Translation Relationship Quantification: A Cluster-Based Approach and its Application to Shakespeare's Sonnets

摘要

We introduce a method for quantifying translation relationship 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 suffix 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 dissimilarities 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 successfully quantifies translation relationships.