Information processing method and device, electronic equipment and storage medium

Abstract

The invention provides an information processing method and device, electronic equipment and a storage medium, and relates to the technical fields of information recommendation, advertisement bidding and the like. According to the specific implementation scheme, the method comprises the following steps: receiving interaction request information sent by a client, and obtaining a traffic prediction value of the interaction request information for candidate delivery information; acquiring cost constraint information and basic bidding information of the candidate delivery information; according to the cost constraint information and the traffic prediction value, correcting the basic bidding information to obtain bidding information of the candidate delivery information; and determining target delivery information from the candidate delivery information according to the bid information, and sending the target delivery information to the client.

Description

Technical Field

[0001] The present disclosure relates to technical fields such as information recommendation and advertisement bidding, and in particular to an information processing method, device, electronic device and storage medium. Background Art

[0002] With the booming development of the Internet advertising industry, the means of integrating advertising into content are becoming more and more common. In the traditional advertising delivery system, bidding is the decisive factor affecting the bidding results, which is usually fully controlled by the advertiser. However, with the advancement of online advertising systems, the real-time bidding mechanism has brought newer and higher challenges to advertisers: they not only need to deeply understand the content, quality and target audience of the materials, but also have a grasp of the dynamics of real-time traffic, making the bidding process more complicated. Summary of the invention

[0003] The present disclosure provides an information processing method, apparatus, electronic device, and storage medium.

[0004] According to one aspect of the present disclosure, there is provided an information processing method, including: receiving interaction request information sent by a client, and obtaining a traffic prediction value of the interaction request information for candidate delivery information; obtaining cost constraint information and basic bidding information of the candidate delivery information; modifying the basic bidding information according to the cost constraint information and the traffic prediction value to obtain bid information of the candidate delivery information; determining target delivery information from the candidate delivery information according to the bid information, and sending the target delivery information to the client.

[0005] According to another aspect of the present disclosure, an information processing device is provided, including: a first acquisition module, used to receive interaction request information sent by a client, and obtain a traffic prediction value of the interaction request information for candidate delivery information; a second acquisition module, used to obtain cost constraint information and basic bidding information of the candidate delivery information; a correction module, used to correct the basic bidding information according to the cost constraint information and the traffic prediction value, and obtain the bid information of the candidate delivery information; a determination module, used to determine target delivery information from the candidate delivery information according to the bid information, and send the target delivery information to the client.

[0006] According to another aspect of the present disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the information processing method described in the above-mentioned one aspect embodiment.

[0007] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, on which a computer program / instructions are stored, and the computer instructions are used to enable the computer to execute the information processing method described in the above-mentioned embodiment.

[0008] According to another aspect of the present disclosure, a computer program product is provided, including a computer program / instruction, wherein when the computer program / instruction is executed by a processor, the information processing method described in the above-mentioned embodiment is implemented.

[0009] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0011] Figure 1 A flowchart of an information processing method provided by an embodiment of the present disclosure;

[0012] Figure 2 A flowchart of another information processing method provided by an embodiment of the present disclosure;

[0013] Figure 3 A flowchart of another information processing method provided by an embodiment of the present disclosure;

[0014] Figure 4 A flowchart of another information processing method provided by an embodiment of the present disclosure;

[0015] Figure 5 A schematic diagram of the structure of the intelligent bidding system provided by the embodiment of the present disclosure;

[0016] Figure 6 A schematic diagram of the structure of an information processing device provided by an embodiment of the present disclosure;

[0017] Figure 7 The present invention is a block diagram of an electronic device for implementing the information processing method according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0018] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0019] The following describes an information processing method, an apparatus, an electronic device, and a storage medium according to embodiments of the present disclosure with reference to the accompanying drawings.

[0020] Figure 1 A flowchart of an information processing method provided by an embodiment of the present disclosure.

[0021] like Figure 1 As shown, the information processing method may include:

[0022] S101, receiving interaction request information sent by a client, and obtaining a traffic prediction value of the interaction request information for candidate delivery information.

