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Semantic Learning Service Personalized

  • Research Article
  • Open access
  • Published: 01 February 2012
  • Volume 5, pages 163–172, (2012)
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International Journal of Computational Intelligence Systems Aims and scope Submit manuscript
Semantic Learning Service Personalized
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  • Yibo Chen1,
  • Chanle Wu2,
  • Xiaojun Guo1 &
  • …
  • Jiyan Wu1 
  • 67 Accesses

  • 2 Citations

  • Explore all metrics

Abstract

To provide users with more suitable and personalized service, personalization is widely used in various fields. Current e-Learning systems search for learning resources using information search technology, based on the keywords that selected or inputted by the user. Due to lack of semantic analysis for keywords and exploring the user contexts, the system cannot provide a good learning experiment. In this paper, we defined the concept and characteristic of the personalized learning service, and proposed a semantic learning service personalized framework. Moreover, we made full use of semantic technology, using ontologies to represent the learning contents and user profile, mining and utilizing the friendship and membership of the social relationship to construct the user social relationship profile, and improved the collaboration filtering algorithm to recommend personalized learning resources for users. The results of the empirical evaluation show that the approach is effectiveness in augmenting recommendation.

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  • eLearning
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References

  1. Dagger, D. O'Connor, A. Lawless, S. Walsh, E. Wade, V.P Service-Oriented E-Learning Platforms From Monolithic Systems to Flexible Services, Internet Computing. 11(3)(2007):28–35.

  2. Leyla Zhuhadar, Olfa Nasraoui. Semantic Information Retrieval for Personalized E-Learning. 20th IEEE International Conference on Tools with Artificial Intelligence (vol. 1, 2008), pp.364–368.

  3. L. Chen, K. Sycara. WebMate: A Personal Agent for Browsing and Searching. (Autonomous Agents and Multi Agent Systems, 1998).

  4. J. Budzik, J. K. Hammond. Watson: Anticipating and contextualizing information needs, in Proceedings of the Sixty-second Annual Meeting of the American Society for Information Science, 1999.

  5. E. Glover, G. Flake, S. Lawrence, W. Birmingham, A. Kruger, C. Giles, D. Pennock. Improving Category Specific Web Search by Learning Query Modifications. (SAINT, 2001).

  6. 6. A. Pretschner, S. Gauch. Ontology based personalized search. (ICTAI, 1999).

  7. M. Speretta, S. Gauch. Personalized search based on user search histories. In Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2005 (Compigne, France, September 2005), pp. 622–628.

  8. A. Micarelli, F. Sciarrone. Anatomy and empirical evaluation of an adaptive web-based information filtering system, User Modeling and User-Adapted Interaction. 14(2–3)(2004)159–200.

  9. P. A. Chirita, W. Nejdl, R. Paiu, C. Kohlschutter. Using odp metadata to personalize search, in Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2005 (Salvador, Brazil, August 2005), pp. 178–185.

  10. C. Ziegler, K. Simon, G. Lausen. Automatic computation of semantic proximity using taxonomic knowledge, in Proceedings of the 15th ACM International Conference on Information and Knowledge Management, CIKM 2006 (Arlington, VA, November 2006), pp. 465–474.

  11. F. Liu, C. Yu, W. Meng. Personalized web search for improving retrieval effectiveness, IEEE Transactions on Knowledge and Data Engineering. 16(1)(2004) 28–40.

  12. P. Chirita, C. Firan, W. Nejdl. Summarizing local context to personalize global web search, in Proceedings of the 15th ACM International Conference on Information and Knowledge Management, CIKM 2006 (Arlington, VA, November 2006), pp. 287–296.

  13. F. Tanudjaja and L. Mui. Persona: A contextualized and personalized web search. In Proceedings of the 35th Annual Hawaii International Conference on System Sciences, HICSS 2002 (Big Island, Hawaii, January 2002), p. 67.

  14. A. Sieg, B. Mobasher, R. Burke. Learning Ontology-Based User Profiles: A Semantic Approach to Personalized Web Search, IEEE Intelligent Informatics Bulletin. (2007)

  15. Recker M, Walker A. Supporting ‘word-of-mouth’ social networks via collaborative information filtering, Journal of Interactive Learning Research. 14(2003)79–98.

  16. Walker A., Recker M., Lawless K, Wiley D. Collaborative information filtering: a review and an educational application, International Journal of Artificial Intelligence in Education. 14(2004)1–26.

  17. Lemire D. Scale and translation invariant collaborative filtering systems, Information Retrieval. 8(2005)129–150.

  18. Rafaeli S, Dan-Gur Y, Barak M. Social recommender systems: recommendations in support of e-learning, Journal of Distance Education Technologies. 3(2005)29–45.

  19. Avancini H, Straccia U. User recommendation for collaborative and personalized digital archives, International Journal of Web Based Communities. 1(2005)163–175.

  20. Shen L, Shen R. Learning content recommendation service based on simple sequencing specification, in Proc. of the ICWL 2004, Vol. 3143, 2004, pp. 363–370.

  21. Tang T.Y, McCalla G.I. Smart recommendation for an evolving e-learning system: architecture and experiment, International Journal on E-Learning. 4(2005)105–129.

  22. Drachsler H, Hummel H.G.K, Koper R. Recommendations for learners are different: applying memory-based recommender system techniques to lifelong learning, in Proc. of the Workshop on Social Information Retrieval in Technology Enhanced Learning (SIRTEL 2007), 2007, pp.18–26.

  23. Drachsler H, Hummel H.G.K, Van den Berg B, Eshuis J, Berlanga A, Nadolski R, Waterink W, Boers N, Koper R. Effects of the ISIS Recommender System for navigation support in self-organized learning networks, Journal of Educational Technology & Society. 12(2009)122–135.

  24. Feng Tian, Qinghua Zheng, Ruomeng Zhao, Tonghao Chen, Xinyan Jia. Can e-learner's emotion be recognized from interactive Chinese texts, in proceedings of the 2009 13th International Conference on Computer Supported Cooperative Work in Design (CSCWD 2009), pp.546–551.

  25. N. Manouselis, R. Vuorikari, F. Van Assche. Collaborative recommendation of e-learning resources: an experimental investigation, Journal of Computer Assisted Learning. 26(2010)227–242

  26. Salton, G. The SMART retrieval system: experiments in automatic document processing. (New Jersey: Prentice Hall, 1971)

  27. Salton, G. Automatic text processing. (MA: Addison-Wesley Publishing Co, 1988)

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Authors and Affiliations

  1. Computer School of Wuhan University, Wuhan, Hubei, China

    Yibo Chen, Xiaojun Guo & Jiyan Wu

  2. Computer School of Wuhan University, National Engineering Research Center for Multimedia Software, Wuhan, Hubei, China

    Chanle Wu

Authors
  1. Yibo Chen
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  2. Chanle Wu
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  3. Xiaojun Guo
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  4. Jiyan Wu
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Corresponding author

Correspondence to Yibo Chen.

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This is an open access article distributed under the CC BY-NC license (https://doi.org/creativecommons.org/licenses/by-nc/4.0/).

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Chen, Y., Wu, C., Guo, X. et al. Semantic Learning Service Personalized. Int J Comput Intell Syst 5, 163–172 (2012). https://doi.org/10.1080/18756891.2012.670528

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  • Received: 26 October 2011

  • Accepted: 30 January 2012

  • Published: 01 February 2012

  • Issue Date: February 2012

  • DOI: https://doi.org/10.1080/18756891.2012.670528

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Keywords

  • personalized learning service
  • semantic information search
  • ontology
  • collaboration filtering
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