Application of Multi-Attribute Rating Matrix in KNN Collaborative Filtering

this evaluation algorithm based on Attribute Rating Matrix is inefficient in the case of cold-start. The Application of Multi-Attribute Rating Matrix can solve the problem effectively. The situations are analyzed to create their attribute-tables. The ratings are mapped to the relevant attributes generate a User Attribute-Item Attribute Rating Matrix (UAIARM). After UAIARM is simplified, MARM will be created. When a new item enters into this system, the attributes of new item and MARM are matched to find the N items with the highest match degrees as the target of the new items or the recommended items. Experiment results validate the improved algorithm based on MARM is efficient.