Browsing by Author "Karbeyaz, Ceyhun"

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    A content-based social network study of evliyâ çelebi's seyahatnâme-bitlis section
    (Springer, London, 2012) Karbeyaz, Ceyhun; Can, Ethem F; Can, Fazlı; Kalpaklı, Mehmet
    Evliyâ Çelebi, an Ottoman writer, scholar and world traveler, visited most of the territories and also some of the neighboring countries of the Ottoman Empire in the seventeenth century. He took notes about his trips and wrote a 10-volume book called Seyahatnâme (Book of Travels). In this paper, we present two methods for constructing social networks by using textual data and apply it to Seyahatnâme-Bitlis Section from book IV. The first social network construction method is based on proximity of co-occurence of names. The second method is based on 2-pair associations obtained by association rule mining by using sliding text blocks as transactions. The social networks obtained by these two methods are validated using a Monte Carlo approach by comparing them with the social network created by a scholar-historian. © 2012 Springer-Verlag London Limited.
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    Translation relationship quantification: A cluster-based approach and its application to Shakespeare's sonnets
    (Springer, Dordrecht, 2010) Can, Fazlı; Can, Ethem F.; Karbeyaz, Ceyhun
    We introduce a method for quantifying translation relation-ship between source and target texts.In this method, we partition source and target texts into corresponding blocks and cluster them separately using word phrases extracted by a suffx tree approach. We quantify the translation relationship by examining the similarity between source and target clustering structures. In this comparison we aim to observe that their similarity is meaningful, i.e., it is significantly different from random. The method is based on the hypothesis that similarities and dis-similarities among the source blocks will not be lost in translation and reappear among target blocks. For testing we use Shakespeare's sonnets and its translation in Turkish. The results show that our method suc-cessfully quantifies translation relationships. © 2011 Springer Science+Business Media B.V.