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Use What You Have: Yovisto Video Search Engine Takes a Semantic Turn

  • Jörg Waitelonis
  • Nadine Ludwig
  • Harald Sack
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6725)

Abstract

The phenomenal increase of online video content confronts the consuming user with an immeasurable amount of data which can only be accessed with sophisticated multimedia search and management technologies.

Usual video search engines provide a keyword-based search, where lexical ambiguity of natural language often leads to imprecise and incomplete results.

Semantics of keywords and metadata has to be determined to overcome these shortcomings to provide high precision and high recall.

In this work, we show how to gradually transform the video search engine Yovisto from a simple keyword-based search engine to a fully-fledged semantic video search engine simply by using the existing search engine infrastructure based on Lucene augmented by simple semantic metadata.

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References

  1. 1.
    Berners-Lee, T.: Linked Data. World wide web design issues (July 2006), http://www.w3.org/DesignIssues/LinkedData.html
  2. 2.
    Bizer, C., Heath, T., Idehen, K., Berners-Lee, T.: Linked data on the web. In: Proc. of the 17th Int. Conf. on World Wide Web, pp. 1265–1266. ACM, New York (2008)Google Scholar
  3. 3.
    Carpineto, C., de Mori, R., Romano, G., Bigi, B.: An information-theoretic approach to automatic query expansion. ACM Trans. Inf. Syst. 19(1), 1–27 (2001)CrossRefGoogle Scholar
  4. 4.
    Christel, M.G.: Supporting video library exploratory search: when storyboards are not enough. In: Proc. of the Int. Conf. on Content-based Image and Video Retrieval, pp. 447–456. ACM, New York (2008)Google Scholar
  5. 5.
    Sack, H., Waitelonis, J.: Integrating Social Tagging and Document Annotation for Content-Based Search in Multimedia Data. In: Proc. of the 1st Semantic Authoring and Annotation Workshop. Athens (GA), USA (2006)Google Scholar
  6. 6.
    Kleb, J., Abecker, A.: Entity reference resolution via spreading activation on rdf-graphs. In: Aroyo, L., Antoniou, G., Hyvönen, E., ten Teije, A., Stuckenschmidt, H., Cabral, L., Tudorache, T. (eds.) ESWC 2010. LNCS, vol. 6088, pp. 152–166. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    Marchionini, G.: Exploratory search: from finding to understanding. Commun. ACM 49(4), 41–46 (2006)CrossRefGoogle Scholar
  8. 8.
    Oren, E., Delbru, R., Catasta, M., Cyganiak, R., Stenzhorn, H., Tummarello, G.: Sindice. com: a document-oriented lookup index for open linked data. IJMSO 3(1), 37–52 (2008)CrossRefGoogle Scholar
  9. 9.
    Pilz, A., Paaß, G.: Named Entity Resolution Using Automatically Extracted Semantic Information. In: Workshop on Knowledge Discovery, Data Mining, and Machine Learning, pp. 84–91 (2009)Google Scholar
  10. 10.
    Porter, M.F.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980)CrossRefGoogle Scholar
  11. 11.
    Prud’hommeaux, E., Seaborne, A.: SPARQL query language for RDF. W3C (January 2008)Google Scholar
  12. 12.
    Repp, S., Waitelonis, J., Sack, H., Meinel, C.: Segmentation and Annotation of Audiovisual Recordings based on Automated Speech Recognition. In: Proc. of 8th Int. Conf. on Intelligent Data Engineering and Automated Learning (2007)Google Scholar
  13. 13.
    Richert, M., Quasthoff, U., Hallensteinsdottir, E., Biemann, C.: Exploiting the Leipzig Corpora Collection. In: Proceedings of the IS-LTC 2006. Ljubliana, Slovenia (2006), http://wortschatz.uni-leipzig.de/
  14. 14.
    Schraefel, Wilson, M., Russell, A., Smith, D.A.: mSpace: improving information access to multimedia domains with multimodal exploratory search. Commun. ACM 49(4), 47–49 (2006)CrossRefGoogle Scholar
  15. 15.
    Snoek, C., Sande, K.v.d., Rooij, O.D., Huurnink, B., Gemert, J.v., Uijlings, J., He, J., Li, X., Everts, I., Nedovic, V., Liempt, M.v., Balen, R.v., Yan, F., Tahir, M., Mikolajczyk, K., Kittler, J., Rijke, M.d., Geusebroek, J., Gevers, T., Worring, M., Smeulders, A., Koelma, D.: The MediaMill TRECVID 2008 semantic video search engine. National Institute of Standards and Technology, NIST (2009)Google Scholar
  16. 16.
    Stoermer, H., Rassadko, N.: Results of OKKAM Feature based Entity Matching Algorithm for Instance Matching Contest of OAEI 2009. In: OM (2009)Google Scholar
  17. 17.
    Tummarello, G., Delbru, R., Oren, E.: Sindice.com: Weaving the Open Linked Data. In: The Semantic Web, pp. 552–565 (2008)Google Scholar
  18. 18.
    Waitelonis, J., Sack, H., Kramer, Z., Hercher, J.: Semantically Enabled Exploratory Video Search. In: Proc. of Semantic Search Workshop at the 19th Int. World Wide Web Conference, Raleigh, NC, USA (2010)Google Scholar
  19. 19.
    Waitelonis, J., Sack, H.: Augmenting Video Search with Linked Open Data. In: Proc. of Int. Conf. on Semantic Systems 2009 (2009)Google Scholar
  20. 20.
    Waitelonis, J., Sack, H.: Towards Exploratory Video Search Using Linked Data. In: Proc. of the 11th IEEE Int. Symp. on Multimedia, pp. 540–545. IEEE Computer Society, Washington, DC (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jörg Waitelonis
    • 1
  • Nadine Ludwig
    • 1
  • Harald Sack
    • 1
  1. 1.Hasso-Plattner-Institute PotsdamPotsdamGermany

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