[0023] It should be noted that the execution subject of the information processing method in the embodiment of the present disclosure may be a hardware device with data processing capabilities and / or the necessary software required to drive the hardware device to work. Optionally, the execution subject may include a server, a user terminal and other intelligent devices. Optionally, the user terminal includes but is not limited to a mobile phone, a computer, an intelligent voice interaction device, etc. Optionally, the server includes but is not limited to a network server, an application server, and may also be a server of a distributed system, or a server combined with a blockchain, etc. The embodiment of the present disclosure is not specifically limited.

[0024] In some implementations, when the client generates behavior information, it can generate interaction request information based on the behavior information and send the interaction request information to the server. That is, the server will receive the interaction request information sent by the client.

[0025] Exemplarily, the client's behavior information includes clicking a button, browsing a page, searching a keyword, etc. For example, when a user searches for information in a browser, the search behavior generates interactive request information, and the interactive request information is sent to the server.

[0026] In some implementations, candidate delivery information that attracts the user's attention can be determined based on the interaction request information, thereby generating traffic, where traffic refers to clicks, browsing, purchases, etc. That is, the traffic of the candidate delivery information can be predicted to determine the traffic prediction value, and the candidate delivery information can be bid based on the traffic prediction value to determine the target delivery information from the candidate delivery information, and deliver the target delivery information to the client.

[0027] Among them, the traffic forecast value refers to a quantitative indicator, such as the expected click-through rate, conversion rate or number of impressions.

[0028] Optionally, a traffic prediction model may be pre-trained, and material information associated with the candidate delivery information may be input into the pre-trained traffic prediction model, and the traffic prediction model may predict the traffic of the material information to obtain a traffic prediction value for the candidate delivery information.

[0029] S102, obtaining cost constraint information and basic bidding information of candidate delivery information.

[0030] In some implementations, cost constraint information of the candidate delivery information may be determined based on the delivery cost of the candidate delivery information, and basic bidding information of the candidate delivery information may be determined based on historical bidding information of the candidate delivery information.

[0031] In some implementations, an adjustment coefficient of the candidate delivery information may be calculated based on the delivery cost, and the adjustment coefficient may be used as cost constraint information of the candidate delivery information.

[0032] In some implementations, historical delivery data of the candidate delivery information is obtained, and historical bidding information of the candidate delivery information is determined from the historical delivery data. The historical bidding information is averaged to obtain historical average bidding information as basic bidding information for the candidate delivery information.

[0033] Optionally, the actual delivery cost and the target delivery cost of the candidate delivery information may be obtained, and the adjustment coefficient may be determined based on the size relationship between the actual delivery cost and the target delivery cost.

[0034] In some implementations, in order to ensure the stability of costs and the continuity of information delivery effects, a set value of an adjustment coefficient may be predetermined so that when the actual delivery cost and the target delivery cost are the same, the set value is used as the adjustment coefficient.

[0035] In some implementations, when the actual delivery cost is greater than the target delivery cost, the adjustment coefficient is less than the set value, thereby reducing the bid to save the delivery cost; when the actual delivery cost is less than the target delivery cost, the adjustment coefficient is greater than the set value, thereby increasing the bid to improve the success rate of the bidding.

[0036] S103, modifying the basic bidding information according to the cost constraint information and the traffic prediction value to obtain the bidding information of the candidate delivery information.

[0037] In some implementations, the basic bidding information can be modified using cost constraint information and traffic prediction values ​​to obtain bid information for candidate delivery information, and then information delivery can be performed based on the bid information, thereby achieving cost control and optimization, as well as traffic acquisition and conversion improvement.

[0038] In some implementations, the basic bidding information may be modified once using the traffic prediction value to obtain modified bidding information, and then the modified bidding information may be modified twice using the cost constraint information to obtain the bid information of the candidate delivery information.

[0039] Optionally, the traffic prediction value may be multiplied by the basic bidding information to achieve a primary correction to obtain the corrected bidding information, and the cost constraint information may be multiplied by the corrected bidding information to achieve a secondary correction to obtain the bid information.

