the use of association rules mining techniques in textual social media
The incursion of social media in our lives has been much accentuated in the last decade.
This has led to a multiplication of data mining tools aimed at obtaining knowledge from these …
This has led to a multiplication of data mining tools aimed at obtaining knowledge from these …
Aimdp: An artificial intelligence modern data platform. use case for Spanish national health service data silo
AS Ortega-Calvo, R Morcillo-Jimenez… - Future Generation …, 2023 - Elsevier
The huge amount of data being handled today in any environment, such as energy,
economics or healthcare, makes data management systems key to extracting information …
economics or healthcare, makes data management systems key to extracting information …
Damped sliding based utility oriented pattern mining over stream data
High utility pattern mining (HUPM) discovers meaningful patterns by considering features of
items and utility from non-binary data. Data called stream data is continually generated over …
items and utility from non-binary data. Data called stream data is continually generated over …
[HTML][HTML] New spark solutions for distributed frequent itemset and association rule mining algorithms
The large amount of data generated every day makes necessary the re-implementation of
new methods capable of handle with massive data efficiently. This is the case of Association …
new methods capable of handle with massive data efficiently. This is the case of Association …
[HTML][HTML] SWEclat: a frequent itemset mining algorithm over streaming data using Spark Streaming
W Xiao, J Hu - The Journal of Supercomputing, 2020 - Springer
Finding frequent itemsets in a continuous streaming data is an important data mining task
which is widely used in network monitoring, Internet of Things data analysis and so on. In the …
which is widely used in network monitoring, Internet of Things data analysis and so on. In the …
Multigranulation consensus fuzzy-rough based attribute reduction
W Ding, J Wang, J Wang - Knowledge-Based Systems, 2020 - Elsevier
As big data often contains a significant amount of unstructured, imprecise, and uncertain
data, the fuzzy-rough-set-based attribute reduction is a valuable technique for uncertainty …
data, the fuzzy-rough-set-based attribute reduction is a valuable technique for uncertainty …
Big data architecture for building energy management systems
MD Ruiz, J Gómez-Romero… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
The enormous quantity of data handled by building management systems are key to
develop more efficient energy operational systems. However, the inability of current systems …
develop more efficient energy operational systems. However, the inability of current systems …