ABSTRACT
With the rapid development of smart devices and wireless communication, especially with the pre-launch of Google Glass, augmented reality (AR) has received enormous attention recently. AR adds virtual objects into a user's real-world environment enabling live interaction in three dimensions. Limited by the small display of AR devices, content selection is one of the key issues to improve user experience. In this paper, we present an aggregated random walk algorithm incorporating personal preferences, location information, and temporal information in a layered graph. By adaptively changing the graph edge weight and computing the rank score, the proposed AR recommender system predicts users' preferences and provides the most relevant recommendations with aggregated information.
- G. Adomavicius, R. Sankaranarayanan, S. Sen, and A. Tuzhilin. Incorporating contextual information in recommender systems using a multidimensional approach. ACM Transactions on Information Systems, 23(1):103--145, 2005. Google ScholarDigital Library
- 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, 17(6):734--749, 2005. Google ScholarDigital Library
- M. Allamanis, S. Scellato, and C. Mascolo. Evolution of a location-based online social network: analysis and models. In Proceedings of the 2012 ACM Internet Measurement Conference, pages 145{158. ACM, 2012. Google ScholarDigital Library
- R. T. Azuma et al. A survey of augmented reality. Presence-Teleoperators and Virtual Environments, 6(4):355--385, 1997.Google ScholarCross Ref
- R. M. Bell and Y. Koren. Improved neighborhood-based collaborative filtering. In KDD Cup and Workshop at the 13th ACM SIGKDD, 2007.Google Scholar
- S. Benford and L. Fahl--en. A spatial model of interaction in large virtual environments. In Proceedings of the 3rd Conference on European Conference on Computer-Supported Cooperative Work, pages 109--124. Kluwer Academic Publishers, 1993. Google ScholarDigital Library
- S. Brin and L. Page. The anatomy of a large-scale hypertextual web search engine. Computer Networks and ISDN Systems, 30(1):107--117, 1998. Google ScholarDigital Library
- F. Ricci. Mobile recommender systems. Information Technology & Tourism, 12(3):205--231, 2010.Google ScholarCross Ref
- F. Ricci and Q. N. Nguyen. Acquiring and revising preferences in a critique-based mobile recommender system. Intelligent Systems, 22(3):22--29, 2007. Google ScholarDigital Library
- S. Shang, S. R. Kulkarni, P. W. Cu, and P. Hui. A random walk based model incorporating social information for recommendations. In 2012 International Workshop on Machine Learning and Signal Processing, pages 1--6. IEEE, 2012.Google ScholarCross Ref
- K. H. Tso-Sutter, L. B. Marinho, and L. Schmidt-Thieme. Tag-aware recommender systems by fusion of collaborative filtering algorithms. In Proceedings of the 2008 ACM Symposium on Applied computing, pages 1995--1999. ACM, 2008. Google ScholarDigital Library
- L. Xiang, Q. Yuan, S. Zhao, L. Chen, X. Zhang, Q. Yang, and J. Sun. Temporal recommendation on graphs via long-and short-term preference fusion. In Proceedings of the 16th ACM SIGKDD, pages 723--732. ACM, 2010. Google ScholarDigital Library
Index Terms
- Improving augmented reality using recommender systems
Recommendations
Improving Accuracy of Recommender System by Item Clustering
Recommender System (RS) predicts user's ratings towards items, and then recommends highly-predicted items to user. In recent years, RS has been playing more and more important role in the agent research field. There have been a great deal of researches ...
Integrating augmented reality into print media: use case analyses and user interface development
AcademicMindTrek '14: Proceedings of the 18th International Academic MindTrek Conference: Media Business, Management, Content & ServicesMobile technologies offer an extremely wide range of possibilities which were still unimaginable a few years ago. Smartphones enable a ubiquitous connection to the internet and Augmented Reality (AR) allows the interaction of virtual entities with the ...
Haptics in Augmented Reality
ICMCS '99: Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2An augmented reality system merges synthetic sensory information into a user's perception of a three-dimensional environment. An important performance goal for an augmented reality system is that the user perceives a single seamless environment. In most ...
Comments