[0040] S104: Determine target delivery information from candidate delivery information according to the bid information, and send the target delivery information to the client.

[0041] In some implementations, in order to make the target delivery information more targeted and thus improve the delivery efficiency of information, the candidate delivery information can be screened in combination with user information and bid information to determine the target delivery information from the candidate delivery information and deliver the target delivery information to the client.

[0042] In some implementations, a user matching prediction value between the user and the candidate delivery information may be determined based on the user information, so as to sort the bid information according to the user matching prediction value, and determine the candidate delivery information corresponding to one or more bid information with the highest ranking as the target delivery information. The sorting may be performed in descending order.

[0043] Optionally, user information may be obtained from the interaction request information, and a matching value between the user information and the candidate delivery information may be determined as a user matching prediction value.

[0044] In some implementations, the product of the user matching prediction value and the bidding information may be obtained, and the product may be sorted to determine one or more bidding information with a top ranking.

[0045] According to the information processing method provided by the embodiment of the present disclosure, the interactive request information of the client is obtained, and the traffic prediction value for the candidate delivery information is determined from the interactive request information. The cost constraint information and basic bidding information of the candidate delivery information are determined, and the basic bidding information is modified according to the traffic prediction value and the cost constraint information to obtain the bidding information of the candidate delivery information. Then, the target delivery information can be determined from the candidate delivery information according to the bidding information, and the target delivery information is delivered to the client. In the present disclosure, the bidding information is adjusted according to the traffic prediction value and the cost constraint information of the candidate delivery information, thereby optimizing the traffic structure, attracting potential users, improving the conversion efficiency of the target delivery information, and realizing the control and optimization of the delivery cost.

[0046] Figure 2 A flowchart of an information processing method provided by an embodiment of the present disclosure.

[0047] like Figure 2 As shown, the information processing method may include:

[0048] S201, receiving interaction request information sent by a client, and obtaining a traffic prediction value of the interaction request information for candidate delivery information.

[0049] S202, obtaining cost constraint information and basic bidding information of candidate delivery information.

[0050] The relevant contents of steps S201 - S202 can be found in the above embodiment and will not be described again here.

[0051] S203: Modify the basic bidding information according to the cost constraint information and the traffic prediction value to obtain the bidding information of the candidate delivery information.

[0052] In some implementations, in order to control and optimize delivery costs, as well as to acquire and improve traffic and conversion, the basic bidding information may be modified using cost constraint information and traffic prediction values ​​to obtain bid information for candidate delivery information.

[0053] In some implementations, the basic bidding information may be modified once according to the traffic prediction value to obtain modified bidding information, and the modified bidding information may be modified twice according to the cost constraint information to obtain the bid information.

[0054] Optionally, the traffic prediction value may be multiplied by the basic bidding information to achieve a primary correction to obtain the corrected bidding information, and the cost constraint information may be multiplied by the corrected bidding information to achieve a secondary correction to obtain the bid information.

[0055] S204, obtaining a user matching prediction value of the interaction request information for the candidate delivery information.

[0056] In some implementations, deep learning technology can be used in advance to build a multi-head architecture prediction model to achieve value prediction of multiple targets in one model, so that the prediction model can be used to predict the traffic prediction value and user matching prediction value of candidate delivery information, avoiding the load problem caused by multiple models in parallel and improving the prediction efficiency.

[0057] In some implementations, by obtaining user information of interactive request information and material information of candidate delivery information, and inputting the user information and the material information of the candidate delivery information into a prediction model, the prediction model outputs traffic prediction values ​​and user matching prediction values ​​for the candidate delivery information, thereby achieving the goal of obtaining traffic prediction values ​​and user matching prediction values ​​for the candidate delivery information based on the interactive request information and the material information.

[0058] S205, sorting the bidding information of the candidate delivery information according to the user matching prediction value, and determining the target delivery information from the candidate delivery information according to the sorting result of the bidding information.

