Kişla T.Metin S.K.Karao?lan B.2019-10-262019-10-2620159781467373869https://doi.org/10.1109/SIU.2015.7130443https://hdl.handle.net/11454/172622015 23rd Signal Processing and Communications Applications Conference, SIU 2015 -- 16 May 2015 through 19 May 2015 -- 113052Automatic identification of text similarity has found applications in information retrieval, text summarization, assessment of machine translation, assessment of question answering, word sense disambiguation and many more. In this work, the results of discrimant analysis applied to find out the cumulative effect of the attributes used in the literature so far (ratio of common words, text lentgths, common word sequences, synonyms, hypernyms, hyponyms) in detecting word similarity are reported. © 2015 IEEE.tr10.1109/SIU.2015.7130443info:eu-repo/semantics/closedAccessdiscrimant analysisparaphrase corpustext similarityConference Object180183N/A