Kisla, TarikMetin, Senem KumovaKaraoglan, Bahar2023-06-162023-06-162015978-1-4673-7386-92165-0608https://hdl.handle.net/20.500.14365/320723nd Signal Processing and Communications Applications Conference (SIU) -- MAY 16-19, 2015 -- Inonu Univ, Malatya, TURKEYAutomatic 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.trinfo:eu-repo/semantics/closedAccesstext similarityparaphrase corpusdiscrimant analysisConference Object10.1109/SIU.2015.71304432-s2.0-84939180034