In this paper we extend previous work on document retrieval across multilingual corpora. In this setting it is often assumed that we have a certain alignment given based on which we can learn mapping between spaces. In true multilingual corpora however, we often do not have alignments between all languages. There are hub languages which have alignments with many other languages. We look at the effectiveness of leveraging these alignments to learn maps which may have small or no alignments given. We test several methods and investigate the performance of various approaches on theWikipedia dataset.