Towards Automatic Web Identification of Solutions in Patient Innovation

摘要: Patient Innovation is an online open platform, with a community of over 60.000 users and more than 800 innovative solutions developed by patients and informal caregivers from all over the world. These solutions and/or creators were found by manually searching the Web in four different languages, through a combination of appropriate keywords and using experts to curate the results. In this paper we present a classifier architecture composed by a Word2Vec based SVM and a Fuzzy Fingerprint relevance classifier that is able to obtain a F1-score of 0.98 in the process of automatically identifying Patient Innovation solutions from texts obtained from the web.