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Anomaly detection using fuzzy association rules., , , , and . Int. J. Electron. Secur. Digit. Forensics, 6 (1): 25-37 (2014)Generalized Association Rules for Sentiment Analysis in Twitter., , and . FQAS, volume 11529 of Lecture Notes in Computer Science, page 166-175. Springer, (2019)Detecting Anomalous and Exceptional Behaviour on Credit Data by Means of Association Rules., , , and . FQAS, volume 8132 of Lecture Notes in Computer Science, page 143-154. Springer, (2013)Bot Detection in Twitter: An Overview., , , and . FQAS, volume 14113 of Lecture Notes in Computer Science, page 131-144. Springer, (2023)A Comparative Study of Word Embeddings for the Construction of a Social Media Expert Filter., , and . FQAS, volume 12871 of Lecture Notes in Computer Science, page 196-208. Springer, (2021)Comparing Partitions by Means of Fuzzy Data Mining Tools., , , , and . SUM, volume 7520 of Lecture Notes in Computer Science, page 337-350. Springer, (2012)A Fuzzy-Based Approach for Cyberbullying Analysis., , , , , and . IPMU (2), volume 1602 of Communications in Computer and Information Science, page 317-328. Springer, (2022)Summarizing Documents Using Fractal Techniques., and . ICEIS (4), page 26-33. (2007)Improving Text Clustering Using a New Technique for Selecting Trustworthy Content in Social Networks., , , , and . IPMU (2), volume 1602 of Communications in Computer and Information Science, page 275-287. Springer, (2022)New Approaches for Discovering Exception and Anomalous Rules., , and . Int. J. Uncertain. Fuzziness Knowl. Based Syst., 19 (2): 361-399 (2011)