Advertisement bidding method and device and electronic equipment
An advertising and probabilistic technology, applied in the Internet field, can solve problems such as unreasonable bidding methods, lower user conversion rates, and not in line with the actual interests of advertisers, so as to maximize actual benefits, increase conversion rates, and avoid wasting advertising investment.
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Embodiment 1
[0047] figure 1 A schematic flowchart of an advertising bidding method provided in Embodiment 1 of this specification, the method may specifically include the following steps:
[0048] In step S110, one or more advertisement bid requests are received, and the advertisement bid requests include information associated with users.
[0049] In one or more embodiments of this specification, when a user browses or accesses a certain media platform through a terminal device, if the media page in the media platform has an advertising space available for sale, the media platform will send a message to the predetermined advertiser Send traffic (which can be regarded as an advertisement bid request), and the advertisement bid request includes information associated with the user. In practical applications, the terminal device can be a mobile terminal (such as a mobile phone, a tablet computer, etc.), or a terminal device such as a PC; the media platform can also be called a third-party ...
Embodiment 2
[0075] image 3 A schematic flowchart of an advertisement bidding method provided in Embodiment 2 of this specification, the method may specifically include the following steps:
[0076] In step S310, one or more advertisement bid requests are received, and the advertisement bid requests include information associated with users.
[0077] In step S320, it is judged according to the information whether the user is a target user, and if the user is a target user, user characteristic data of the target user and advertisement characteristic data are acquired.
[0078] In the second embodiment, step S310 and step S320 correspond to step S110 and step S120 in the first embodiment. Please refer to the content in the foregoing embodiments for specific implementation, and details will not be repeated here. The following mainly introduces the second embodiment How to predict the conversion probability of the target user based on another deep learning model (the third deep learning mode...
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