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| incremental learning of triadic plsa for collaborative filtering | |
| Wu Hu; Wang Yongji | |
| 2009 | |
| Conference Name | 5th International Conference on Active Media Technology |
| Source | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Conference Date | OCT 22-24, |
| Conference Place | Beijing, PEOPLES R CHINA |
| Publish Place | HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY |
| Publisher | ACTIVE MEDIA TECHNOLOGY, PROCEEDINGS |
| ISSN | 0302-9743 |
| ISBN | 978-3-642-04874-6 |
| Department | Wu, Hu; Wang, Yongji Chinese Acad Sci, Inst Software, Beijing, Peoples R China. |
| English Abstract | PLSA which was originally introduced in text analysis area, has been extended to predict user ratings in the collaborative filtering context, known as Triadic PLSA (TPLSA). It is a promising recommender technique but the computational cost is a bottleneck for huge data set. We design a incremental learning scheme for TPLSA for collaborative filtering task that could make forced prediction and free prediction as well. Our incremental implementation is the first of its kind in the probabilistic model based collaborative filtering area, to our best knowledge. Its effectiveness is validated by experiments designed for both rating-based and ranking-based collaborative filtering. |
| Keyword | Blood Vessel Prostheses Data Flow Analysis Forecasting |
| Sponsorship | Beijing University of Technology (BJUT); Beijing Municipal Lab of Brain Informatics; Chinese Society of Radiology; National Natural Science Foundation of China (NSFC); State Administration of Foreign Experts Affairs |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/8298 |
| Collection | 互联网软件技术实验室 |
| Recommended Citation GB/T 7714 | Wu Hu,Wang Yongji. incremental learning of triadic plsa for collaborative filtering[C]. HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY:ACTIVE MEDIA TECHNOLOGY, PROCEEDINGS,2009. |
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| File Name/Size | DocType | Version | Access | License | ||
| incremental learning（298KB） | 开放获取 | -- | Application Full Text | |||
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