Information on subcategorization and selectional restrictions is very important for natural language processing in tasks such as monolingual parsing, accurate rule-based machine translation and automatic summarization. However, adding this detailed information to a valency dictionary is both time consuming and costly. In this paper we present a method of assigning valency information and selectional restrictions to entries in a bilingual dictionary, based on information in an existing valency dictionary. The method is based on two assumptions: words with similar meaning have similar subcategorization frames and selectional restrictions; and words with the same translations have similar meanings. Based on these assumptions, new valency entries are constructed for words in a plain bilingual dictionary, using entries with similar source-language meaning and the same target-language translations. We evaluate the effects of various measures of similarity.