Skip to main content

Extraction and Reuse of Pattern Configuration for Personalized Customization of Cantonese Porcelain Based on Artificial Intelligence

  • Conference paper
  • First Online:
  • 2028 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12183))

Abstract

To solve the problems of inefficient learning caused by the complexity, fragmentation and lack of personalization of traditional handicraft learning resources. Based on the method of pattern configuration extraction and reuse, this paper takes the innovative design of Canton Porcelain pattern as an example. For the first time, sorting the knowledge of Cantonese Porcelain according to different cultural attributes (labels), to establish the knowledge base and pattern sample base of Canton Porcelain, and build a semantic relationship between the them, recommend Cantonese Porcelain elements that meet users’ needs through semantic search. Then, shape context was used to extract patterns of Cantonese Porcelain, and topological methods was combined to establish the configuration rules of patterns. Shape grammar based on character encoding were improved in the process of generation of personalized customization patterns of Cantonese Porcelain, used to describe the transformation of shapes during pattern filling, thereby generation of personalized customization patterns of Cantonese Porcelain based on element extraction will be completed. Develop a personalized customization system for Cantonese Porcelain crafts, and tests the method feasible through an application example.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Luo, S., Dong, J.: Knowledge integration and management of objects for cultural and creative design. Comput. Integr. Manuf. Syst. 24(4), 964–977 (2018)

    Google Scholar 

  2. Luo, S., Dong, J.: Research on the classification of object knowledge for creative design investigate. J. Zhejiang Univ.: Eng. Ed. 51(1), 113–123 (2017)

    Google Scholar 

  3. Zhu, K.: Research and discussion on the construction of basic database of cultural relics. Cultural relic protection. Sci. Conserv. Archaeol. 23(3), 16–21 (2011)

    Google Scholar 

  4. Doerr, M.: The CIDOC conceptual reference module: an ontological approach to semantic interoperability of metadata. Archive 24(3), 75–92 (2003)

    Google Scholar 

  5. Gong, H., Hu, C., Liu, C.: Research on information resource classification and metadata design of digital cultural relic museum. Intell. Mag. 33(1), 183–189 (2014)

    Google Scholar 

  6. Meyer, É., Grussenmeyer, P., Perrin, J., et al.: A web information system for the management and the dissemination of Cultural Heritage data. J. Cult. Herit. 8(4), 396–411 (2007)

    Article  Google Scholar 

  7. Yang, Y., Du, J., Ping, Y.: Intelligent information retrieval system based on ontology. J. Softw. 26(7), 1675–1687 (2015)

    MathSciNet  Google Scholar 

  8. Leong, B.D., Clark, H.: Culture-based knowledge towards new design thinking and practice-a dialogue. Des. Issues 19(3), 48–58 (2003)

    Article  Google Scholar 

  9. Zhang, X., Wang, J., Lu, G., et al.: Pattern configuration and reuse based on ontology and shape grammar. J. Zhejiang Univ. Eng. Ed. 52(3), 461–472 (2018)

    Google Scholar 

  10. Cui, J., Tang, M.X.: Integrating shape grammars into a generative system for Zhuang ethnic embroidery design exploration. CAD Comput. Aided Des. 45(3), 591–604 (2013)

    Article  MathSciNet  Google Scholar 

  11. 
Sayed, Z., Ugail, H., Pakmer, I., et al.: Parameterized shape grammar for n-fold generating islamic geometric motifs. In: 2015 International Conference on Cyberworlds, Chongqing, pp. 79–85. IEEE Press, New York (2015)

    Google Scholar 

  12. Grobler, F., Aksamija, A., Kim, H., Krishnamurti, R., Yue, K., Hickerson, C.: Ontologies and shape grammars: communication between knowledge-based and generative systems. In: Gero, J.S., Goel, A.K. (eds.) Design Computing and Cognition 2008, pp. 23–40. Springer, Dordrecht (2008). https://doi.org/10.1007/978-1-4020-8728-8_2

    Chapter  Google Scholar 

  13. Jiang, Y., Jin, Y.: Full information acquisition and utilization based on natural language understanding in knowledge construction. Libr. Inf. Serv. 59(6), 104–112 (2015)

    Google Scholar 

  14. Ji, Y., Tan, P.: Exploring personalized learning pattern for studying Chinese traditional handicraft. In: Proceedings of the Sixth International Symposium of Chinese CHI - Chinese CHI 2018, Montreal, QC, Canada, 21–22 April 2018, pp. 140–143. ACM Press (2018)

