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Experimenting with tagging and context for collaborative MPEG-7 metadata

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Abstract

Whether unstructured or structured, tagging of multimedia resources is a laborious and time-consuming process when carried out in the context of a single individual. However, effort can be greatly reduced and the detail, quality and volume of metadata increased within the context of a web community. Despite this, little empirical research has been carried out to understand how users individually or collaboratively work with multimedia tagging tools, whether structured or unstructured. Consequently, we explore how to effectively achieve collaborative multimedia tagging through the results of an experiment that collected data from 51 users using both unstructured folksonomy (Flickr, YouTube and del.icio.us) and structured MPEG-7 tools (COSMOSIS). We contribute a detailed analysis of the use of the multimedia tagging tools used in the experiment and show the relationships between user behaviours, resultant outcomes of these behaviours, and subsequent implications for future collaborative multimedia MPEG-7 tagging tools.

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Notes

  1. http://www.youtube.com

  2. http://www.dublincore.org/

  3. http://www.flickr.com

  4. http://bmproductions.fixnum.org/wmptagplus/

  5. http://flac.sourceforge.net/

  6. http://www.vorbis.com/

  7. http://www.wavpack.com/

  8. http://www.imdb.com/

  9. At the time of writing, del.icio.us is in the process of being revamped as Delicious, accessed via http://www.delicious.com/, and it is unsure how much of the original functionality will remain.

  10. http://www.facebook.com

  11. http://www.wistia.com

  12. http://www.startuptv.co.uk

  13. http://www.ted.com

  14. http://www.vimeo.com

  15. http://www.qsrinternational.com/products_nvivo.aspx

  16. average deviation

References

  1. Agius H, Angelides M (2006) MPEG-7 in action: end user experiences with COSMOS-7 front end systems. Proceedings of 21st Annual ACM Symposium on Applied Computing (SAC ’06) 2:1348–1355

    Article  Google Scholar 

  2. Agius H, Angelides M (2007) Closing the content-user gap in MPEG-7: the hanging basket model. Multimedia Systems 13(2):155–172

    Article  Google Scholar 

  3. Agius H, Angelides M (2009) From MPEG-7 user interaction tools to hanging basket models: bridging the gap. Multimedia Tools and Applications 41(3):375–406

    Article  Google Scholar 

  4. Al-Khalifa HS, Davis HC (2006) FolksAnnotation: A Semantic Metadata Tool for Annotating Learning Resources Using Folksonomies and Domain Ontologies. In: Proceedings of 3 rd International Conference on Innovations in Information Technology, pp. 1–5

  5. Aurnhammer M, Hanappe P, Steels L (2006) Augmenting Navigation for Collaborative Tagging with Emergent Semantics Lecture Notes in Computer Science, Vol. 4273. Springer, Berlin / Heidelberg, pp 58–71

    Google Scholar 

  6. Begelman G, Keller P, Smadja F (2006) Automated Tag Clustering: Improving search and exploration in the tag space. In: Proceedings of Workshop on Collaborative Web Tagging. http://www.pui.ch/phred/automated_tag_clustering/

  7. Blankinship E, Mikhak B (2007) Video-Wikis and Media Fluency. In: Proceedings of 6th International Conference on Interaction Design and Children, pp. 175–176

  8. Carneiro G, Vasconcelos N (2005) Formulating semantic image annotation as a supervised learning problem. Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition 2:163–168, vol. 162

    Google Scholar 

  9. Celebi E, Alpkoca A (2005) Combining textual and visual clusters for semantic image retrieval and auto-annotation. In: Proceedings of 2nd European Workshop on the Integration of Knowledge, Semantics and Digital Media Technology, pp. 219–225

  10. Charmaz K (2006) Constructing Grounded Theory: A Practical Guide through Qualitative Analysis. Sage Publications Ltd, Newbury Park, CA

    Google Scholar 

  11. Corbin J, Strauss A (2008) Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory. Sage Publications Ltd., Newbury Park, CA

    Google Scholar 

  12. Cui Y, Jin JS, Zhang S, Luo S, Tian Q (2010) Music video affective understanding using feature importance analysis. In: Proceedings of ACM International Conference on Image and Video Retrieval, pp. 213–219

  13. Dickerson JA, Kosko B (1993) Virtual worlds as fuzzy cognitive maps. In: Proceedings of IEEE Virtual Reality Annual International Symposium, 1993., pp. 471–477

  14. Ding G, Wang J, Qin K (2010) A visual word weighting scheme based on emerging itemsets for video annotation. Information Processing Letters 110(16):692–696

    Article  MATH  Google Scholar 

  15. Edvardsen LFH, Sølvberg IT, Aalberg T, Trætteberg H (2009) Automatically generating high quality metadata by analyzing the document code of common file types. In: Proceedings of 9th ACM/IEEE-CS Joint Conference on Digital Libraries, pp. 29–38

  16. Golder SA, Huberman BA (2006) Usage patterns of collaborative tagging systems. Journal of Information Science 32(2):198–208

