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Organization of multimedia data for conceptual search based on ontologies


Nowadays, there is a large volume of semantically annotated multimedia data available in the Semantic Web. These data have originated from several different sources, generating new issues about their storage and retrieval. In this scenario, simple ontologies are commonly used to define knowledge domains and classify data into concepts, establishing relations between them. Such conceptual relationship may be measured by a similarity function which allows the search to be performed by similarity in an indexing system. The contribution of this paper is to propose how to organize multimedia data using this conceptual classification in LSH (Locality Sensitive Hashing) functions, facilitating the conceptual search in distributed systems like P2P networks.


  1. Berners-Lee T, Hendler J, Lassila O (2001) The semantic web: a new form of web content that is meaningful to computers will unleash a revolution of new possibilities. Sci Am 284(5):29–37

    Article  Google Scholar 

  2. Batista CECF, Schwabe D (2009) LinkedTube: semantic information on web media objects. In: Proceedings of the XV Brazilian symposium on multimedia and the web (Webmedia 2009)

    Google Scholar 

  3. Haghani P, Michel S, Cudré-Mauroux P, Aberer K (2008) LSH at large—distributed KNN search in high dimensions. In: WebDB

    Google Scholar 

  4. Kulis B, Jain P, Grauman K (2009) Fast similarity search for learned metrics. IEEE Trans Pattern Anal Mach Intell 31:2143–2157

    Article  Google Scholar 

  5. Zhu Y (2005) Enhancing search performance in peer-to-peer networks. PhD thesis, University of Cincinnati

  6. Köhler J, Philippi S, Specht M, Rüegg A (2006) Ontology based text indexing and querying for the semantic web. Elsevier Science, Amsterdam

    Google Scholar 

  7. Ratinov L, Roth D, Srikumar V (2008) Conceptual search and text categorization. Technical report UIUCDCS-R-2008-2932, UIUC, CS dept

  8. Lyte V, Jones S, Ananiadou S, Kerr L, (2009) UK institutional repository search: innovation and discovery, Ariadne, Issue 61

  9. Formica A (2008) Concept similarity in formal concept analysis: an information content approach, know-based syst. Elsevier Science, Amsterdam

    Google Scholar 

  10. Cordi V, Lombardi P, Martelli M, Mascardi V (2005) An ontology-based similarity between sets of concepts. In: WOA’05

    Google Scholar 

  11. Sridevi UK, Nagaveni N (2010) Ontology based similarity measure in document ranking. Int J Comput Appl 1(26):125–129

    Google Scholar 

  12. Polyvyanyy A (2007) Evaluation of a novel information retrieval model: eTVSM. Hasso Plattner Institut, Master’s thesis, Univeristat Potsdm

  13. Stoica I, Morris R, Karger D, Kaashoek MF, Balakrishnan H (2001) Chord: a scalable peer-to-peer lookup service for internet applications. In: Proceedings of ACM SIGCOMM’01

    Google Scholar 

  14. Indyk P, Motwani R (1998) Approximate nearest neighbors: towards removing the curse of dimensionality. In: Proceedings of the thirtieth annual ACM symposium on theory of computing (STOC ’98), New York, NY, USA

    Google Scholar 

  15. Charikar MS (2002) Similarity estimation techniques from rounding algorithms. In: Proceedings of the thiry-fourth annual ACM symposium on theory of computing (STOC ’02). ACM, New York

    Google Scholar 

  16. Varelas G, Voutsakis E, Raftopoulou P, Petrakis EGM, Milios EE (2005) Semantic similarity methods in wordNet and their application to information retrieval on the web. In: Proceedings of the 7th annual ACM international workshop on web information and data management (WIDM ’05)

