| 摘要 |
A method and apparatus are disclosed for recommending items of interest to a user, such as television program recommendations. According to the principals of the invention, initial recommendations, which may be generated before a viewing history or purchase history of the user is available, are adapted or transformed to better capture a users viewing behavior using a feedback process. In particular, stereotypes are generated, which are used to build a stereotypical profiles. Stereotypical profiles are then generated that reflect the typical patterns of items selected by representative viewers. Recommendations are computed against a ground truth data using the stereotypical profiles, wherein distances are computed between each show in a so called ground truth data with the centroid of each stereotype in the stereotypical profile. If there is disagreement between what is computed recommendation and the original ground truth data, then additional feedback is solicited from a user, which is used to create a meta-profile. A meta-profile consists of the set of all weights the user has provided for the shows that he/she wants the shows to be recommended or discarded (e.g. positive/negative reinforcement). Lastly, the recommendation is recomputed using the meta-profile against the stereotypical profile.
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