Combines the Apriori and FCM Algorithm to Improve the Extracted Association Rules with Determine the Minimum Support Automatically [PDF]
Journal of Information Technology Management, 2015 Apriori algorithm is the most popular algorithm in association rules mining. One of the problems the Apriori algorithm is that the user must specify a minimum support threshold.
Heydar Jafarzadeh +2 more
doaj +1 more source
Quality measures for fuzzy predicates in conjunctive and disjunctive normal forms
Ingeniería e Investigación, 2014 Association rule mining is a very popular data mining technique. Rules in this technique are often used to identify and represent de-pendencies between attributes in databases.
Taymi Ceruto Cordovés +2 more
doaj +1 more source
A Strategic Study of Mining Fuzzy Association Rules Using Fuzzy Multiple Correlation Measues
Journal of Algorithms & Computational Technology, 2012 Two different data variables may behave very similarly. Correlation is the problem of determining how much alike the two variables actually are and association rules are used just to show the relationships between data items.
Robinson P. John +2 more
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Mining Fuzzy Coherent Rules from Quantitative Transactions Without Minimum Support Threshold [PDF]
, 2012 Many fuzzy data mining approaches have been proposed for finding fuzzy association rules with the predefined minimum support from the give quantitative transactions. However, some comment problems of those approaches are that (1) a minimum support should
Chen, Chun-hao, Chne, Chun-hao
core +1 more source
Recommendation with quantitative implication rules [PDF]
EAI Endorsed Transactions on Context-aware Systems and Applications, 2019 Association rules based recommendation is one of approaches to develop recommendation systems. However, such systems just focus on binary dataset, whereas many datasets are in the quantitative form. There are many solutions proposed for this problem such
Hoang Nguyen +3 more
doaj +1 more source
International Journal of Interactive Multimedia and Artificial Intelligence, 2022 Association rule mining is an important data mining technique used for discovering relationships among all data items. Membership functions have a significant impact on the outcome of the mining association rules.
Zohreh Anari +2 more
doaj +1 more source
Cluster-Based Membership Function Acquisition Approaches for Mining Fuzzy Temporal Association Rules
IEEE Access, 2020 In real-world applications, transactions are typically represented by quantitative data. Thus, fuzzy association rule mining algorithms have been proposed to handle these quantitative transactions.
Chun-Hao Chen +3 more
doaj +1 more source
Developing a Course Recommender by Combining Clustering and Fuzzy Association Rules [PDF]
Journal of Artificial Intelligence and Data Mining, 2019 Each semester, students go through the process of selecting appropriate courses. It is difficult to find information about each course and ultimately make decisions.
Sh. Asadi +2 more
doaj +1 more source
Neuro-fuzzy knowledge processing in intelligent learning environments for improved student diagnosis [PDF]
, 2005 In this paper, a neural network implementation for a fuzzy logic-based model of the diagnostic process is proposed as a means to achieve accurate student diagnosis and updates of the student model in Intelligent Learning Environments.
Grigoriadou, M. +3 more
core +2 more sources
Survey of data mining approaches to user modeling for adaptive hypermedia [PDF]
, 2006 The ability of an adaptive hypermedia system to create tailored environments depends mainly on the amount and accuracy of information stored in each user model.
Chen, SY, Frias-Martinez, E, Liu, X
core +3 more sources