A Study on Recommendation Method Based on Web 3.0

  • Published : 2012.12.30

Abstract

Web 3.0 is the next-generation of the World Wide Web and is included two main platforms, semantic technologies and social computing environment. The basic idea of web 3.0 is to define structure data and link them in order to more effective discovery, automation, integration, and reuse across various applications. The semantic technologies represent open standards that can be applied on the top of the web. The social computing environment allows human-machine co-operations and organizing a large number of the social web communities. In the recent years, recommender systems have been combined with ontologies to further improve the recommendation by adding semantics to the context on the web 3.0. In this paper, we study previous researches about recommendation method and propose a recommendation method based on web 3.0. Our method scores documents based on context tags and social network services. Our social scoring model is computed by both a tagging score of a document and a tagging score of a document that was tagged by a user's friends.

Keywords

References

  1. Sareh Aghaei, Mohammad Ali Nematbakhsh and Hadi Khosravi Farsani, "Evoution of the World Wide Web: From the WEB 1.0 to WEB 4.0," International Journal of Web & Semantic Technology (IJWesT) Vol. 3, No. 1, January 2012
  2. Christine Beuchert, Trevor Stuart-Hill, Frederic W. Malek, "Web 3.0 : Emerging Insights for Travel Marketers," A special report from the HSMAI Travel Internet Marketing Special Interest Group.
  3. Norasak, Suphakorntanakit (2008), "Web 3.0," .
  4. Tim Berners-Lee. "The World Wide Web: A very short personal history," http://www.w3.org/People/Berners-Lee/ShortHistory.html, 1998.
  5. San, Murugesan,, "Understanding Web 2.0," Journal IT Professional, 2007.
  6. Nova, Spivack, "Web 3.0: The Third Generation Web is Coming," http://lifeboat.com/ex/web. 3.0, 2011.
  7. Ossi, Nykanen, "Semantic Web: Definition," .
  8. Sean B, Palmer, "The Semantic Web: An Introduction," , 2001.
  9. boyd, d., & Ellison, N. B., "Social network sites: Definition, history, and scholarship," Journal of Computer-Mediated Communication, Vol. 13, No. 21, 2008, pp. 210-230.
  10. Elizabeth F. Churchill, Christine A. Halverson, "Social Networks and Social Networking," IEEE internet computing, Vol 9, Issue 5, 2005, pp. 14-19.
  11. Yoon, Tae Hyun, Kwon, Joon Hee, "Design and Implementation of Social Search System using user Context and Tag," Vol. 8, No. 3, KSDIM, 2012.
  12. Alan E. Mislove, "Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems," Rice University, 2010.
  13. Resnick P, Iacovou N, Suchak M, Bergstrom P, Riedl Grouplens: "An open architecture for collaborative filtering of netnews," In: CSCW, 1994, pp. 175-186.
  14. Xujuan Zhou, Yue Xu, Yuefeng Li, Audun Josang and Clive Cox, "The State-of-the-Art in Personalized Recommender Systems for Social Networking," Journal Artificial Intelligence Review Vol. 37 Issue 2, February 2012, pp. 119-132. https://doi.org/10.1007/s10462-011-9222-1
  15. Kim, Sung Rim, Kwon, Joon Hee, "Recommendation Method for Social Service in Ubiquitous Environment," Vol. 7, No. 2, KSDIM, 2011.
  16. Andreas Emrich, Alexandra Chapko, Marc Grable, Dirk Werth, "Personalized and situation-aware recommendation runners," In proceeding of: Pacific Asia Conference on Information Systems, PACIS 2011.
  17. Wolney L. de Mello Neto, Ann Nowe, "Insights on Social Recommender System," Workshop on Recommendation Utility Evaluation: Beyond RMSE (RUE 2012).
  18. B. Sigurbjornsson and R. van Zwol. "Flickr tag recommendation based on collective knowledge," In International conference on World Wide Web, 2008, pp. 327-336.
  19. Adam Rae, Borkur Sigurbjornsson, Roelof van Zwol, "Improving Tag Recommendation Using Social Networks," RIAO, 2010.
  20. Wolfgang Woerndl and Georg Groh, "Utilizing Physical and Social Context to Improve Recommender Systems," Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, 2007, pp. 123-128.
  21. Sungrim Kim, and Joonhee Kwon, "Effective Context-aware Recommendation on the Semantic Web," IJCSNS, 2007.