Abstract
A concept is a key phrase which can represent an entity, event or idea that people are interested in. Concept-centric Web news recommendation is a novel content-based recommendation paradigm which can partially alleviate the cold-start problem and provide better recommendation results in terms of diversity than traditional news recommendation systems, as it can capture users’ interest in a natural way and can even recommend a new Web news to a user as long as it is conceptually relevant to a main concept of the Web news the user is browsing. This demonstration paper presents a novel CONcept-Centric nEws Recommendation sysTem called CONCERT. CONCERT consists of two parts: (1) A concept extractor which is based on machine learning algorithms and can extract main concepts from Web news pages, (2) A real-time recommender which recommends conceptually relevant Web news to a user based on the extracted concepts.
The demonstration system of the CONCERT system is available online at: http://dmgroup.cs.tsinghua.edu.cn/CONCERT/main.html
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Balabanovic, M., Shoham, Y.: Fab: Content-based, collaborative recommendation. Communications of the ACM 40(3), 66–72 (1997)
Chen, T., Han, W., Wang, H., Zhou, Y., Xu, B., Zang, B.: Content Recommendation System Based on Private Dynamic User Profile. In: Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, August 19-22 (2007)
Salton, G.: Automatic Text Processing. Addison-Wesley (1989)
Parameswaran, A., Rajaraman, A., Garcia-Molina, H.: Towards the Web of Concepts: Extracting Concepts from Large Datasets. In: VLDB 2010 (2010)
Witten, I.H., Paynter, G.W., Frank, E., Gutwin, C., Nevill-Manning, C.G.: KEA: Practical Automatic Keyphrase Extraction. In: DL 1999 Proceedings of the Fourth ACM Conference on Digital Libraries, pp. 254–255 (1999)
Liu, Z., Chen, X., Zheng, Y., Sun, M.: Automatic Keyphrase Extraction by Bridging Vocabulary Gap. In: Proceedings of the 15th Conference on Computational Natural Language Learning, CoNLL (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ren, H., Feng, W. (2013). CONCERT: A Concept-Centric Web News Recommendation System. In: Wang, J., Xiong, H., Ishikawa, Y., Xu, J., Zhou, J. (eds) Web-Age Information Management. WAIM 2013. Lecture Notes in Computer Science, vol 7923. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38562-9_82
Download citation
DOI: https://doi.org/10.1007/978-3-642-38562-9_82
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38561-2
Online ISBN: 978-3-642-38562-9
eBook Packages: Computer ScienceComputer Science (R0)