A hybrid approach for spotting, disambiguating and annotating places in user-generated text

Karen Stepanyan, George Gkotsis, Vangelis Banos, Alexandra I. Cristea, Mike Joy

Abstract: We introduce a geolocation-aware semantic annotation model that extends the existing solutions for spotting and disambiguation of places within user-generated texts. The implemented prototype processes the text of weblog posts and annotates the places and toponyms. It outperforms existing solutions by taking into consideration the embedded geolocation data. The evaluation of the model is based on a set of randomly selected 3,165 geolocation embedded weblog posts, obtained from 1,775 web feeds. The results demonstrate a high degree of accuracy in annotation (87.7%) and a considerable gain (27.8%) in identifying additional entities, and therefore support the adoption of the model for supplementing the existing solutions.