Journal of Engineering and Applied Sciences

Year: 2017
Volume: 12
Issue: 10 SI
Page No. 8858 - 8863

Enhancing Content-Based Recommender System by Using Enriched User Profile

Authors : Ghaidaa Einas Al-Turkey and Huda Almamory

References

Abdullah, E., H. Nawaf and G. Bilal, 2016. User profile enrichment with correlative item contents and user context. Intl. J. Soc. Sci., 11: 4320-4322.
CrossRef  |  Direct Link  |  

Bae, S.M., K.H. Han and J.H. Park, 2012. Movie recommendation based on user profile and reviews. Proceedings of the WSEAS 1st International Conference on Latest Trends in Information Technology and Computer Engineering, November 10-12, 2012, WSEAS, Vienna, Austria, ISBN:978-1-61804-134-0, pp: 168-191.

Han, J., H.R. Schmidtke, X. Xie and W. Woo, 2014. Adaptive content recommendation for mobile users: Ordering recommendations using a hierarchical context model with granularity. Pervasive Mobile Comput., 13: 85-98.
Direct Link  |  

Inzunza, S., R. Juarez-Ramirez and A. Ramirez-Noriega, 2016. User and Context Information in Context-Aware Recommender Systems: A Systematic Literature Review. In: New Advances in Information Systems and Technologies, Rocha, A., M.C. Ana, A. Hojjat, P.R. Luis and M.T. Marcelo (Eds.). Springer, Berlin, Germany, ISBN:978-3-319-31231-6, pp: 649-658.

Kazienko, P. and P. Kolodziejski, 2006. Personalized integration of recommendation methods for E-commerce. Intl. J. Comput. Sci. Appl. IJCSA., 3: 12-26.

Kosir, A., A. Odic, M. Kunaver, M. Tkalcic and J.F. Tasic, 2011. Database for contextual personalization. Elektrotehniski Vestnik, 78: 270-274.
Direct Link  |  

Mladenic, D., 1999. Text-learning and related intelligent agents: A survey. IEEE. Intell. Syst. Appl., 14: 44-54.
CrossRef  |  Direct Link  |  

Odic, A., M. Tkalcic, J.F. Tasic and A. Kosir, 2013. Predicting and detecting the relevant contextual information in a movie-recommender system. Interacting Comput., 25: 74-90.
Direct Link  |  

Raj, N. and R.M.S. Suja, 2015. An overview of content recommendation methods. Intl. J. Innovative Res. Comput. Commun. Eng., 3: 334-339.
Direct Link  |  

Rajaraman, A. and J.D. Ullman, 2011. Mining of Massive Datasets. Cambridge University Press, UK., ISBN-13: 978-1107015357, Pages: 326.

Resnick, P. and H.R. Varian, 1997. Recommender systems. Commun. ACM., 40: 56-58.
CrossRef  |  Direct Link  |  

Ricci, F., L. Rokach and B. Shapira, 2011. Introduction to Recommender Systems Handbook. In: Recommender Systems Handbook, Ricci, F., L. Rokach, B. Shapira and P.B. Kantor (Eds.). Springer, New York, USA., ISBN:978-0-387-85819-7, pp: 1-35.

Schafer, J.B., D. Frankowski, J. Herlocker and S. Sen, 2007. Collaborative Filtering Recommender Systems. In: The Adaptive Web, Brusilovsky, P., K. Alfred and N. Wolfgang (Eds.). Springer, Berlin, Germany, ISBN:978-3-540-72079-9, pp: 291-324.

Thorat, P.B., R.M. Goudar and S. Barve, 2015. Survey on collaborative filtering, content-based filtering and hybrid recommendation system. Intl. J. Comput. Appl., 110: 31-36.
Direct Link  |  

Uluyagmur, M., Z. Cataltepe and E. Tayfur, 2012. Content-based movie recommendation using different feature sets. Proceedings of the World Congress on Engineering and Computer Science Vol. 1, October 24-26, 2012, WCECS, San Francisco, USA., ISBN:978-988-19251-6-9, pp: 17-24.

Zheng, Y., 2015. Context suggestion: Solutions and challenges. Proceedings of the 2015 IEEE International Conference on Data Mining Workshop (ICDMW), November 14-17, 2015, IEEE, Atlantic City, New Jersey, USA., ISBN:978-1-4673-8493-3, pp: 1602-1603.

Zheng, Y., B. Mobasher and R. Burke, 2016. User-oriented context suggestion. Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization, July 13-17, 2016, ACM, Halifax, Nova Scotia, Canada, ISBN:978-1-4503-4368-8, pp: 249-258.

Design and power by Medwell Web Development Team. © Medwell Publishing 2024 All Rights Reserved