[0059] In some implementations, the product of the user matching prediction value and the bidding information may be obtained, and the product may be sorted to obtain a sorting result of the bidding information, and then the target delivery information may be determined according to the sorting result.

[0060] Optionally, one or more bid information ranked high can be determined from the sorting results, and the candidate delivery information corresponding to the bid information can be used as the target delivery information. By considering the user experience in the bidding process, efficient allocation of information resources can be ensured, and the benefits of the delivery information can be maximized while improving the user experience.

[0061] S206, sending target delivery information to the client.

[0062] The relevant contents of step S206 can be found in the above embodiment and will not be described again here.

[0063] According to the information processing method provided by the embodiment of the present disclosure, in the process of determining the target delivery information, the bid information is sorted in combination with the user matching prediction value, so as to determine the target delivery information from the candidate delivery information according to the sorting result for delivery. This can improve the user experience while ensuring the efficient allocation of information resources and maximize the benefits of the delivery information.

[0064] Figure 3 A flowchart of an information processing method provided by an embodiment of the present disclosure.

[0065] like Figure 3 As shown, the information processing method may include:

[0066] S301, receiving interaction request information sent by a client, and obtaining a traffic prediction value of the interaction request information for candidate delivery information.

[0067] S302, obtaining cost constraint information and basic bidding information of candidate delivery information.

[0068] The relevant contents of steps S301 - S302 can be found in the above embodiment and will not be described again here.

[0069] S303: Obtain the target delivery cost and the actual delivery cost of the candidate delivery information.

[0070] In some implementations, the advertiser corresponding to the candidate delivery information is determined, and the delivery cost of the candidate delivery information preset by the advertiser is obtained as the target delivery cost.

[0071] In some implementations, the actual delivery cost of the candidate delivery information may be determined by monitoring the delivery of the candidate delivery information.

[0072] S304: Obtain cost constraint information according to the target delivery cost and the actual delivery cost.

[0073] In some implementations, in order to improve the efficiency of information delivery and control and optimize the delivery cost, the relationship between the target delivery cost and the actual delivery cost can be obtained, and the cost constraint information can be determined based on the relationship.

[0074] In some implementations, an adjustment coefficient of the delivery cost may be determined based on the size relationship, and the adjustment coefficient may be used as cost constraint information.

[0075] Optionally, the formula for determining the adjustment factor is as follows:

[0076]

[0077] Among them, constraint_ratio represents the adjustment coefficient, cost represents the actual delivery cost, constraint represents the target delivery cost, and a and b represent adjustable parameters. By adjusting a and b, the sensitivity of the cost constraint and the intensity of the adjustment can be controlled.

[0078] In some implementations, in response to the actual delivery cost being greater than the target delivery cost, the cost constraint information is determined to be a first adjustment coefficient that is less than a set value; in response to the actual delivery cost being greater than the target delivery cost, the cost constraint information is determined to be a second adjustment coefficient that is greater than a set value. This can ensure that high-value information can be given a higher bid, while low-value information can be bid accordingly, thereby improving the utilization efficiency of information resources.

[0079] In some implementations, in response to the actual delivery cost being equal to the target delivery cost, the cost constraint information is determined to be a third adjustment coefficient, and the third adjustment coefficient is a set value to ensure cost stability and continuity of information delivery effects.

[0080] S305: According to the candidate materials corresponding to the candidate delivery information and the advertiser identifier corresponding to the candidate delivery information.

[0081] S306: Obtain historical delivery data corresponding to the candidate delivery information according to at least one dimension information in the candidate material and the advertiser identifier.

[0082] S307, obtaining average bidding information based on historical delivery data as basic bidding information for candidate delivery information.

[0083] In some implementations, in order to ensure the accuracy and effectiveness of the bidding, the basic bidding information of the candidate delivery information may be determined based on the historical delivery data of the candidate delivery information in multiple dimensions.

[0084] In some implementations, the candidate materials carried by the candidate delivery information and the advertiser identifier of the advertiser corresponding to the candidate delivery information can be obtained, and the historical delivery data corresponding to the candidate delivery information can be obtained from at least one dimension information in the candidate materials and the advertiser identifier.

