Classifying tags using open content resources

ABSTRACT

Tagging has emerged as a popular means to annotate on-line objects such as bookmarks, photos and videos. Tags vary in semantic meaning and can describe different aspects of a media object. Tags describe the content of the media as well as locations, dates, people and other associated meta-data. Being able to automatically classify tags into semantic categories allows us to understand better the way users annotate media objects and to build tools for viewing and browsing the media objects. In this paper we present a generic method for classifying tags using third party open content resources, such as Wikipedia and the Open Directory. Our method uses structural patterns that can be extracted from resource meta-data. We describe the implementation of our method on Wikipedia using WordNet categories as our classification schema and ground truth. Two structural patterns found in Wikipedia are used for training and classification: categories and templates. We apply our system to classifying Flickr tags. Compared to a WordNet baseline our method increases the coverage of the Flickr vocabulary by 115%. We can classify many important entities that are not covered by WordNet, such as, London Eye, Big Island, Ronaldinho, geocaching and wii.

REFERENCES

• 1: Sören Auer , Jens Lehmann, What Have Innsbruck and Leipzig in Common? Extracting Semantics from Wiki Content, Proceedings of the 4th European conference on The Semantic Web: Research and Applications, June 03-07, 2007, Innsbruck, Austria [doi>10.1007/978-3-540-72667-8_36]
• 2: R. Bunescu and M. Pasca. Using encyclopedic knowledge for named entity disambiguation. In Proc. of EACL, pages 9--16, 2006.
• 3: D. Buscaldi, P. Rosso, and P. García. Inferring geographic ontologies from multiple resources for geographical information retrieval. In Proc. of the SIGIR workshop on GIR, pages 53--55, 2006.
• 4: P. Clough, A. Al-Maskari, and K. Darwish. Providing multilingual access to Flickr for arabic users. In Proc. of CLEF, 2006.
• 5: S. Cucerzan. Large-scale named entity disambiguation based on Wikipedia data. In Proc. of EMNLP-CoNLL, pages 708--716, 2007.
• 6: DBpedia. http://dbpedia.org/. Accessed 5 Dec 08.
• 7: Delicious. http://del.icio.us/. Accessed 5 Dec 08.
• 8: Flickr. http://www.Flickr.com/. Accessed 5 Dec 08.
• 9: FlickrAPI. http://www.flickr.com/services/api/. Accessed 5 Dec 08.
• 10: T. Joachims. Making large-scale SVM learning practical. In Advances in Kernal Methods - Support Vector Learning, pages 41--56, 1998.
• 11: R. Mihalcea. Using wikipedia for automatic word sense disambiguation. In Proc. of NAACL, pages 196--203, 2007.
• 12: Simon E. Overell , Stefan Rüger, Geographic co-occurrence as a tool for gir., Proceedings of the 4th ACM workshop on Geographical information retrieval, November 09-09, 2007, Lisbon, Portugal [doi>10.1145/1316948.1316968]
• 13: Tye Rattenbury , Nathaniel Good , Mor Naaman, Towards automatic extraction of event and place semantics from flickr tags, Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, July 23-27, 2007, Amsterdam, The Netherlands [doi>10.1145/1277741.1277762]
• 14: M. Ruiz-Casado, E. Alfonseca, and P. Castells. Automatic assignment of Wikipedia encyclopedic entries to WordNet synsets. In Proc. of AWIC, pages 380--386, 2005.
• 15: P. Schmitz. Inducing an ontology from flickr tags. In Proc. of the Workshop on Collaborative Web Tagging at WWW'06, 2006.
• 16: Börkur Sigurbjörnsson , Roelof van Zwol, Flickr tag recommendation based on collective knowledge, Proceeding of the 17th international conference on World Wide Web, April 21-25, 2008, Beijing, China [doi>10.1145/1367497.1367542]
• 17: Fabian M. Suchanek , Gjergji Kasneci , Gerhard Weikum, Yago: a core of semantic knowledge, Proceedings of the 16th international conference on World Wide Web, May 08-12, 2007, Banff, Alberta, Canada [doi>10.1145/1242572.1242667]
• 18: TagExplorer. http://sandbox.yahoo.com/TagExplorer. Accessed 5 Dec 08.
• 19: Gabriel Weaver , Barbara Strickland , Gregory Crane, Quantifying the accuracy of relational statements in Wikipedia: a methodology, Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries, June 11-15, 2006, Chapel Hill, NC, USA [doi>10.1145/1141753.1141853]
• 20: Wikipedia. http://www.wikipedia.org/. Accessed 5 Dec 08.
• 21: WordNet. http://wordnet.princeton.edu/. Accessed 5 Dec 08.
• 22: Ka-Ping Yee , Kirsten Swearingen , Kevin Li , Marti Hearst, Faceted metadata for image search and browsing, Proceedings of the SIGCHI conference on Human factors in computing systems, April 05-10, 2003, Ft. Lauderdale, Florida, USA [doi>10.1145/642611.642681]
• 23: YouTube. http://youtube.com/. Accessed 5 Dec 08.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing

General Terms:
Algorithms, Experimentation, Performance

Keywords:
Flickr, categorization, multimedia annotation, user-generated content, wikipedia