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text2arff: A Text Representation Library

dc.contributor.authorCan, Ender
dc.contributor.authorAmasyali, Mehmet Fatih
dc.date.accessioned2026-06-27T13:58:11Z
dc.date.issued2016
dc.description.abstractWhich features are the most important for the text classification tasks? In the automatic text categorization area, several studies seek answers to this question. In this paper, new version of Text2arff (a library for text representation) and its new features (word2vec, Word trajectories, etc.) are presented. Also, the software is now a java library which can be used in the user's own projects. In the experiments, the library is run on two sample datasets. The results show that the effect of text representation method is bigger than the classification method. This result also emphasizes the importance of developing new test representation methods.en
dc.identifier.endpage200
dc.identifier.isbn978-1-5090-1679-2
dc.identifier.startpage197
dc.identifier.urihttps://hdl.handle.net/20.500.14981/56054
dc.identifier.wos000391250900027
dc.language.isotur
dc.publisherIEEE
dc.relation.conference24th Signal Processing and Communication Application Conference (SIU)
dc.relation.ispartof2016 24TH SIGNAL PROCESSING AND COMMUNICATION APPLICATION CONFERENCE (SIU)
dc.subjecttext classification
dc.subjectmachine learning
dc.subjectnatural language processing
dc.subjectEngineering
dc.titletext2arff: A Text Representation Library
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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