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Mining Association Rules using Lattice Theory (6th Workshop on Stochastic Numerics)
Mining Association Rules using Lattice Theory (6th Workshop on Stochastic Numerics)openaire +1 more source
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Toward Anomaly Detection in the Blockchain Using Numerical Association Rule Mining
2023 IEEE 21st Jubilee International Symposium on Intelligent Systems and Informatics (SISY), 2023With the global increase in the popularity of cryptocurrencies, the need for anomaly detection and fraudulent behavior is reaching an all-time high. In our paper, we propose a novel method of anomaly detection with the use of Numerical Association Rule ...
Iztok Fister, Jr. +2 more
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Time Series Numerical Association Rule Mining for assisting Smart Agriculture
2022 International Conference on Electrical, Computer and Energy Technologies (ICECET), 2022Smart agriculture is a modern paradigm that incorporates modern technologies ranging from cloud computing, big data, Internet of Things, or data mining, among others.
Sancho Salcedo-Sanz, Iztok Fister, Jr.
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A Systematic Assessment of Numerical Association Rule Mining Methods
SN Computer Science, 2021In data mining, the classical association rule mining techniques deal with binary attributes; however, real-world data have a variety of attributes (numerical, categorical, Boolean). To deal with the variety of data attributes, the classical association rule mining technique was extended to numerical association rule mining.
Sadok Ben Yahya +2 more
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TinyNARM: Simplifying Numerical Association Rule Mining for Running on Microcontrollers
Lecture Notes in Networks and Systems, 2023Akemi Galvez Tomida, Andrés Iglesias
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On the Potential of Numerical Association Rule Mining
Communications in Computer and Information Science, 2020In association rule mining, both the classical algorithms and today’s available tools either use binary data items or discretized data. However, in real-world scenarios, data are available in many different forms (numerical, text) and these types of data items are not supported in the classical association rule mining algorithms.
Sadok Ben Yahya +2 more
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2025 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA)
In Numerical Association Rule Mining, some attributes are more inclined to disappear. These attributes are inclined to disappear primarily when rules consist of a small value of support or confidence. These kinds of attributes are mainly discrete.
Andrés Iglesias
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In Numerical Association Rule Mining, some attributes are more inclined to disappear. These attributes are inclined to disappear primarily when rules consist of a small value of support or confidence. These kinds of attributes are mainly discrete.
Andrés Iglesias
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Improving Association Rule Mining Using Clustering-based Discretization of Numerical Data
2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC), 2018Association rule mining is an important data mining technique that help discover interesting attribute relationships that are useful for decision making.
Swee Chuan Tan
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Information Sciences, 2021
In association rules mining from data that have numeric-valued attributes, automatically adjusting the attribute intervals at the time of the mining process without a preprocess is very critical for preventing data loss and attribute interactions.
Elif Varol Altay, Bilal Alatas
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In association rules mining from data that have numeric-valued attributes, automatically adjusting the attribute intervals at the time of the mining process without a preprocess is very critical for preventing data loss and attribute interactions.
Elif Varol Altay, Bilal Alatas
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Differential Evolution for Association Rule Mining Using Categorical and Numerical Attributes
Lecture Notes in Computer Science, 2018Association rule mining is a method for identification of dependence rules between features in a transaction database. In the past years, researchers applied the method using features consisting of categorical attributes. Rarely, numerical attributes were used in these studies.
Eneko Osaba +2 more
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