Difference between revisions of "Li et al IJCAI 11"
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This a [[Category::Paper]] that appeared at the [http://ijcai.org/ International joint conference on Artificial Intelligence] 2011 | This a [[Category::Paper]] that appeared at the [http://ijcai.org/ International joint conference on Artificial Intelligence] 2011 | ||
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| + | == Citation == | ||
| + | Incorporating reviewer and product information for review rating prediction | ||
| + | Li, F. and Liu, N. and Jin, H. and Zhao, K. and Yang, Q. and Zhu, X. | ||
| + | Proceedings of the Twenty-Second international joint conference on Artificial Intelligence-Volume Volume Three | ||
| + | pages 1820--1825 | ||
| + | year 2011 | ||
| + | |||
| + | == Online version == | ||
| + | |||
| + | [http://www.cs.cmu.edu/~deepay/mywww/papers/icdm05.pdf Neighborhood Formation and Anomaly Detection in Bipartite Graphs] | ||
| + | |||
| + | == Summary == | ||
| + | |||
| + | This paper poses two interesting social problems on [[bipartite graph]] named [[AddressesProblem::Neighborhood formation and Anomaly detection]]. They also propose solutions based on [[UsesMethod::Random walk with restart]]. | ||
| + | |||
| + | The experimented on 3 real world social graphs [[UsesDataset::Conference-Author dataset]], [[UsesDataset::Author-Paper dataset]] and [[UsesDataset::IMDB dataset]] | ||
| + | |||
| + | == Evaluation == | ||
Revision as of 20:02, 26 September 2012
This a Paper that appeared at the International joint conference on Artificial Intelligence 2011
Contents
Citation
Incorporating reviewer and product information for review rating prediction Li, F. and Liu, N. and Jin, H. and Zhao, K. and Yang, Q. and Zhu, X. Proceedings of the Twenty-Second international joint conference on Artificial Intelligence-Volume Volume Three pages 1820--1825 year 2011
Online version
Neighborhood Formation and Anomaly Detection in Bipartite Graphs
Summary
This paper poses two interesting social problems on bipartite graph named Neighborhood formation and Anomaly detection. They also propose solutions based on Random walk with restart.
The experimented on 3 real world social graphs Conference-Author dataset, Author-Paper dataset and IMDB dataset
