Items by Michel, Sebastian

We show how a number of novel email search features can be implemented without any kind of natural language processing (NLP) or advanced data mining. Our approach inspects the email headers of all messages a user has ever sent or received and it creates simple per-contact summaries, including simple information about the message exchange history, the domain of the sender or even the sender’s gender. With these summaries advanced questions/tasks such as “Who do I still need to reply to?” or “Find ‘fun’ messages sent by friends.” become possible. As a proof of concept, we implemented a Mozilla-Thunderbird extension, adding powerful people search to the popular email client.