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26th IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 02-05, 2018 -- Izmir, TURKEY WOS:000511448500654 Text generation systems provide facilities such as making new information deductions from the existing ones, getting information related to them by going out to a knowledgeable way, and generating more detailed results about the calls to the users by generating the codes entered on the internet. In this study, it is aimed to generate meaningful new Turkish sentences using class-based n-gram model from the sentences in the source data set. In order to realize sentence production, a trigram model is proposed and sentences are generated from the word or word groups in the sentence to the number of groups related to it. Thus, new sentences are generated, none of which were identical to the others. IEEE, Huawei, Aselsan, NETAS, IEEE Turkey Sect, IEEE Signal Proc Soc, IEEE Commun Soc, ViSRATEK, Adresgezgini, Rohde & Schwarz, Integrated Syst & Syst Design, Atilim Univ, Havelsan, Izmir Katip Celebi Univ |
