Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2016 (2016), Article ID 9535808, 10 pages
http://dx.doi.org/10.1155/2016/9535808
Research Article

A Probability-Based Hybrid User Model for Recommendation System

1School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
2Beijing Institute of Astronautic System Engineering, Beijing 310027, China

Received 13 July 2015; Revised 16 December 2015; Accepted 20 December 2015

Academic Editor: Matteo Gaeta

Copyright © 2016 Jia Hao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. A. A. Ammar, D. Scaravetti, and J. P. Nadeau, “Knowledge reuse: towards a design tool,” in Proceedings of the 11th International Design Conference (DESIGN '10), pp. 1451–1460, Dubrovnik, Croatia, May 2010. View at Scopus
  2. Y. S. Kim and K.-Y. Kim, “DCR-based causal design knowledge evaluation method and system for future CAD applications,” CAD Computer Aided Design, vol. 44, no. 10, pp. 947–960, 2012. View at Publisher · View at Google Scholar · View at Scopus
  3. N. Reed, J. Scanlan, G. Wills, and S. T. Halliday, “Knowledge use in an advanced manufacturing environment,” Design Studies, vol. 32, no. 3, pp. 292–312, 2011. View at Publisher · View at Google Scholar · View at Scopus
  4. J. H. Ge, Y. P. Wang, J. Zhang, and H. Gao, “Research on method of product configuration design based on product family ontology model,” International Journal of Database Theory and Application, vol. 6, no. 4, pp. 169–178, 2013. View at Google Scholar
  5. J. Hao, Y. Yan, G. Wang, L. Gong, and J. Lin, “A user-oriented design knowledge reuse model,” ISRN Industrial Engineering, vol. 2013, Article ID 928013, 10 pages, 2013. View at Publisher · View at Google Scholar
  6. M. Y. H. Al-Shamri and K. K. Bharadwaj, “Fuzzy-genetic approach to recommender systems based on a novel hybrid user model,” Expert Systems with Applications, vol. 35, no. 3, pp. 1386–1399, 2008. View at Publisher · View at Google Scholar · View at Scopus
  7. J. Lu, D. S. Wu, M. S. Mao, W. Wang, and G. Zhang, “Recommender system application developments: a survey,” Decision Support Systems, vol. 74, pp. 12–32, 2015. View at Publisher · View at Google Scholar
  8. S. Bergamaschi, F. Guerra, and B. Leiba, “Guest editors' introduction: information overload,” IEEE Internet Computing, vol. 14, no. 6, pp. 10–13, 2010. View at Publisher · View at Google Scholar · View at Scopus
  9. S. Wan, C. Paris, and R. Dale, “Supporting browsing-specific information needs: Introducing the Citation-Sensitive In-Browser Summariser,” Journal of Web Semantics, vol. 8, no. 2-3, pp. 196–202, 2010. View at Publisher · View at Google Scholar · View at Scopus
  10. H.-N. Kim, I. Ha, K.-S. Lee, G.-S. Jo, and A. El-Saddik, “Collaborative user modeling for enhanced content filtering in recommender systems,” Decision Support Systems, vol. 51, no. 4, pp. 772–781, 2011. View at Publisher · View at Google Scholar · View at Scopus
  11. J. P. Michael and B. Daniel, “Content-based recommendation systems,” in The Adaptive Web, pp. 325–341, Springer, Berlin, Germany, 2007. View at Google Scholar
  12. J. B. Schafer, D. Frankowski, J. Herlocker, and S. Sen, “Collaborative filtering recommender systems,” in The Adaptive Web, pp. 291–324, Springer, Berlin, Germany, 2007. View at Google Scholar
  13. R. Burke, “Knowledge-based recommender systems,” Encyclopedia of Library and Information System, vol. 69, no. 2000, pp. 175–186, 2000. View at Google Scholar
  14. S. K. Shinde and U. Kulkarni, “Hybrid personalized recommender system using centering-bunching based clustering algorithm,” Expert Systems with Applications, vol. 39, no. 1, pp. 1381–1387, 2012. View at Publisher · View at Google Scholar · View at Scopus
  15. R. Burke, “Hybrid web recommender systems,” in The Adaptive Web, vol. 4321 of Lecture Notes in Computer Science, pp. 377–408, Springer, Berlin, Germany, 2007. View at Publisher · View at Google Scholar
  16. E. M. Stuart, D. R. David, and R. S. Nigel, “Ontology-based recommender systems,” in Handbook on Ontologies, pp. 779–796, Springer, Berlin, Germany, 2009. View at Google Scholar
  17. T. Bogers, M. Koolen, and I. Cantador, “Workshop on new trends in content-based recommender systems,” in Proceedings of the 8th ACM Conference on Recommender systems (RecSys '14), pp. 379–380, ACM, Foster City, Calif, USA, October 2014. View at Publisher · View at Google Scholar
