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The Detection of Scene Features in Flickr

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New Horizons in Web-Based Learning - ICWL 2010 Workshops (ICWL 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6537))

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Abstract

Detecting events from web resources has attracted increasing research interests in recent years. Flickr is one of Web resources, which is used to share photos. Complex event detection on Flickr includes the detection of tourist features, user’s interest, and so on. With the increasing user requirements of efficient and personalized services, the detection of scene features in Flickr is urgently needed. In this paper we propose a novel method to detect tourist features of every scene, and its difference in different seasons as a probabilistic combination of tags. The use of topic models enables the automatic detection of such patterns, which can translate unstructured tag information into structured event form. The experimental evaluation using real datasets in Flickr show the feasibility and efficiency of the proposed method.

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References

  1. Allan, J., Carbonell, J.G., Doddington, G., Yamron, J., Yang, Y.: Topic Detection and Tracking Pilot Study: Final Report. In: DARPA Broadcast News Transcription and Understanding Workshop (1998)

    Google Scholar 

  2. Yang, Y., Pierce, T., Carbonell, J.G.: A Study of Retrospective and On-line Event Detection. In: The 21th Annual International ACM SIGIR Conference (SIGIR), pp. 28–36 (1998)

    Google Scholar 

  3. He, Q., Chang, K., Lim, E.P.: Analyzing Feature Trajectories for Event Detection. In: The 30th Annual International ACM SIGIR Conference (SIGIR), pp. 207–214 (2007)

    Google Scholar 

  4. Li, Z., Wang, B., Li, M., Ma, W.Y.: A Probabilistic Model for Retrospective News Event Detection. In: The 28th Annual International ACM SIGIR Conference, SIGIR (2005)

    Google Scholar 

  5. Kleinberg, J.M.: Bursty and Hierarchical Structure in Streams. In: The 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), vol. 7(4), pp. 373–397 (2003)

    Google Scholar 

  6. Halpin, H., Robu, V., Shepherd, H.: The Complex Dynamics fo Collaborative Tagging. In: The 16th International Conference on World Wide Web (WWW), pp. 211–220 (2007)

    Google Scholar 

  7. Dubinko, M., Kumar, J., Magnani, J., et al.: Visualizing Tags over Time. In: The 15th International Conference on World Wide Web (WWW), pp. 193–202 (2006)

    Google Scholar 

  8. Dmitriev, P.A., Eiron, N., Fontoura, M., Shekita, E.: Using Annotations in Enterprise Search. In: The 15th International Conference on World Wide Web (WWW), pp. 811–817 (2006)

    Google Scholar 

  9. Bao, S., Xue, G.R., Wu, X., Yu, Y., Su, Z.: Optimizing Web Search Using Social Annotations. In: The 16th International Conference on World Wide Web (WWW), pp. 501–510 (2007)

    Google Scholar 

  10. Rattenbury, T., Good, N., Naaman, M.: Towards Automatic Extraction of Event and Place Semantics from Flickr Tags. In: The 30th Annual International ACM SIGIR Conference (SIGIR), pp. 103–110 (2007)

    Google Scholar 

  11. Popescu, A., Grefenstette, G., Moellic, P.A.: Mining Tourist Information from User-Supplied Collections. In: The 18th ACM Conference on Information and Knowledge Management (CIKM), pp. 1713–1716 (2009)

    Google Scholar 

  12. Rattenbury, T., Good, N., Naaman, M.: Towards Automatic Extraction of Event and Place Semantics from Flickr Tags. In: Proceedings of the 30th Annual International ACM SIGIR Conference (2007)

    Google Scholar 

  13. Ahern, S., Naaman, M., Nair, R., Yang, J.: World Explorer: Visualizing Aggregate Data from Unstructured Text in Georeferenced Collections. In: Proceedings of the ACM IEEE Joint Conference on Digital Libraries, JCDL (2007)

    Google Scholar 

  14. Quack, T., Leibe, B., van Gool, L.: World-Scale Mining of Objects and Events from Community Photo Collections. In: Proceedings of the 7th ACM International Conference on Image and Video Retrieval, CIVR (2008)

    Google Scholar 

  15. Crandall, D., Backstrom, L., Hutternlocher, D., Kleinberg, J.: Mapping the World’s photos. In: Proceedings of the 18th International World Wide Web Conference, WWW (2009)

    Google Scholar 

  16. Zheng, I., Zhang, L., Xie, X., Ma, W.Y.: Mining Interesting Locations and Travel Sequences from GPS Trajectories. In: Proceedings of the 18th International World Wide Web Conference, WWW (2009)

    Google Scholar 

  17. Gonotti, F., et al.: Trajectory Pattern Mining. In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 330–339 (2007)

    Google Scholar 

  18. Girardin, F., Dal, F., Blat, J., et al.: Understanding of Tourist Dynamics from Explicitly Disclosed Location Information. In: Proceedings of the 4th International Symposium on LBS and Telecartography (2007)

    Google Scholar 

  19. Chen, Z., Shen, H.T., Zhou, X., Zheng, Y., Xie, X.: Searching Trajectories by Locations-An Efficiency Study. In: Proceedings of the 36th SIGMOD International Conference on Management of Data, SIGMOD (2010)

    Google Scholar 

  20. Home and Abroad, http://homeandabroad.com

  21. Popescu, A., Grefenstette, G.: Deducing Trip Related Information from Flickr. In: Proceedings of the 18th International World Wide Web Conference, WWW (2009)

    Google Scholar 

  22. Popescu, A., Grefenstette, G., Alain, P.: Mining Tourist Information from User-Supplied Collections. In: Proceedings of The 18th ACM Conference on Information and Knowledge Management, CIKM (2009); SIGMOD (2004)

    Google Scholar 

  23. Shekhar, S., Liu, D.: CCAM: A Connectivity Clustered Acccess Method for Networks and Network Computations. IEEE Transactions on Knowledge and Data Engineering (TKDE), 102–119 (1997)

    Google Scholar 

  24. Li, F., Cheng, D.: On trip planning queries in spatial databases. In: Anshelevich, E., Egenhofer, M.J., Hwang, J. (eds.) SSTD 2005. LNCS, vol. 3633, pp. 273–290. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  25. Blei, D., Ng, A., Jordan, M.: Latent Dirichlet Allocation. The Journal of Machine Learning Research, 993–1022 (2003)

    Google Scholar 

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Zhou, C., Dai, P., Liu, J. (2011). The Detection of Scene Features in Flickr. In: Luo, X., Cao, Y., Yang, B., Liu, J., Ye, F. (eds) New Horizons in Web-Based Learning - ICWL 2010 Workshops. ICWL 2010. Lecture Notes in Computer Science, vol 6537. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20539-2_24

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  • DOI: https://doi.org/10.1007/978-3-642-20539-2_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20538-5

  • Online ISBN: 978-3-642-20539-2

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