Börkur Sigurbjörnsson
Roelof van Zwol
ABSTRACT
Online photo services such as Flickr and Zooomr allow users to share their photos with family, friends, and the online community at large. An important facet of these services is that users manually annotate their photos using so called tags, which describe the contents of the photo or provide additional contextual and semantical information. In this paper we investigate how we can assist users in the tagging phase. The contribution of our research is twofold. We analyse a representative snapshot of Flickr and present the results by means of a tag characterisation focussing on how users tags photos and what information is contained in the tagging. Based on this analysis, we present and evaluate tag recommendation strategies to support the user in the photo annotation task by recommending a set of tags that can be added to the photo. The results of the empirical evaluation show that we can effectively recommend relevant tags for a variety of photos with different levels of exhaustiveness of original tagging.
- L. A. Adamic. Zipf, power-laws, and pareto - a ranking tutorial. http://www.hpl.hp.com/research/idl/papers/ranking/ranking.html, 2002.Google Scholar
- S. Ahern, S. King, M. Naaman, R. Nair, and J. H.-I. Yang. ZoneTag: Rich, community-supported context-aware media capture and annotation. In Mobile Spatial Interaction workshop (MSI) at the SIGCHI conference on Human Factors in computing systems (CHI 2007), 2007.Google Scholar
- S. Ahern, M. Naaman, R. Nair, and J. Yang. World explorer: Visualizing aggregate data from unstructured text in geo-referenced collections. In Proceedings of the Seventh ACM/IEEE-CS Joint Conference on Digital Libraries, (JCDL 07), 2007. Google ScholarDigital Library
- M. Ames and M. Naaman. Why we tag: Motivations for annotation in mobile and online media. In Proceedings of the SIGCHI conference on Human Factors in computing systems (CHI 2007), San Jose, CA, USA, 2007. Google ScholarDigital Library
- K. Barnard, P. Duygulu, D. Forsyth, N. de Freitas, D. Blei, and M. Jordan. Matching words and pictures. Journal of Machine Learning Research, 3:1107--1135, 2003. Google ScholarDigital Library
- CiteULike. http://www.citeulike.org.Google Scholar
- R. Datta, D. Joshi, J. Li, and J. Z. Wang. Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Surveys, 40, 2008. to appear. Google ScholarDigital Library
- del.icio.us. http://www.del.icio.us.Google Scholar
- M. Dubinko, R. Kumar, J. Magnani, J. Novak, P. Raghavan, and A. Tomkins. Visualizing tags over time. In WWW '06: Proceedings of the 15th international conference on World Wide Web, pages 193--202. ACM Press, 2006. Google ScholarDigital Library
- C. Fellbaum, editor. WordNet: An Electronic Lexical Database. The MIT Press, 1998.Google Scholar
- Flickr. http://www.flickr.com.Google Scholar
- Flickr blog. http://blog.flickr.com/en/2007/05/29/were-going-down/.Google Scholar
- S. Golder and B. A. Huberman. The structure of collaborative tagging systems. http://www.hpl.hp.com/research/idl/papers/tags/, 2006. Google ScholarDigital Library
- K. Lerman and L. Jones. Social browsing on flickr. In Proceedings of International Conference on Weblogs and Social Media, Boulder, Co, USA, 2007.Google Scholar
- J. Li and J. Z. Wang. Real-time computerized annotation of pictures. In Proceedings of the ACM Multimedia Conference, pages 911--920, 2006. Google ScholarDigital Library
- C. Marlow, M. Naaman, M. Davis, and D. Boyd. HT06, tagging paper, taxonomy, Flickr, academic article, toread. In HT'06: Proceedings of the seventeenth ACM conference on Hypertext and hypermedia, 2006. Google ScholarDigital Library
- P. Mika. Ontologies are us: A unified model of social networks and semantics. In Proceedings of the 4th International Semantic Web Conference (ISWC 2005), volume 3729 of LNCS. Springer-Verlag, 2005. Google ScholarDigital Library
- T. Rattenbury, N. Good, and M. Naaman. Towards automatic extraction of event and place semantics from Flickr tags. In Proceedings of the Thirtieth International ACM SIGIR Conference, (SIGIR 07), 2007. Google ScholarDigital Library
- W. J. Reed. The Pareto, Zipf and other power laws. Economics Letters, 74(1):15--19, December 2001.Google ScholarCross Ref
- M. Sanderson and B. Croft. Deriving concept hierarchies from text. In SIGIR '99: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 206--213. ACM Press, 1999. Google ScholarDigital Library
- P. Schmitz. Inducing ontology from Flickr tags. In Proceedings of the Collaborative Web Tagging Workshop (WWW'06), 2006.Google Scholar
- A. W. M. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain. Content-based image retrieval at the end of the early years. IEEE Transactions Pattern Analysis Machine Intelligence, 22(12):1349--1380, 2000. Google ScholarDigital Library
- L. von Ahn and L. Dabbish. Labeling images with a computer game. In CHI '04: Proceedings of the SIGCHI conference on Human factors in computing systems, pages 319--326, New York, NY, USA, 2004. ACM Press. Google ScholarDigital Library
- Zonetag. http://zonetag.research.yahoo.com/.Google Scholar
- Zooomr. http://www.zooomr.com/.Google Scholar
Index Terms
- Flickr tag recommendation based on collective knowledge
Recommendations
Mining Tags from Flickr User Comments Using a Hybrid Ranking Model
ICSS '15: Proceedings of the 2015 International Conference on Service ScienceIn the Web2.0 era, user generated content has become the main source of information of many popular websites such as Flickr. In Flickr, each user can share his/her photos and browse others' easily. Tagging system is an important approach to the photo ...
Tag recommendation for social bookmarking: Probabilistic approaches
Principles and Practice of Multi-Agent SystemsTagging has become increasingly popular with the explosion of user-created content on the web. A 'tag' can be defined as a group of keywords that makes organizing, browsing and searching for content more efficient. Users apply tags to a variety of web-...
Personalized, interactive tag recommendation for flickr
RecSys '08: Proceedings of the 2008 ACM conference on Recommender systemsWe study the problem of personalized, interactive tag recommendation for Flickr: While a user enters/selects new tags for a particular picture, the system suggests related tags to her, based on the tags that she or other people have used in the past ...
Comments