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- Description:
SVDFeature is a toolkit developed by Apex Data & Knowledge Management Lab during the competition of KDDCup'11. It is designed to solve the feature-based matrix factorization efficiently. New models can be developed just by defining new features. The feature-based setting allows us to include many kinds of information into the model, making the model informative. Using the toolkit, we can easily incorporate information such as temporal dynamics, neighborhood relationship, and hierarchical information into the model. Both learning to rank and rate prediction models are supported.
- Changes to previous version:
Initial Announcement on mloss.org.
- BibTeX Entry: Download
- Supported Operating Systems: Linux, Windows, Unix
- Data Formats: Ascii
- Tags: Collaborative Filtering, Contextual Aware Recommendation, Kddcup2011
- Archive: download here
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