[0085] Optionally, historical delivery data corresponding to the candidate delivery information may be obtained based on the candidate material; historical delivery data corresponding to the candidate delivery information may also be obtained based on the advertiser identifier; historical delivery data corresponding to the candidate delivery information may also be obtained based on the candidate material and the advertiser identifier.

[0086] Furthermore, the historical bidding information corresponding to the candidate delivery information in the historical delivery data is determined, and the historical bidding information is averaged to obtain the average bidding information as the basic bidding information of the candidate delivery information.

[0087] S308, modifying the basic bidding information according to the cost constraint information and the traffic prediction value to obtain the bidding information of the candidate delivery information.

[0088] S309: Determine target delivery information from candidate delivery information according to the bid information, and send the target delivery information to the client.

[0089] The relevant contents of steps S308-S309 can be found in the above embodiment and will not be repeated here.

[0090] According to the information processing method provided by the embodiment of the present disclosure, by determining the target delivery cost and the actual delivery cost of the candidate delivery information, determining the cost constraint information, and determining the basic bidding information based on the historical delivery data of the candidate delivery information, it is possible to accurately control the cost of information delivery, avoid budget overspending and waste, thereby optimizing the information delivery strategy and improving delivery efficiency.

[0091] Figure 4 A flowchart of an information processing method provided by an embodiment of the present disclosure.

[0092] like Figure 4 As shown, the information processing method may include:

[0093] S401, receiving interaction request information sent by a client, and obtaining a traffic prediction value of the interaction request information for candidate delivery information.

[0094] S402, obtaining cost constraint information and basic bidding information of candidate delivery information.

[0095] S403: Modify the basic bidding information according to the cost constraint information and the traffic prediction value to obtain the bidding information of the candidate delivery information.

[0096] S404: Determine target delivery information from candidate delivery information according to the bid information, and send the target delivery information to the client.

[0097] The relevant contents of steps S401 - S404 can be found in the above embodiment and will not be described again here.

[0098] S405, monitoring the delivery status of the target delivery information and obtaining delivery data of the target delivery information.

[0099] In some implementations, after sending the target delivery information to the client, the delivery status of the target delivery information can be monitored, and the delivery data of the target delivery information can be obtained, so that the delivery effect of the delivery information, such as click-through rate, conversion rate, etc., can be understood in real time. According to the delivery data, the delivery strategy can be adjusted in time, such as adjusting the bid information of the target delivery information, so as to improve the delivery efficiency and control the delivery cost.

[0100] Optionally, the delivery data includes the consumed delivery time and consumed delivery cost of the target delivery information.

[0101] S406, obtaining order data of target delivery information.

[0102] In some implementations, the correspondence between the candidate delivery information and the order data may be queried based on the information identifier of the target delivery information, so as to determine the order data of the target delivery information from the correspondence.

[0103] That is to say, before the candidate delivery information is delivered, the target delivery time and target delivery cost of the candidate delivery information can be set as the order data corresponding to the candidate delivery information, and a corresponding relationship between the candidate delivery information and the order data can be established. Then, the order data of the target delivery information can be queried according to the information identifier of the target delivery information.

[0104] S407, dynamically adjusting the bid information of the target delivery information according to the order data and the delivery data.

[0105] In some implementations, the order data includes the target delivery time and target delivery cost of the target delivery information, and the delivery data includes the consumed delivery time and consumed delivery cost of the target delivery information. That is, the target delivery time and target delivery cost of the target delivery information can be obtained based on the order data, and the consumed delivery time and consumed delivery cost of the target delivery information can be obtained based on the delivery data.

[0106] Furthermore, the bid information of the target delivery information can be dynamically adjusted according to the target delivery time and the consumed delivery time, as well as the target delivery cost and the consumed delivery cost. Optionally, the time consumption progress and the cost consumption progress of the target delivery information can be determined according to the target delivery time and the consumed delivery time, as well as the target delivery cost and the consumed delivery cost, and the bid information of the target delivery information can be dynamically adjusted according to the size relationship between the time consumption progress and the cost consumption progress, so as to achieve better control of the cost of information delivery so that the delivery of the information reaches the delivery target.

