Optimizing Membership Functions using Learning Automata for Fuzzy Association Rule Mining [PDF]
Journal of Artificial Intelligence and Data Mining, 2020 The Transactions in web data often consist of quantitative data, suggesting that fuzzy set theory can be used to represent such data. The time spent by users on each web page is one type of web data, was regarded as a trapezoidal membership function (TMF)
Z. Anari +3 more
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Neutrosophic Fuzzy Association Rule Generation-Based Big Data Mining Analysis Algorithm
International Transactions on Electrical Energy Systems, 2022 As a very common and classic big data (BD) mining algorithm, the association rule data mining (DM) algorithm is often used to determine the internal correlation between different items and set a certain threshold to determine the size of the correlation.
Qunfeng Wei, Bin Qi
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Association rules of fuzzy soft set based classification for text classification problem
Journal of King Saud University: Computer and Information Sciences, 2022 Text classification is imperative in order to search for more accessible and appropriate information. It utilized in various fields, including marketing, security, biomedical, etc.
Dede Rohidin +2 more
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ck-FARM: An R package to discover big data associations for business intelligence
SoftwareX, 2023 Fuzzy association rule mining (FARM) is a well-known data mining algorithm to identify frequently occurring patterns from datasets, in which the fuzzy set theory is applied to consider linguistic variables for building an explainable reasoning system. In
George To Sum Ho +3 more
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A trust-based recommender system for e-Learning environment using fuzzy clustering [PDF]
Fanāvarī-i āmūzish, 2021 Background and Objectives: Many conventional e-Learning systems are based on static information and consider all learners the same, so they cannot meet their diverse needs and tastes.
R. Mohamadrezaei, R. Ravanmehr
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Temporal fuzzy association rule mining with 2-tuple linguistic representation [PDF]
, 2012 This paper reports on an approach that contributes towards the problem of discovering fuzzy association rules that exhibit a temporal pattern. The novel application of the 2-tuple linguistic representation identifies fuzzy association rules in a temporal
Ahmadi, Samad +3 more
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Evolving temporal fuzzy association rules from quantitative data with a multi-objective evolutionary algorithm [PDF]
, 2011 A novel method for mining association rules that are both quantitative and temporal using a multi-objective evolutionary algorithm is presented. This method successfully identifies numerous temporal association rules that occur more frequently in areas ...
C. Carmona +8 more
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Multidimensional Time Series Fuzzy Association Rules Mining [PDF]
, 2015 In this paper, we present a new solution, in which the fuzziness of both subsequences and subsequences interval has been taken into consideration for solving the problem of multidimensional time series fuzzy association rules mining.
Gao, Xuedong, Guo, Hongwei
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Incremental Fuzzy Association Rule Mining for Classification and Regression
IEEE Access, 2019 The aim of mining fuzzy association rules is to find both the association and the casual relationships between the itemsets. With the arrival of dynamic data, the fuzzy association rules should be updated in real time.
Ling Wang, Qian Ma, Jianyao Meng
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Selection of Satisfied Association Rules via Aggregation of Linguistic Satisfied Degrees
IEEE Access, 2019 Many association rule mining algorithms have been well-established, such as Apriori, Eclat, FP-Growth, or LCM algorithms. However, the challenge is that the huge size of association rules is extracted by using these algorithms, and it is difficult for ...
Fangling Ren, Zheng Pei, Kehong Wu
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