We introduce a new approach to multilingual information retrieval based on the use of thesaurus-based query expansion techniques applied over a collection of comparable multilingual documents. This approach has been built into the SPIDER information retrieval system and has been tested over a large collection of Italian documents. We have shown that the SPIDER system retrieves Italian documents in response to user queries written in German with better effectiveness than a baseline system evaluating Italian queries against Italian documents. Although the importantance of the SPIDER stemming algorithm for Italian must be stressed in these results, we have also achieved performance on multilingual retrieval tasks within 32% of the best SPIDER performance on Italian retrieval, by including a relevance feedback loop in the task of multilingual retrieval.