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Fuzzy Functional Dependencies and Fuzzy Association Rules
1999This paper proposes fuzzy association rule which is a more generalized concept than boolean, quantitative, and interval association rules. Fuzzy association rule is a spectrum of definitions. Each particular fuzzy association rule can be defined by adding restrictions on the fuzziness depending on the needs of practical situations.
Yuping Yang, Mukesh Singhal
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Anomaly detection using fuzzy association rules
International Journal of Electronic Security and Digital Forensics, 2014Data mining techniques are a very important tool for extracting useful knowledge from databases. Recently, some approaches have been developed for mining novel kinds of useful information, such as anomalous rules. These kinds of rules are a good technique for the recognition of normal and anomalous behaviour, that can be of interest in several area ...
M. Dolores Ruiz +4 more
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Hybrid Approach for Intrusion Detection Using Fuzzy Association Rules
Cyber Security in Networking Conference, 2018Rapid development of internet and network technologies has led to considerable increase in number of attacks. Intrusion detection system is one of the important ways to achieve high security in computer networks.
Samira Douzi +2 more
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Mining fuzzy quantitative association rules
Proceedings 11th International Conference on Tools with Artificial Intelligence, 2003Given a relational database and a set of fuzzy terms defined for some attributes we consider the problem of mining fuzzy quantitative association rules that may contain crisp values, intervals, and fuzzy terms in both antecedent and consequent. We present an algorithm extended from the equi-depth partition (EDP) algorithm for solving this problem.
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Evaluating Fuzzy Association Rules on XML Documents
2006In this work we propose a flexible approach to evaluate association rules on XML documents. In particular we describe evaluation techniques in order to assign a satisfiability degree to structural association rules, which allow one to evaluate the similarity of the XML document with respect to a given structure, and to value association rules which ...
COMBI, Carlo +2 more
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Incremental update for fuzzy association rules
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693), 2004In practice, many databases are not static but changeable. When some records are added or deleted in a database, it could potentially invalidate some existing rules or introduce new rules. Thus, maintenance of the association rules is an important problem. An incremental update algorithm for the fuzzy association rules is presented; this algorithm uses
null Jian-Jiang Lu, null Bao-Wen Xu
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Compact fuzzy association rule-based classifier
Expert Systems with Applications, 2008Classification is one of the most popular data mining techniques applied to many scientific and industrial problems. The efficiency of a classification model is evaluated by two parameters, namely the accuracy and the interpretability of the model. While most of the existing methods claim their accurate superiority over others, their models are usually
F PACH, A GYENESEI, J ABONYI
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Fuzzy Association Rules Mining Using Spark
2018Discovering new trends and co-occurrences in massive data is a key step when analysing social media, data coming from sensors, etc. Traditional Data Mining techniques are not able, in many occasions, to handle such amount of data. For this reason, some approaches have arisen in the last decade to develop parallel and distributed versions of previously ...
Carlos Fernandez-Bassso +2 more
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Intrusion detection using fuzzy association rules
Applied Soft Computing, 2009Vulnerabilities in common security components such as firewalls are inevitable. Intrusion Detection Systems (IDS) are used as another wall to protect computer systems and to identify corresponding vulnerabilities. In this paper, a novel framework based on data mining techniques is proposed for designing an IDS.
Arman Tajbakhsh +2 more
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