This work explores a novel approach for conversation detection in email mailboxes. This approach clusters messages into coherent conversations by using a similarity function among messages that takes into consideration all relevant email attributes, such as message subject, participants, date of submission, and message content. The detection algorithm is evaluated against a manual partition of two email mailboxes into conversations. Experimental results demonstrate the superiority of our detection algorithm over several other alternative approaches.