Term Extraction For User Profiling: Evaluation By The User
Suzan Verberne, Maya Sappelli, Wessel Kraaij ( UMAP-2013 ) http://sverberne.ruhosting.nl/papers/swell_umap_cameraready.pdf There are several methods that social information systems use to recommend people to their users. Among these methods, content-based people recommendation is most widely used in many different systems (e.g., Twitter). The systems collect information from users such as publications, blogs, microblogs, or posts to build their profiles in order to do recommendation later. How to build effective user profiles from texts is a difficult task. Most of the studies represent texts as a bag-of-word. Some other try to extract more meaningful terms or phrases. If a system has a good representation for user profile, it will be able to find more accurately similar users so that it can generate good people recommendation to each user. In this paper, Verberne et al. present a study that compares three popular methods of weighting terms for user profiling. The results of this ...