FFTM: A Fuzzy Feature Transformation Method for Medical Documents

dc.contributor.authorKarami, Amir
dc.contributor.authorGangopadhyay, Aryya
dc.date.accessioned2021-08-16T17:59:13Z
dc.date.available2021-08-16T17:59:13Z
dc.date.issued2014-06
dc.descriptionProceedings of the 2014 Workshop on Biomedical Natural Language Processing (BioNLP 2014), pages 128–133, Baltimore, Maryland USA, June 26-27 2014en_US
dc.description.abstractThe vast array of medical text data represents a valuable resource that can be analyzed to advance the state of the art in medicine. Currently, text mining methods are being used to analyze medical research and clinical text data. Some of the main challenges in text analysis are high dimensionality and noisy data. There is a need to develop novel feature transformation methods that help reduce the dimensionality of data and improve the performance of machine learning algorithms. In this paper we present a feature transformation method named FFTM. We illustrate the efficacy of our method using local term weighting, global term weighting, and Fuzzy clustering methods and show that the quality of text analysis in medical text documents can be improved. We compare FFTM with Latent Dirichlet Allocation (LDA) by using two different datasets and statistical tests show that FFTM outperforms LDA.en_US
dc.description.urihttps://aclanthology.org/W14-3419/en_US
dc.format.extent6 pagesen_US
dc.genreconference papers and proceedingsen_US
dc.identifierdoi:10.13016/m2weqy-sndp
dc.identifier.citationKarami, Amir; Gangopadhyay, Aryya; FFTM: A Fuzzy Feature Transformation Method for Medical Documents; Proceedings of BioNLP 2014, pages 128-133, June, 2014; http://dx.doi.org/10.3115/v1/W14-3419en_US
dc.identifier.urihttp://dx.doi.org/10.3115/v1/W14-3419
dc.identifier.urihttp://hdl.handle.net/11603/22457
dc.language.isoen_USen_US
dc.publisherAssociation for Computational Linguisticsen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.en_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)*
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/3.0/*
dc.titleFFTM: A Fuzzy Feature Transformation Method for Medical Documentsen_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0003-1936-7497en_US

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