[0107] In some implementations, the time consumption progress of the target delivery information can be obtained according to the target delivery duration and the consumed delivery duration, and the cost consumption progress of the target delivery information can be obtained according to the target delivery cost and the consumed delivery cost. Furthermore, the bid information of the target delivery information can be dynamically adjusted according to the time consumption progress and the cost consumption progress.

[0108] In some implementations, the relationship between the time consumption progress and the cost consumption progress is compared, and in response to the time consumption progress being greater than the cost consumption progress, the bid information of the target delivery information is increased to speed up budget consumption; in response to the time consumption progress being less than the cost consumption progress, the bid information of the target delivery information is reduced to avoid premature budget exhaustion.

[0109] Optionally, the formula for comparing the magnitude relationship between the time consumption progress and the cost consumption progress is as follows:

[0110]

[0111] Among them, ltr represents the time consumption progress, ldr represents the cost consumption progress, and λ represents the control parameter, which is used to adjust the consumption speed to ensure that the time consumption progress matches the cost consumption progress.

[0112] According to the information processing method provided by the embodiment of the present disclosure, after sending the target delivery information to the client, by monitoring the delivery status of the target delivery information and obtaining the delivery data of the target delivery information, the bid information of the target delivery information can be adjusted according to the delivery data, thereby improving the delivery efficiency, controlling the delivery cost, and ensuring that the delivery of the information can achieve the delivery target.

[0113] By way of example, an intelligent bidding system can be constructed based on the information processing method provided in the embodiments of the present disclosure. Figure 5 Shown is a schematic diagram of the structure of the smart bidding system. Figure 5 It includes offline part and online part.

[0114] Among them, the offline part includes a consumption database, which includes the consumption delivery time and consumption delivery cost of the target delivery information; the offline part also includes a fulfillment and over-delivery control coefficient module, which is used to dynamically adjust the bidding information of the target delivery information after the target delivery information is delivered; the offline part also includes an average bidding module, which is used to provide average bidding information as basic bidding information.

[0115] In some implementations, the relevant implementation methods of dynamically adjusting the bidding information of the target delivery information and averaging the bidding information can be referred to the above embodiments, which will not be repeated here.

[0116] Among them, the online part includes a material library, which includes material information corresponding to the candidate delivery information; the online part also includes a cost constraint module, which is used to provide cost constraint information of the candidate delivery information; the online part also includes a traffic prediction and user matching module, which is used to predict the traffic prediction value and user matching prediction value for the candidate delivery information, and can predict the traffic prediction value and user matching prediction value based on the material information and user information.

[0117] The online part also includes a bidding module, which is used to modify the basic bidding information according to the cost constraint information and the traffic prediction value, obtain the bidding information of the candidate delivery information, and determine the target delivery information from the candidate delivery information according to the bidding information and the user matching prediction value; the online part also includes a bidding success module, which is used to deliver the target delivery information.

[0118] In some implementations, the related implementation methods of determining cost constraint information of candidate delivery information, predicting traffic prediction values ​​and user matching prediction values, correcting basic bidding information, determining target delivery information, and delivering target delivery information can be referred to the above embodiments and will not be repeated here.

[0119] Corresponding to the information processing methods provided in the above-mentioned embodiments, an embodiment of the present disclosure further provides an information processing device. Since the information processing device provided in the embodiment of the present disclosure corresponds to the information processing methods provided in the above-mentioned embodiments, the implementation methods of the above-mentioned information processing methods are also applicable to the information processing device provided in the embodiment of the present disclosure and will not be described in detail in the following embodiments.

[0120] Figure 6 A schematic diagram of the structure of an information processing device provided in an embodiment of the present disclosure.

[0121] like Figure 6 As shown, the information processing device 600 of the embodiment of the present disclosure includes a first acquisition module 601 , a second acquisition module 602 , a correction module 603 and a determination module 604 .

