Results 271 to 280 of about 6,305 (306)
Some of the next articles are maybe not open access.
On Fuzzy Modus Ponens to Assess Fuzzy Association Rules
2015Fuzzy association rules provide a meaningful tool to represent new useful information extracted from raw data and expressed in a comprehensive way for a decision maker. In this paper we propose an approach to assess Fuzzy Association Rules by using the theoretical results by Trillas et al. about the Fuzzy Modus Ponens.
Miguel Delgado 0001 +3 more
openaire +1 more source
On a Fuzzy Group-By and Its Use for Fuzzy Association Rule Mining
2010Group-by is a core database operation that is used extensively in data analysis and decision support systems. In many application scenarios, it appears useful to group values according to their compliance with a certain concept instead of founding the grouping on value equality.
Bosc, Patrick +2 more
openaire +2 more sources
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
openaire +1 more source
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
Ferenc Peter Pach +2 more
openaire +1 more source
Mining fuzzy association rules in incomplete databases
2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291), 2003Mining quantitative association rules is a particular subject of interest in fuzzy set application theory. However, the theory generally applies to a transactional database with no missing values. A predictive algorithm is proposed in this paper in order to extrapolate (interpolate) the unknown values.
openaire +2 more sources
Botnet Detection based on Fuzzy Association Rules
2018 24th International Conference on Pattern Recognition (ICPR), 2018Difficult to be detected in complex network environments, botnets have been huge threats to network security. As the circumscriptions of normal traffics and botnet traffics are blurring, the commonly used botnet detection methods based on traffic analysis often result in high false positive rates.
Jiazhong Lu +4 more
openaire +1 more source
Fuzzy association rules and the extended mining algorithms
Information Sciences, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Guoqing Chen, Qiang Wei 0001
openaire +1 more source
Lift Measure for Fuzzy Association Rules
2015The aim of this paper is to provide a correct definition of lift measure for fuzzy association rules, to study some of it’s interesting mathematical properties, and to provide an algorithm for fast computation of fuzzy lift during the process of fuzzy association rules mining.
openaire +1 more source
Hiding Fuzzy Association Rules in Quantitative Data
2008 The 3rd International Conference on Grid and Pervasive Computing - Workshops, 2008Data mining and knowledge discovery from databases are researches in which unknown associations automatically discovered from big amounts of data. Advances in data collection, data distribution and related technologies caused researchers to investigate current data mining algorithms from a new point of view. This is personal privacy.
Tolga Berberoglu, Mehmet Kaya
openaire +1 more source
Fuzzy System Based on Class Association Rules
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 2007Fuzzy system has been proved to be a universal approximator, yet the curse of dimensionality is still the unsolved problem for it. Class association rules (CARs) are interesting and frequent patterns derived from data through adapted Apriori algorithm. Using CARs to build the fuzzy rule base of fuzzy system can solve the curse of dimensionality problem
Ren Jia, Yibo Zhang
openaire +1 more source