Ranking search results for translated content

Translation Memory (TM) consists of a collection of previously translated units of text that may prove useful in the translation of new text. The main problem faced by translators who wish to take advantage of TM is that, although search tools do exist, there is no standardized way of effectively ranking search results. This paper proposes a method for effectively ranking TM search results together with a novel approach to efficiently finding common substrings.