Abstract: According to the embodiments of the present disclosure, a method for conversion evaluation comprises: extracting a resource feature from resource-related data of a target resource; extracting an audience feature of the target audience group from audience-related data of a target audience group of the target resource, the target audience group being to be distributed with a recommended content item related to the target resource; and determining, based on the resource feature and the audience feature, a target predicted conversion rate for the target resource through a predetermined association between resource features, audience features and predicted conversion rates, the target predicted conversion rate indicating a predicted probability of the target audience group performing a conversion for the target resource. According to the scheme, the accuracy of the conversion rate evaluation may be improved, thereby improving distribution effect of the recommended content item for a resource.

Abstract: A method, apparatus, device and storage medium for recommending information. The method includes determining, based on a set of feature representations of a plurality of features associated with information recommendation, a first set of weights indicating importance of the plurality of features. The method also includes determining a second set of weights based on the set of feature representations and the first set of weights. The method further includes recommending the information to a user based on the set of feature representations, the first set of weights and the second set of weights. The importance of respective features associated with the information recommendation can be accurately determined through this method, which further improves the effectiveness of information recommendation and improves the user experience.