    Article  Google Scholar 

  17. Goulding C (1998) Grounded theory: the missing methodology on the interpretivist agenda. Qualitative Market Research 1(1):50–57

    Article  Google Scholar 

  18. Haslhofer B, Klas W (2010) A survey of techniques for achieving metadata interoperability. ACM Computing Surveys (CSUR) 42(2):1–37

    Article  Google Scholar 

  19. Hyun-seok M, De Neve W, Yong Man R (2010) Towards using semantic features for near-duplicate video detection. In: Proceedings of 2010 IEEE International Conference on Multimedia and Expo, pp. 1364–1369

  20. ISO/IEC (2003) Information Technology − Multimedia Content Description Interface − Part 5: Multimedia Description Schemes. International Standard 15938-5, Geneva, Switzerland

  21. ISO/IEC (2004) Information Technology − Multimedia Content Description Interface − Part 5: Multimedia Description Schemes: Amendment 2: Multimedia Description Schemes Extensions. International Standard 15938-5/Amd.2, Geneva, Switzerland

  22. ISO/IEC (2005) Information Technology − Multimedia Content Description Interface − Part 5: Multimedia Description Schemes: Amendment 2: Multimedia Description Schemes User Preference Extensions. International Standard 15938-5/Amd.2, Geneva, Switzerland

  23. Jung Y (2008) Influence of Sense of Presence on Intention to Participate in a Virtual Community. In: Proceedings of the 41st Annual Hawaii International Conference on System Sciences

  24. Kosko B (1986) Fuzzy Cognitive Maps. International Journal of Man-Machine Studies 24:56–74

    Article  Google Scholar 

  25. Kosko B (1997) Fuzzy engineering. Prentice-Hall, Inc., Upper Saddle River, NJ, USA

    MATH  Google Scholar 

  26. Kumar R, Tomkins A (2010) A characterization of online browsing behavior. In: Proceedings of 19th International Conference on World Wide Web, pp. 561–570

  27. Kwon O (2009) A two-step approach to building bilateral consensus between agents based on relationship learning theory. Expert Systems with Applications 36(9):11957–11965

    Article  Google Scholar 

  28. Laborie S, Manzat A-M, Sédes F (2010) A generic framework for the integration of heterogeneous metadata standards into a multimedia information retrieval system. In: Proceedings of 9th International Conference on Adaptivity, Personalization and Fusion of Heterogeneous Information, pp. 80–83

  29. Lee S-S, Yong H-S (2007) TagPlus: A Retrieval System using Synonym Tag in Folksonomy. In: Proceedings of International Conference on Multimedia and Ubiquitous Engineering (MUE ’07), pp. 294–298

  30. Li Q, Lu SCY (2008) Collaborative Tagging Applications and Approaches. IEEE Multimedia 15(3):14–21

    Article  Google Scholar 

  31. Li Z, Shi Z, Liu X, Shi Z (2011) Modeling continuous visual features for semantic image annotation and retrieval. Pattern Recognition Letters 32(3):516–523

    Article  Google Scholar 

  32. Lu Y, Li Z-N (2008) Automatic object extraction and reconstruction in active video. Pattern Recogn 41(3):1159–1172

    Article  Google Scholar 

  33. Maleewong K, Anutariya C, Wuwongse, V (2008) A Collective Intelligence Approach to Collaborative Knowledge Creation. In: Proceedings of Fourth International Conference on Semantics, Knowledge and Grid, pp. 64–70

  34. Matavire R, Brown I (2008) Investigating the use of “Grounded Theory” in information systems research. In: Proceedings of Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists on IT research in Developing Countries: Riding the Wave of Technology, pp. 139–147

  35. Mayernik MS, Batcheller AL, Borgman CL (2011) How institutional factors influence the creation of scientific metadata. In: Proceedings of 2011 iConference, pp. 417–425

  36. Mika P (2007) Ontologies are us: A unified model of social networks and semantics. Web Semantics: Science, Services and Agents on the World Wide Web 5(1):5–15

    Article  MathSciNet  Google Scholar 

  37. Mishra S, Gorai A, Oberoi T, Ghosh H (2010) Efficient Visualization of Content and Contextual Information of an Online Multimedia Digital Library for Effective Browsing. Proceedings of 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology 3:257–260

    Article  Google Scholar 

  38. Naaman M, Nair R (2008) ZoneTag’s Collaborative Tag Suggestions: What is This Person Doing in My Phone? IEEE Multimedia 15(3):34–40

    Article  Google Scholar 

  39. Névéol A, Islamaj Dogan R, Lu Z (2011) Semi-automatic semantic annotation of PubMed queries: A study on quality, efficiency, satisfaction. Journal of Biomedical Informatics 44(2):310–318

    Article  Google Scholar 

  40. Ohmukai I, Hamasaki M, Takeda H (2005) A Proposal of Community-Based Folksonomy with RDF Metadata. In: Proceedings of 4th International Semantic Web Conference (ISWC). http://www-kasm.nii.ac.jp/papers/takeda/05/ohmukai05iswc.pdf