  18. A. H. Mohd, A. J. Omar, and S. Ramachandram, “Collaborative filtering based recommendation system: a survey,” International Journal on Computer Science and Engineering, vol. 4, no. 5, pp. 859–876, 2012. View at Google Scholar
  19. C. C. Chen, Y.-H. Wan, M.-C. Chung, and Y.-C. Sun, “An effective recommendation method for cold start new users using trust and distrust networks,” Information Sciences, vol. 224, pp. 19–36, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  20. N. Rastin and M. Zolghadri Jahromi, “Using content features to enhance the performance of user-based collaborative filtering,” International Journal of Artificial Intelligence & Applications, vol. 5, no. 1, pp. 53–62, 2014. View at Publisher · View at Google Scholar
  21. L. Yao, Q. Z. Sheng, A. Segev, and J. Yu, “Recommending web services via combining collaborative filtering with content-based features,” in Proceedings of the IEEE 20th International Conference on Web Services (ICWS '13), pp. 42–49, IEEE, Santa Clara Marriott, Calif, USA, July 2013. View at Publisher · View at Google Scholar · View at Scopus
  22. R. Ronen, N. Koenigstein, E. Ziklik, and N. Nice, “Selecting content-based features for collaborative filtering recommenders,” in Proceedings of the 7th ACM Conference on Recommender Systems (RecSys '13), pp. 407–410, Hong Kong, October 2013. View at Publisher · View at Google Scholar · View at Scopus
  23. A. B. Barragáns-Martínez, E. Costa-Montenegro, J. C. Burguillo, M. Rey-López, F. A. Mikic-Fonte, and A. Peleteiro, “A hybrid content-based and item-based collaborative filtering approach to recommend TV programs enhanced with singular value decomposition,” Information Sciences, vol. 180, no. 22, pp. 4290–4311, 2010. View at Publisher · View at Google Scholar · View at Scopus
  24. S. Berkovsky, T. Kuflik, and F. Ricci, “Mediation of user models for enhanced personalization in recommender systems,” User Modeling and User-Adapted Interaction, vol. 18, no. 3, pp. 245–286, 2008. View at Publisher · View at Google Scholar · View at Scopus
  25. S. Berkovsky, T. Kuflik, and F. Ricci, “Cross-representation mediation of user models,” User Modeling and User-Adapted Interaction, vol. 19, no. 1-2, pp. 35–63, 2009. View at Publisher · View at Google Scholar · View at Scopus
  26. M. Degemmis, P. Lops, and G. Semeraro, “A content-collaborative recommender that exploits WordNet-based user profiles for neighborhood formation,” User Modeling and User-Adapted Interaction, vol. 17, no. 3, pp. 217–255, 2007. View at Publisher · View at Google Scholar · View at Scopus
  27. F. Ricci, L. Rokach, and B. Shapira, “Introduction to recommender systems handbook,” in Recommender Systems Handbook, pp. 1–35, Springer, New York, NY, USA, 2011. View at Publisher · View at Google Scholar
  28. A. Moreno, A. Valls, D. Isern, L. Marin, and J. Borràs, “SigTur/E-destination: ontology-based personalized recommendation of tourism and leisure activities,” Engineering Applications of Artificial Intelligence, vol. 26, no. 1, pp. 633–651, 2013. View at Publisher · View at Google Scholar · View at Scopus
  29. G. Adomavicius and A. Tuzhilin, “Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions,” IEEE Transactions on Knowledge and Data Engineering, vol. 17, no. 6, pp. 734–749, 2005. View at Publisher · View at Google Scholar · View at Scopus
  30. E. Vozalis and K. G. Margaritis, “Analysis of recommender systems algorithms,” in Proceedings of the 6th Hellenic European Conference on Computer Mathematics and its Applications, Athens, Greece, 2003.
  31. P. Resnick, N. Iacovou, M. Suchak, and P. Bergstrom, “GroupLens: an open architecture for collaborative filtering of netnews,” in Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW '94), pp. 175–186, ACM, Chapel Hill, NC, USA, October 1994. View at Publisher · View at Google Scholar
  32. J. L. Herlocker, J. A. Konstan, L. G. Terveen, and J. T. Riedl, “Evaluating collaborative filtering recommender systems,” ACM Transactions on Information Systems, vol. 22, no. 1, pp. 5–53, 2004. View at Publisher · View at Google Scholar · View at Scopus