Feature selection using chaotic salp swarm algorithm for data classification

AE Hegazy, MA Makhlouf, GS El-Tawel - Arabian Journal for Science and …, 2019 - Springer
Salp swarm algorithm (SSA) is a recently created bio-inspired optimization algorithm
presented in 2017 which is based on the swarming mechanism of salps. Despite high …

GDPR compliant information confidentiality preservation in big data processing

L Caruccio, D Desiato, G Polese, G Tortora - IEEE Access, 2020 - ieeexplore.ieee.org
Nowadays, new laws and regulations, such as the European General Data Protection
Regulation (GDPR), require companies to define privacy policies complying with the …

Mining relaxed functional dependencies from data

L Caruccio, V Deufemia, G Polese - Data Mining and Knowledge …, 2020 - Springer
Relaxed functional dependencies (rfd s) are properties expressing important relationships
among data. Thanks to the introduction of approximations in data comparison and/or validity …

Fake account identification in social networks

L Caruccio, D Desiato, G Polese - 2018 IEEE international …, 2018 - ieeexplore.ieee.org
Nowadays, the human influence often depends on the number of followers that an individual
has in his/her own social media context. To this end, the presence of fake accounts is one of …

Incremental discovery of imprecise functional dependencies

L Caruccio, S Cirillo - Journal of Data and Information Quality (JDIQ), 2020 - dl.acm.org
Functional dependencies (fds) are one of the metadata used to assess data quality and to
perform data cleaning operations. However, to pursue robustness with respect to data …

Association Rule Mining through Combining Hybrid Water Wave Optimization Algorithm with Levy Flight

Q He, J Tu, Z Ye, M Wang, Y Cao, X Zhou, W Bai - Mathematics, 2023 - mdpi.com
Association rule mining (ARM) is one of the most important tasks in data mining. In recent
years, swarm intelligence algorithms have been effectively applied to ARM, and the main …

[PDF][PDF] Incremental Discovery of Functional Dependencies with a Bit-vector Algorithm.

L Caruccio, S Cirillo, V Deufemia, G Polese - SEBD, 2019 - academia.edu
Functional dependencies (fds) were conceived in the early'70s, and were mainly used to
verify database design and assess data quality. Nowadays they are automatically …

Dataprism: Exposing disconnect between data and systems

S Galhotra, A Fariha, R Lourenço, J Freire… - Proceedings of the …, 2022 - dl.acm.org
As data is a central component of many modern systems, the cause of a system malfunction
may reside in the data, and, specifically, particular properties of data. Eg, a health …

Conformance constraint discovery: Measuring trust in data-driven systems

A Fariha, A Tiwari, A Radhakrishna, S Gulwani… - Proceedings of the …, 2021 - dl.acm.org
The reliability of inferences made by data-driven systems hinges on the data's continued
conformance to the systems' initial settings and assumptions. When serving data (on which …

Functional Dependencies with Predicates: What Makes the g3-error Easy to Compute?

S Vilmin, P Faure–Giovagnoli, JM Petit… - … on Conceptual Structures, 2023 - Springer
The notion of functional dependencies (FDs) can be used by data scientists and domain
experts to confront background knowledge against data. To overcome the classical, too …