  41. Ojokoh B, Zhang M, Tang J (2011) A trigram hidden Markov model for metadata extraction from heterogeneous references. Information Sciences 181(9):1538–1551

    Article  MATH  Google Scholar 

  42. Otsuka I, Nakane K, Divakaran A, Hatanaka K, Ogawa M (2005) A highlight scene detection and video summarization system using audio feature for a personal video recorder. IEEE Transactions on Consumer Electronics 51(1):112–116

    Article  Google Scholar 

  43. Pea R, Lindgren R, Rosen J (2006) Computer-supported collaborative video analysis. In: Proceedings of 7th International Conference on Learning Sciences, pp. 516–521

  44. Qiu J, Su J, Luo L, Zhou C (2008) The Application of Multimedia in Academic Library. In: Proceedings of 2008 International Conference on MultiMedia and Information Technology, pp. 703–706

  45. Rodriguez MA, Bollen J, Sompel HVD (2009) Automatic metadata generation using associative networks. ACM Transactions on Information Systems (TOIS) 27(2):1–20

    Article  Google Scholar 

  46. Ryu J, Sohn Y, Kim M (2002) MPEG-7 metadata authoring tool. 10th ACM international conference on Multimedia. ACM, Juan-les-Pins, France 267–270

  47. Saathoff C, Scherp A (2010) Unlocking the semantics of multimedia presentations in the web with the multimedia metadata ontology. In: Proceedings of 19th International Conference on World Wide Web, pp. 831–840

  48. Shin Y, Kim Y, Kim EY (2010) Automatic textile image annotation by predicting emotional concepts from visual features. Image and Vision Computing 28(3):526–537

    Article  Google Scholar 

  49. Smoliar SW, HongJiang Z (1994) Content based video indexing and retrieval. IEEE Multimedia 1(2):62–72

    Article  Google Scholar 

  50. Tang L, Liu H, Zhang J, Agarwal N, Salerno JJ (2008) Topic taxonomy adaptation for group profiling. ACM Trans Knowl Discov Data 1(4):1–28

    Article  Google Scholar 

  51. Tao C, Embley DW (2009) Automatic hidden-web table interpretation, conceptualization, and semantic annotation. Data & Knowledge Engineering 68(7):683–703

    Article  Google Scholar 

  52. Ulges A, Schulze C, Keysers D, Breuel T (2008) A System That Learns to Tag Videos by Watching Youtube. Computer Vision Systems, pp. 415–424

  53. Viitaniemi V, Laaksonen J (2007) Evaluating the performance in automatic image annotation: Example case by adaptive fusion of global image features. Signal Processing: Image Communication 22(6):557–568

    Article  Google Scholar 

  54. Voss J (2007) Tagging, Folksonomy & Co - Renaissance of Manual Indexing? In: Proceedings of 10th International Symposium for Information Science, pp. 234–254

  55. William K (2006) Exploiting “The World is Flat” Syndrome in Digital Photo Collections for Contextual Metadata. In: Proceedings of Eighth IEEE International Symposium on Multimedia (ISM’06), pp. 341–347

  56. Wu R-S, Li P-C (2011) Video annotation using hierarchical Dirichlet process mixture model. Expert Systems with Applications 38(4):3040–3048

    Article  Google Scholar 

  57. Yamamoto D, Masuda T, Ohira S, Nagao K (2008) Video Scene Annotation Based on Web Social Activities. IEEE Multimedia 15(3):22–32

    Article  Google Scholar 

  58. Yang D, Wu D, Koolmanojwong S, Brown AW, Boehm BW (2008) WikiWinWin: A Wiki Based System for Collaborative Requirements Negotiation. In: Proceedings of 41st Annual Hawaii International Conference on System Sciences, pp. 24–24

  59. You J, Liu G, Perkis A (2010) A semantic framework for video genre classification and event analysis. Signal Processing: Image Communication 25(4):287–302

    Article  Google Scholar 

  60. Zhang X, Xu C, Cheng J, Lu H, Ma S (2009) Effective Annotation and Search for Video Blogs with Integration of Context and Content Analysis. IEEE Transactions on Multimedia 11(2):272–285

    Article  Google Scholar 

  61. Zhou H, Sadka AH, Swash MR, Azizi J, Sadiq UA (2010) Feature extraction and clustering for dynamic video summarisation. Neurocomputing 73(10–12):1718–1729

    Article  Google Scholar 

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Acknowledgement

This research was supported by the UK Engineering and Physical Sciences Research Council (EPSRC), grant no. EP/E034578/1.

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  1. Electronic and Computer Engineering, School of Engineering and Design, Brunel University, Uxbridge, Middlesex, UB8 3PH, UK

    Harry Agius, Marios C. Angelides & Damon Daylamani Zad

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  1. Harry Agius
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  2. Marios C. Angelides
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  3. Damon Daylamani Zad
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Correspondence to Harry Agius.

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Agius, H., Angelides, M.C. & Daylamani Zad, D. Experimenting with tagging and context for collaborative MPEG-7 metadata. Multimed Tools Appl 62, 143–177 (2013). https://doi.org/10.1007/s11042-011-0984-x

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