Publication:
An Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Weka

dc.contributor.authorZainal K.en_US
dc.contributor.authorSulaiman N.F.en_US
dc.contributor.authorJali M.Z.en_US
dc.date.accessioned2024-05-27T15:07:06Z
dc.date.available2024-05-27T15:07:06Z
dc.date.issued2015
dc.date.submitted--
dc.description.abstractThis paper reported and summarized findings of spam management for Short Message Service (SMS) which consists of classification and clustering of spam using two different tools, namely RapidMiner and Weka. By using the same dataset, which is downloaded from UCI, Machine Learning Repository, various algorithms used in classification and clustering in this simulation has been analysed comparatively. From the simulation, both tools giving the similar results that the same classifiers are the best for SMS spam classification and clustering which are outperformed than other algorithms. . Keywords- SMS spam; RapidMiner; Weka; Naïve Bayesian (NB); Support Vector Machine (SVM); k-Nearest Neighbour (kNN); K-Mean; Cobweb; Hierarchical clustering; spam classification; spam clustering. .en_US
dc.identifier.citation(IJCSIS) International Journal of Computer Science and Information Security,Vol. 13, No. 3, March 2015en_US
dc.identifier.epage74
dc.identifier.issn1947-5500
dc.identifier.issue3
dc.identifier.other429-13
dc.identifier.spage66
dc.identifier.urihttps://sites.google.com/site/ijcsis/all-volumes-issues/vol-13-no-3-mar-2015
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/4167
dc.identifier.volume13
dc.language.isoenen_US
dc.publisherInternational Journal of Computer Science & Information Securityen_US
dc.relation.ispartofInternational Journal of Computer Science & Information Security (IJCSIS)en_US
dc.subjectSMS spam;en_US
dc.subjectRapidMiner;en_US
dc.subjectWeka;en_US
dc.subjectNaïve Bayesian (NB);en_US
dc.subjectSupport Vector Machine (SVM);en_US
dc.subjectk-Nearest Neighbour (kNN);en_US
dc.subjectK-Mean; Cobweb;en_US
dc.subjectHierarchical clustering;en_US
dc.subjectspam classification;en_US
dc.subjectspam clustering. .en_US
dc.titleAn Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Wekaen_US
dc.typeArticleen_US
dspace.entity.typePublication

Files