    Google Scholar 

  17. Gupta A, Agrawal D, El Abbadi A (2002) Approximate range selection queries in peer-to-peer systems. In: CIDR

    Google Scholar 

  18. Watts DJ, Strogatz SH (1998) Collective dynamics of small world networks. Nature 393(6684), June

  19. Kleinberg J (2000) The small-world phenomenon: an algorithm perspective. In: Proceedings of the thirty-second annual ACM symposium on theory of computing (STOC ’00), New York, NY, USA

    Google Scholar 

  20. Girdzijauskas S (2009) Designing peer-to-peer overlays: a small-world perspective. PhD dissertation, Ecole Polytechnique Federale de Lausanne (EPFL), Lausane, CH, March 2009

  21. Chum O, Perdoch M, Matas J (2009) Geometric min-hashing: finding a (thick) needle in a haystack

  22. Georgoulas K, Kotidis Y (2010) Random hyperplane projection using derived dimensions. In: Proceedings of the ninth ACM international workshop on data engineering for wireless and mobile access (MobiDE ’10)

    Google Scholar 

  23. Ryyndnen M, Klapuri A (2008) Query by humming of midi and audio using locality sensitive hashing. In: IEEE international conference on acoustics, speech and signal processing (ICASSP 2008)

    Google Scholar 

  24. Yoshida K, Murabayashi N (2008) Tiny LSH for content-based copied video detection. In: International symposium on applications and the internet (SAINT 2008)

    Google Scholar 

  25. Bulskov H, Andreasen T (2002) On measuring similarity for conceptual querying. In: Proc. of the 5th international conference on flexible query answering systems. Springer, Berlin

    Google Scholar 

  26. Chu S, Cesnik B (2001) Knowledge representation and retrieval using conceptual graphs and free text document self-organisation techniques. Int J Med Inform 62(2–3):121–133

    Article  Google Scholar 

  27. Dick JP (1991) Representation of legal text for conceptual retrieval. In: Proceedings of the 3rd international conference on artificial intelligence and law (ICAIL ’91)

    Google Scholar 

  28. Ounis I, Pasca M (1998) Modeling, indexing and retrieving images using conceptual graphs. In: DEXA ’98

    Google Scholar 

  29. Mishne G, De Rijke M (2004) Source code retrieval using conceptual similarity. In: Proc conf computer assisted information retrieval (RIAO 04)

    Google Scholar 

  30. D’Amato C, Staab S, Fanizzi N (2008) On the influence of description logics ontologies on conceptual similarity. In: Proceedings of the 16th international conference on knowledge engineering: practice and patterns (EKAW ’08)

    Google Scholar 

  31. Yang G, Oh J (1993) Knowledge acquisition and retrieval based on conceptual graphs. In: Proceedings of the 1993 ACM SIGAPP symposium on applied computing: states of the art and practice (SAC 93)

    Google Scholar 

  32. Zhu Y, Hu Y (2007) Efficient semantic search on DHT overlays. J Parallel Distrib Comput 67(5):604–616

    Article  MathSciNet  Google Scholar 

  33. Crespo A, Garcia-Molina H (2004) Semantic overlay networks for p2p systems. In: Third international workshop on agents and peer-to-peer computing (AP2PC)

    Google Scholar 

  34. Haase P, Siebes R, Van Harmelen F (2004) Peer selection in peer-to-peer networks with semantic topologies. In: International conference on semantics of a networked world: semantics for grid databases

    Google Scholar 

  35. Schlosser M, Sintek M, Decker S, Nejdl W (2002) HyperCuP—hypercubes, ontologies and efficient search on P2P networks. In: International workshop on agents and peer-to-peer computing

    Google Scholar 

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Correspondence to Luciano Bernardes de Paula.

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A previous version of this paper appeared at WEBMEDIA 2010, the Brazilian Symposium on Multimedia and the Web.

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de Paula, L.B., Villaça, R.d.S. & Magalhães, M.F. Organization of multimedia data for conceptual search based on ontologies. J Braz Comput Soc 17, 241–254 (2011).

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  • Semantics
  • Semantic web
  • Conceptual search
  • Small world