An Empirical Study of Online Terminology Translation Retrieval:Using Search Engines as a Tool

Abstract

Online search engines and other computer-aided tools are playing an increasingly important role in technical translation, especially in the translation of out-of-vocabulary new terms. Dictionaries, at times, prove to be of little help to term translation where out-of-vocabulary terms rely on polysemy for heuristic effects. This paper explores the role of online search engines in terminology translation by analyzing the effectiveness of four terminology translation extraction methods which utilize online search engines as search tools, thereby generating suggestions on how to use search result for reference. An experiment with some new terms was conducted to examine the effectiveness of each method. This study revealed that template-based term translation extraction and dictionary-based translation extraction have the highest accuracy rate of 86% and 89% respectively while semantic prediction search method is the most flexible method with the highest retrieval rate of 95% although its results are not always accurate. Therefore, a verification model was proposed, which utilizes quantitative-and-qualitative context analysis to verify the accuracy of translation results obtained from a search engine.