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2010 IEEE International Conference on Data Mining Workshops
Parallel User Profiling Based on Folksonomy for Large Scaled Recommender Systems: An Implimentation of Cascading MapReduce
Sydney, Australia
December 13-December 13
ISBN: 978-0-7695-4257-7
| ASCII Text | x | ||
| Huizhi Liang, Jim Hogan, Yue Xu, "Parallel User Profiling Based on Folksonomy for Large Scaled Recommender Systems: An Implimentation of Cascading MapReduce," 2012 IEEE 12th International Conference on Data Mining Workshops, pp. 154-161, 2010 IEEE International Conference on Data Mining Workshops, 2010. | |||
| BibTex | x | ||
| @article{ 10.1109/ICDMW.2010.161, author = {Huizhi Liang and Jim Hogan and Yue Xu}, title = {Parallel User Profiling Based on Folksonomy for Large Scaled Recommender Systems: An Implimentation of Cascading MapReduce}, journal ={2012 IEEE 12th International Conference on Data Mining Workshops}, volume = {0}, year = {2010}, isbn = {978-0-7695-4257-7}, pages = {154-161}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDMW.2010.161}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - 2012 IEEE 12th International Conference on Data Mining Workshops TI - Parallel User Profiling Based on Folksonomy for Large Scaled Recommender Systems: An Implimentation of Cascading MapReduce SN - 978-0-7695-4257-7 SP154 EP161 A1 - Huizhi Liang, A1 - Jim Hogan, A1 - Yue Xu, PY - 2010 KW - User Profiling KW - Large Scales Recommender Systems KW - Cloud Computing KW - Tags KW - Folksonomy KW - Web 2.0 VL - 0 JA - 2012 IEEE 12th International Conference on Data Mining Workshops ER - | |||
The Large scaled emerging user created information in web 2.0 such as tags, reviews, comments and blogs can be used to profile users¡¯ interests and preferences to make personalized recommendations. To solve the scalability problem of the current user profiling and recommender systems, this paper proposes a parallel user profiling approach and a scalable recommender system. The current advanced cloud computing techniques including Hadoop, MapReduce and Cascading are employed to implement the proposed approaches. The experiments were conducted on Amazon EC2 Elastic MapReduce and S3 with a real world large scaled dataset from Delicious website.
Index Terms:
User Profiling, Large Scales Recommender Systems, Cloud Computing, Tags, Folksonomy, Web 2.0
Citation:
Huizhi Liang, Jim Hogan, Yue Xu, "Parallel User Profiling Based on Folksonomy for Large Scaled Recommender Systems: An Implimentation of Cascading MapReduce," icdmw, pp.154-161, 2010 IEEE International Conference on Data Mining Workshops, 2010
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