    Google Scholar 

  15. Chinese magazine editorial board of otolaryngology head and neck surgery, Chinese medical association otolaryngology head and neck surgery branch of nasal science group. Diagnosis and treatment of allergic rhinitis guide. J. Chin. Clin. Doctors (6), 67–68 (2010). https://doi.org/10.3969/j.iSSN.1008-1089.2010.06.028

  16. Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24(4), 509–522 (2002)

    Article  Google Scholar 

  17. Zhang, L., Lu, D., Zhang, L., Pan, Y., et al.: Composition knowledge generation model based on comprehensive reasoning. J. Comput. Aided Des. Graph. 12(5), 384–389 (2000)

    Google Scholar 

  18. Bibri, S.E., Krogstie, J.: ICT of the new wave of computing for sustainable urban forms: their big data and context-aware augmented typologies and design concepts. Sustain. Cities Soc. 32, 449–474 (2017)

    Article  Google Scholar 

  19. Wei, X., Weng, D., Liu, Y., Wang, Y.: Teaching based on augmented reality for a technical creative design course. Comput. Educ. 81(C), 221–234 (2015)

    Google Scholar 

  20. Russon, J.: Sites of Exposure: Art, Politics, and the Nature of Experience. Indiana University Press, Bloomington (2017)

    Book  Google Scholar 

  21. Pine, B.J., Gilmore, J.H.: The Experience Economy. Harvard Business School Press, Boston (1999)

    Google Scholar 

  22. Mou, Q.C., et al.: Making children’s education products of “TuTuLe” based on AR 
technology. Comput. Inf. Technol. (2017)

    Google Scholar 

  23. Wei, S., Wang, B.: Application of AR technology in intangible cultural heritage and cultural tourism industry. J. Jianghan Univ. 44(4), 364–368 (2016)

    MathSciNet  Google Scholar 

  24. Ilic, U., Yildirim, O.G.: Augmented reality and its reflections on education in Turkey. In: 
International Dynamic, Explorative and Active Learning (2015)

    Google Scholar 

  25. Hirve, S.A., Kunjir, A., Shaikh, B., Shah, K.: An approach towards data visualization based 
on AR principles. In: International Conference on Big Data Analytics and Computational Intelligence, pp. 128–133. IEEE (2017)

    Google Scholar 

  26. Heun, V., Kasahara, S., Maes, P.: Smarter objects: using AR technology to program physical objects and their interactions. In: Extended Abstracts on Human Factors in Computing 
Systems CHI 2013, pp. 2817–2818. ACM (2013)

    Google Scholar 

  27. Zhang, Y., Zhu, Z.: Interactive spatial AR for classroom teaching. In: De Paolis, L.T., Mongelli, A. (eds.) AVR 2016. LNCS, vol. 9768, pp. 463–470. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-40621-3_34

    Chapter  Google Scholar 

  28. Augmented Reality. In: IEEE International Conference on Trust, Security and Privacy in 
Computing and Communications, pp. 1666–1675. IEEE, fchencq

    Google Scholar 

  29. Puyuelo, M., Higón, J.L., Merino, L., Contero, M.: Experiencing augmented reality as an accessibility resource in the UNESCO heritage site called “la lonja”, Valencia. Proc. Comput. Sci. 25, 171–178 (2013)

    Article  Google Scholar 

  30. Mendoza, R., Baldiris, S., Fabregat, R.: Framework to heritage education using emerging technologies. Proc. Comput. Sci. 75, 239–249 (2015)

    Article  Google Scholar 

  31. Kim, E., Kim, J., Woo, W.: Metadata schema for context-aware augmented reality applications 
in cultural heritage domain. In: Digital Heritage, vol. 2, pp. 283–290. IEEE (2016)

    Google Scholar 

  32. Dieck, M.C.T., Jung, H.: Value of augmented reality at cultural heritage sites: a stakeholder approach. J. Destin. Mark. Manag. 6(2), 110–117 (2017)

    Google Scholar 

  33. Anonymous. Related Content Database, Inc.: RCDb Licenses BD-Live Software to Netflix for PS3 Instant Streaming Disc. Information Technology Newsweekly (2009)

    Google Scholar 

  34. Big Data for Development: Challenges & Opportunities [DB/OL], 01 May 2012. http://www.unglobalpulse.org/sites/default/files/BigDataforDevelopmentUNGlobalPulseJune2012.pdf

  35. [7][12][13][14] Enhancing Teaching and Learning through Educational Data Mining and Learning

