Difference between revisions of "Feature-based matrix factorization"
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| − | Feature-based matrix factorization is an abstract matrix factorization model that | + | '''Feature-based matrix factorization''' is an abstract [[matrix factorization]] model that uses 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, | 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''. | taxonomy information into feature-based matrix factorization to make the model ''informative''. | ||
| 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 = | + | == Implementation == |
*[[SVDFeature]] is an efficient and scalable implementation of feature-based matrix factorization. | *[[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 04:57, 24 September 2011
Feature-based matrix factorization is an abstract matrix factorization model that uses 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
