Kumova S.Karaoglan B.Kisla T.2023-06-162023-06-1620169.78E+12https://doi.org/10.1109/SIU.2016.7496009https://hdl.handle.net/20.500.14365/359924th Signal Processing and Communication Application Conference, SIU 2016 -- 16 May 2016 through 19 May 2016 -- 122605Identification of paraphrase sentence pairs becomes increasingly prominent in natural language processing area (e.g plagiarism detection, summarization, machine translation). In this study, it is proposed to employ information gain measure in determining the value-ranges of the paraphrase classification features on the renown paraphrase corpus of Microsoft Research (MSRP). The classification performances of value-ranges that are determined by information gain measure and an alternative heuristic method are compared by the use of Bayes classifier. The results show that the proposed method performs better than the heuristic method. © 2016 IEEE.trinfo:eu-repo/semantics/closedAccessBayesian classificationfeaturesinformation gainparaphraseparaphrase sentence pairsHeuristic methodsNatural language processing systemsSignal detectionSignal processingBayesian classificationfeaturesInformation gainparaphraseparaphrase sentence pairsClassification (of information)Conference Object10.1109/SIU.2016.74960092-s2.0-84982833742