Open Access
Issue |
MATEC Web of Conferences
Volume 44, 2016
2016 International Conference on Electronic, Information and Computer Engineering
|
|
---|---|---|
Article Number | 01005 | |
Number of page(s) | 5 | |
Section | Computer, Algorithm, Control and Application Engineering | |
DOI | https://doi.org/10.1051/matecconf/20164401005 | |
Published online | 08 March 2016 |
- WPEveland Jr, S Dunwoody. Examining information processing on the World Wide Web using think aloud protocols. MEDIAPSYCHOLOGY, 2 (2000) [Google Scholar]
- BBrown, M Chui, J Manyika. Are you ready for the era of ‘big data’. McKinsey Quarterly, 11 (2011) [Google Scholar]
- Tuan-Dung Cao, Quang-Minh Nguyen. Semantic approach to travel information search and itinerary recommendation. International Journal of Web Information Systems, 8, 3 (2012) [Google Scholar]
- Paolo Cremonesi, Franca Garzotto, Sara Negroet et al. Comparative evaluation of recommender system quality. CHI '11 Extended Abstracts on Human Factors in Computing Systems, (ACM, New York, 2011) [Google Scholar]
- GI Alptekin, Gülçin Büyüközkan. An integrated case-based reasoning and MCDM system for Web based tourism destination planning. Expert Systems with Applications,38,3(2011) [CrossRef] [Google Scholar]
- Xiaoyuan Su, Taghi M. Khoshgoftaar. A survey of collaborative filtering techniques. Advances in Artificial Intelligence, (2009) [Google Scholar]
- Adomavicius, G., Tuzhilin, A. 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(2005) [Google Scholar]
- Linden, G, Smith, B., York, J. Amazon.com recommendations: item-to-item collaborative filtering. IEEE Internet Computing, (IEEE Computer Society Press, Los Alamitos, 2003) [Google Scholar]
- Jonathan L Herlocker, Joseph A. Konstan, John Riedl. Explainingcollaborativefilteringrecommendations. Proceedings of the 2000 ACM conference on Computer, (ACM, New York, 2011) [Google Scholar]
- W. R. Gilks and P. Wild. Adaptive Rejection Sampling for Gibbs Sampling. Journal of the Royal Statistical Society. Series C (Applied Statistics), 2, 41(1992) [Google Scholar]
- Badrul Sarwar, George Karypis, Joseph Konstan, and John Riedl. Application of Dimensionality Reduction in Recommender System - A Case Study. Technical Report, (2000) [Google Scholar]
- Robin Burke. Hybrid Recommender Systems: Survey and Experiments. User Modeling and User-Adapted Interaction, 4, 12(2002) [Google Scholar]
- Lu, EH.-C., Chih-Yuan Lin, Tseng, V.S. Trip-Mine: An Efficient Trip Planning Approach with Travel Time Constraints. 2011 12th IEEE International Conference on Mobile Data Management (MDM) (IEEE Computer Society Press, Los Alamitos, 2007) [Google Scholar]
- G. D. Abowd, C. G. Atkeson, J. Hong, S. Long, R Kooper and M. Pinkerton. Cyberguide: A Mobile Context Aware Tour Guide. Wireless Networks, 5, 3 (1997) [Google Scholar]
- T. Horozov, N. Narasimhan, V. Vasudevan. Using Location for Personalized POI Recommendations in Mobile Environments. Proceedings of International Symposium on Applications on Internet, (IEEE Computer Society Press, Los Alamitos, 2006) [Google Scholar]
- Y.Zheng, X. Xie. Learning Travel Recommendations from User-Generated GPS Traces. ACM Transactions on Intelligent Systems and Technologies, 2, 2(2011) [Google Scholar]
- V.-W. Soo, S.-H. Liang. Recommending a Trip Plan by Negotiation with a Software Travel Agent. Cooperative Information Agents (Springer Berlin Heidelberg, 2001) [Google Scholar]
- Makoto Yokoo. Constraint Satisfaction Problem. Distributed Constraint Satisfaction, Springer Series on Agent Technology, (Springer Berlin Heidelberg, 2001) [CrossRef] [Google Scholar]
- Dietmar Jannach, Markus Zanker, Matthias Fuchs. Constraint-based recommendation in tourism: A multi-perspective case study, Information Technology & Tourism, 11 ( 2009) [Google Scholar]
- Tsang, E. Foundations of Constraint Satisfaction, (Academic Press, London and San Diego, 1993) [Google Scholar]
- A. Felfemig, G. Friedrich, D. Jannach, M. Zanker. Developing Constraint-based Recommenders, Recommender Systems Handbook, (Springer Berlin Heidelberg, 2011) [Google Scholar]
- Ricci, F., Mirzadeh, N., Bansal, M. Supporting user query relaxation in a recommender system. In: Proceedings of the 5th International Conference in E-Commerce and WebTechnologies - EC-Web, 2004: 31–40. [Google Scholar]
- WP Eveland Jr, S Dunwoody. Examining information processing on the World Wide Web using think aloud protocols. MEDIAPSYCHOLOGY, 2 (2000) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.