In the task of acquiring Japanese-Chinese technical term translation equivalent pairs from parallel patent documents, this paper considers situations where a technical term is observed in many parallel patent sentences and is translated into many translation equivalents and studies the issue of identifying synonymous translation equivalent pairs. First, we collect candidates of synonymous translation equivalent pairs from parallel patent sentences. Then, we apply the Support Vector Machines (SVMs) to the task of identifying bilingual synonymous technical terms, and achieve the performance of over 85% precision and over 60% F-measure. We further examine two types of segmentation of Chinese sentences, i.e., by characters and by morphemes, and integrate those two types of segmentation in the form of the intersection of SVM judgments, which achieved over 90% precision.