    Google Scholar 

  36. Analytics [DB/OL], 12 October 2012. http://www.ed.gov/edblogs/technology/files/2012/03/edm-la-brief.pdf

  37. Jara, C.A., Candelas, F.A., Puente, S.T., Torres, F.: Hands-on experiences of undergraduate students in automatics and robotics using a virtual and remote laboratory. Comput. Educ. 57(4), 2451–2461 (2011)

    Article  Google Scholar 

  38. Bacca, J., Baldiris, S., Fabregat, R., Graf, S., Kinshuk: Augmented reality trends in education: a systematic review of research and applications. J. Educ. Technol. Soc. 17(4), 133–149 (2014)

    Google Scholar 

  39. International Organization for Standardization. Ergonomics of human system interaction - Part 210 (2009)

    Google Scholar 

  40. Human-centered design for interactive systems (formerly known as 13407). ISO F ± DIS 9241-210 (2009)

    Google Scholar 

  41. Law, E., Roto, V., Hassenzahl, M., Vermeeren, A., Kort, J.: Understanding, scoping and defining user experience: a survey approach (PDF). In: Proceedings of Human Factors in Computing Systems Conference CHI 2009, Boston, MA, USA, 4–9 April 2009 (2009)

    Google Scholar 

  42. Huang, T.C., Chen, C.C., Chou, Y.W.: Animating eco-education: to see, feel, and discover in an augmented reality-based experiential learning environment. Comput. Educ. 96, 72–82 (2016)

    Article  Google Scholar 

  43. Dunlap, J., Dobrovolny, J., Young, D.: Preparing e-Learning designers using Kolb’s model of experiential learning. J. Online Educ. 4(4), 1–6 (2008)

    Google Scholar 

  44. Fan, H., Scottpoole, M.: What is personalization? Perspectives on the design and implementation of personalization in information systems. J. Organ. Comput. 16(3–4), 179–202 (2006)

    Google Scholar 

  45. Mayeku, B.: Enhancing personalization and learner engagement in context-aware learning environment - a pedagogical and technological perspective (2015)

    Google Scholar 

  46. Li, M., Ogata, H., Hou, B., Uosaki, N., Yano, Y.: Personalization in context-aware ubiquitous learning-log system. In: IEEE Seventh International Conference on Wireless, Mobile and Ubiquitous Technology in Education, vol. 16, pp. 41–48. IEEE (2012)

    Google Scholar 

  47. Kucirkova, N., Messer, D., Whitelock, D.: Parents reading with their toddlers: the role of personalization in book engagement. J. Early Child. Literacy 13(4), 445–470 (2012)

    Article  Google Scholar 

  48. Keller, J.M., Litchfield, B.C.: Motivation and performance. Trends Issues Instr. Des. Technol. 2, 89–92 (2002)

    Google Scholar 

  49. Lidón, I., Rebollar, R., Møller, C.: A collaborative learning environment for management education based on experiential learning. Innov. Educ. Teach. Int. 48(3), 301–312 (2011)

    Article  Google Scholar 

  50. Roosta, F., Taghiyareh, F., Mosharraf, M.: Personalization of gamification-elements in an e-learning environment based on learners’ motivation. In: International Symposium on Telecommunications, pp. 637–642. IEEE (2017)

    Google Scholar 

  51. Townsend, R.: A Handbook for Teaching and Learning in Higher Education: Enhancing Academic Practice, 3rd edn. Kogan Page, New York (2009)

    Google Scholar 

  52. Kwon, K., Kim, C.: How to design personalization in a context of customer retention: who personalizes what and to what extent? Electron. Commer. Res. Appl. 11(2), 101–116 (2012)

    Article  MathSciNet  Google Scholar 

  53. Felicia, P.: Handbook of Research on Improving Learning and Motivation, p. 1003 (2011)

    Google Scholar 

  54. Hisatomi, K., Tomiyama, K., Katayama, M., Iwadate, Y.: Method of 3D reconstruction using graph cuts, and its application to preserving intangible cultural heritage. In: IEEE 
International Conference on Computer Vision Workshops, pp. 923–930. IEEE (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiaohong Sun .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ji, Y., Sun, X., Dai, X., Clark, S., Liu, Y., Fu, T. (2020). Extraction and Reuse of Pattern Configuration for Personalized Customization of Cantonese Porcelain Based on Artificial Intelligence. In: Kurosu, M. (eds) Human-Computer Interaction. Human Values and Quality of Life. HCII 2020. Lecture Notes in Computer Science(), vol 12183. Springer, Cham. https://doi.org/10.1007/978-3-030-49065-2_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-49065-2_20

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49064-5

  • Online ISBN: 978-3-030-49065-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics