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This paper proposes a method for acquiring geospatial knowledge in the form of places and relations between them from the user-generated data and metadata on the Social Web. The key to acquiring geospatial knowledge from social metadata is the ability to accurately represent places. The authors describe a simple, efficient algorithm for finding a non-convex boundary of a region from a sample of points from that region. Used within a procedure that learns part-of relations between places from real-world data extracted from the social photo-sharing site Flickr, the proposed algorithm leads to more precise relations than the earlier method and helps uncover knowledge not contained in expert-curated geospatial knowledge bases.<\/p>","DOI":"10.4018\/jiscrm.2011040103","type":"journal-article","created":{"date-parts":[[2011,10,19]],"date-time":"2011-10-19T16:30:49Z","timestamp":1319041849000},"page":"33-47","source":"Crossref","is-referenced-by-count":4,"title":["Mining Geospatial Knowledge on the Social Web"],"prefix":"10.4018","volume":"3","author":[{"given":"Suradej","family":"Intagorn","sequence":"first","affiliation":[{"name":"USC Information Sciences Institute, USA"}]},{"given":"Kristina","family":"Lerman","sequence":"additional","affiliation":[{"name":"USC Information Sciences Institute, USA"}]}],"member":"2432","reference":[{"key":"jiscrm.2011040103-0","doi-asserted-by":"publisher","DOI":"10.1080\/13658810110038942"},{"key":"jiscrm.2011040103-1","doi-asserted-by":"crossref","unstructured":"Amitay, E. 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