Hark, C.Seyyarer, A.Uçkan, T.Karci, A.2025-05-102025-05-102017978153861880610.1109/IDAP.2017.80903062-s2.0-85039902661https://doi.org/10.1109/IDAP.2017.8090306https://hdl.handle.net/20.500.14720/5062Unstructured document and archive stacks that are formed in the past years are growing in size faster these days and they need to be clarified with various methods. This increases the interest in natural language processing discipline day by day and makes it more popular. In this study, we've tried to calculate the similarities between document stacks, that no information is presented onbehalf of their similarities and are completely independent of each other. Text mining approaches have been utilized in order to calculate the similarities of non-structural documents given. For this purpose, the R programming language labels have been used to structure only text based documents stacks in order to make them proccessable and to determine their similiraties afterwards. © 2017 IEEE.trinfo:eu-repo/semantics/closedAccessData MiningDocument StacksDocuments SimilaritiesNatural Language ProcessingR Programming LanguageConference ObjectN/AN/A