Difference between revisions of "Feature-based matrix factorization"
Jump to navigation
Jump to search
m |
|||
| Line 5: | Line 5: | ||
without engineering efforts for writing codes for each new model. | without engineering efforts for writing codes for each new model. | ||
| − | + | ||
| − | |||
= Related Models = | = Related Models = | ||
* [[Factorization Machine]]: feature-based matrix factorization can be viewed as a restricted case of factorization machine to distinguish different types of features. | * [[Factorization Machine]]: feature-based matrix factorization can be viewed as a restricted case of factorization machine to distinguish different types of features. | ||
| + | |||
| + | = Implementation = | ||
| + | *[[SVDFeature]] is an efficient and scalable implementation of feature-based matrix factorization. | ||
= References = | = References = | ||
* [[User:Tqchen | Tianqi Chen]], Zhao Zheng, Qiuxia Lu and Yong Yu: Feature-based Matrix Factorization, http://arxiv.org/abs/1109.2271 | * [[User:Tqchen | Tianqi Chen]], Zhao Zheng, Qiuxia Lu and Yong Yu: Feature-based Matrix Factorization, http://arxiv.org/abs/1109.2271 | ||
[[Category:Method]] | [[Category:Method]] | ||
Revision as of 20:12, 23 September 2011
Feature-based matrix factorization is an abstract matrix factorization model that use features to describe the global bias and user/item factors. The the model allows development of new model simply by feature defining. We can incorporate information such as temporal information, neighborhood information, taxonomy information into feature-based matrix factorization to make the model informative. If we have a solver for feature-based matrix factorization, we only need to design context-aware or informative collaborative filtering(or ranking) models by feature-defining, without engineering efforts for writing codes for each new model.
Related Models
- Factorization Machine: feature-based matrix factorization can be viewed as a restricted case of factorization machine to distinguish different types of features.
Implementation
- SVDFeature is an efficient and scalable implementation of feature-based matrix factorization.
References
- Tianqi Chen, Zhao Zheng, Qiuxia Lu and Yong Yu: Feature-based Matrix Factorization, http://arxiv.org/abs/1109.2271
