Abstract: The present disclosure relates to a method for feature construction, a method for content display and a related apparatus. The method for feature construction comprises: acquiring interaction data on a content page and loading performance data of the content page; constructing a user interaction feature according to the interaction data on the content page, and constructing a page performance feature of the content page according to the loading performance data of the content page. The user interaction feature and the page performance feature are used for training a content display model, and the content display model is used for determining target content displayed to a target user.

Abstract: The present disclosure relates to a web page classification method, apparatus, storage medium, and electronic device. The method comprises: acquiring feature information of a web page to be classified; respectively predicting, according to each piece of the feature information, a candidate web page category of the web page to be classified; and determining, from all the candidate web page categories, a target web page category to which the web page to be classified belongs. The candidate web page category of the web page to be classified is predicted by using various feature information of the web page to be classified, and the target web page category of the web page to be classified is further determined from the candidate web page categories, thereby improving the accuracy of web page classification.

Abstract: The present disclosure relates to an information distribution method, apparatus, and computer readable storage medium, which relates to the field of information processing. The information distribution method includes: determining a recommended value of a target indicator corresponding to a user based on a historical indicator of information historically distributed by the user and a historical indicator of a category to which the user belongs, wherein an indicator is determined based on resources gained and consumed through distributed information; recommending the recommended value of the target indicator to the user; determining target recipients of target information to be distributed by the user based on a target indicator input by the user, wherein the target indicator input by the user is determined based on the recommended value of the target indicator by the user; and sending the target information to the target recipients.

Abstract: After determining a trip order has a high risk, verification information unavailable in a passenger information database system can be requested and provided for a passenger of the account. Validity of the verification information can be determined using a verification service and stored in a passenger information database. A decision for the trip order can be determined based on the validity of the verification information stored in the passenger information database.

Abstract: After determining a trip order has a high risk, verification information unavailable in a passenger information database system can be requested and provided for a passenger of the account. Validity of the verification information can be determined using a verification service and stored in a passenger information database. A decision for the trip order can be determined based on the validity of the verification information stored in the passenger information database.

Abstract: After determining a trip order has a high risk, verification information unavailable in a passenger information database system can be requested and provided for a passenger of the account. Validity of the verification information can be determined using a verification service and stored in a passenger information database. A decision for the trip order can be determined based on the validity of the verification information stored in the passenger information database.

Abstract: Trips on a ride sharing platform may be monitored in order to predict abnormal trips. A set of fixed features may be obtained based on a trip on a ride sharing platform. A set of dynamic features may be obtained based on the trip on the ride sharing platform. The set of fixed features and the set of dynamic features may be input into a prediction model. The trip on the ride sharing platform may be classified based on an output of the prediction model. An action may be performed based on the classification of the trip on the ride sharing platform.

Abstract: After determining a trip order has a high risk, verification information unavailable in a passenger information database system can be requested and provided for a passenger of the account. Validity of the verification information can be determined using a verification service and stored in a passenger information database. A decision for the trip order can be determined based on the validity of the verification information stored in the passenger information database.