In my 2011 Text-Mining course, Freek did a project on text-mining twitter data, which was very interesting. After the text mining course, I supervised Freek at his internship. Freek helped to develop advanced applications such as finding travel patterns, visualizing relations in email collections and social networks, and basic name disambiguation and normalization. Freek programmed computer programs that took the results of what was possible one step further. The work performed by Freek was very good and clearly shows what text-mining technology is capable off in a commercial environment. In 2012, I also supervised Freek his thesis work related to authorship disambiguation and alias resolution in email data sets. Given a set of emails, it is investigated how to resolve aliases and disambiguate authors even if their names are misspelled, if they use completely different email addresses or if they deliberately use aliases. Freek’s thesis was very well written and to the point. He also delivered a lot of usefull and working code. The application that Freek developedis very important in fighting fraud, terrorism, child abuse and other criminal behavior, because there are many people that do not want to be found, with Freeks work it should be possible to trace them down much better and faster!

In my 2011 Text-Mining course, Freek did a project on text-mining twitter data, which was very interesting. After the text mining course, I supervised Freek at his internship. Freek helped to develop advanced applications such as finding travel patterns, visualizing relations in email collections and social networks, and basic name disambiguation and normalization. Freek programmed computer programs that took the results of what was possible one step further. The work performed by Freek was very good and clearly shows what text-mining technology is capable off in a commercial environment. In 2012, I also supervised Freek his thesis work related to authorship disambiguation and alias resolution in email data sets. Given a set of emails, it is investigated how to resolve aliases and disambiguate authors even if their names are misspelled, if they use completely different email addresses or if they deliberately use aliases. Freek’s thesis was very well written and to the point. He also delivered a lot of usefull and working code. The application that Freek developedis very important in fighting fraud, terrorism, child abuse and other criminal behavior, because there are many people that do not want to be found, with Freeks work it should be possible to trace them down much better and faster!

In my 2011 Text-Mining course, Freek did a project on text-mining twitter data, which was very interesting. After the text mining course, I supervised Freek at his internship. Freek helped to develop advanced applications such as finding travel patterns, visualizing relations in email collections and social networks, and basic name disambiguation and normalization. Freek programmed computer programs that took the results of what was possible one step further. The work performed by Freek was very good and clearly shows what text-mining technology is capable off in a commercial environment. In 2012, I also supervised Freek his thesis work related to authorship disambiguation and alias resolution in email data sets. Given a set of emails, it is investigated how to resolve aliases and disambiguate authors even if their names are misspelled, if they use completely different email addresses or if they deliberately use aliases. Freek’s thesis was very well written and to the point. He also delivered a lot of usefull and working code. The application that Freek developedis very important in fighting fraud, terrorism, child abuse and other criminal behavior, because there are many people that do not want to be found, with Freeks work it should be possible to trace them down much better and faster!