[0122] The first acquisition module 601 is used to receive the interaction request information sent by the client, and obtain the traffic prediction value of the interaction request information for the candidate delivery information;

[0123] The second acquisition module 602 is used to acquire the cost constraint information and basic bidding information of the candidate delivery information;

[0124] A correction module 603, configured to correct the basic bidding information according to the cost constraint information and the traffic prediction value, to obtain the bidding information of the candidate delivery information;

[0125] The determination module 604 is used to determine target delivery information from the candidate delivery information according to the bidding information, and send the target delivery information to the client.

[0126] In one embodiment of the present disclosure, the determination module 604 is further used to: obtain a user matching prediction value of the interactive request information for the candidate delivery information; sort the bid information of the candidate delivery information according to the user matching prediction value, and determine the target delivery information from the candidate delivery information according to the sorting result of the bid information.

[0127] In one embodiment of the present disclosure, the first acquisition module 601 is further used to: obtain user information of the interaction request information; obtain material information of the candidate delivery information; and obtain the traffic prediction value and the user matching prediction value of the interaction request information for the candidate delivery information based on the user information and the material information.

[0128] In one embodiment of the present disclosure, the second acquisition module 602 is further used to: acquire the target delivery cost and the actual delivery cost of the candidate delivery information; and acquire the cost constraint information according to the target delivery cost and the actual delivery cost.

[0129] In one embodiment of the present disclosure, the second acquisition module 602 is further used to: acquire the size relationship between the target delivery cost and the actual delivery cost; and determine the cost constraint information according to the size relationship.

[0130] In one embodiment of the present disclosure, the second acquisition module 602 is further used to: in response to the actual delivery cost being greater than the target delivery cost, determine that the cost constraint information is a first adjustment coefficient less than a set value; in response to the actual delivery cost being greater than the target delivery cost, determine that the cost constraint information is a second adjustment coefficient greater than the set value; in response to the actual delivery cost being equal to the target delivery cost, determine that the cost constraint information is a third adjustment coefficient, and the third adjustment coefficient is the set value.

[0131] In one embodiment of the present disclosure, the second acquisition module 602 is further used to: obtain historical delivery data corresponding to the candidate delivery information based on the candidate material corresponding to the candidate delivery information and the advertiser identifier corresponding to the candidate delivery information; and obtain average bidding information based on the historical delivery data as basic bidding information for the candidate delivery information.

[0132] In one embodiment of the present disclosure, the correction module 603 is further used to: perform a primary correction on the basic bidding information according to the traffic prediction value to obtain the corrected bidding information; perform a secondary correction on the corrected bidding information according to the cost constraint information to obtain the bid information.

[0133] In one embodiment of the present disclosure, the determination module 604 is also used to: monitor the delivery status of the target delivery information and obtain the delivery data of the target delivery information; obtain the order data of the target delivery information; and dynamically adjust the bidding information of the target delivery information based on the order data and the delivery data.

[0134] In one embodiment of the present disclosure, the determination module 604 is further used to: obtain the target delivery time and target delivery cost of the target delivery information according to the order data; obtain the consumed delivery time and consumed delivery cost of the target delivery information according to the delivery data; and dynamically adjust the bidding information of the target delivery information according to the target delivery time and the consumed delivery time, as well as the target delivery cost and the consumed delivery cost.

[0135] In one embodiment of the present disclosure, the determination module 604 is also used to: obtain the time consumption progress of the target delivery information according to the target delivery duration and the consumed delivery duration; obtain the cost consumption progress of the target delivery information according to the target delivery cost and the consumed delivery cost; and dynamically adjust the bidding information of the target delivery information according to the time consumption progress and the cost consumption progress.

[0136] In one embodiment of the present disclosure, the determination module 604 is also used to: in response to the time consumption progress being greater than the cost consumption progress, increase the bid information of the target delivery information; in response to the time consumption progress being less than the cost consumption progress, reduce the bid information of the target delivery information.

[0137] According to the information processing device provided by the embodiment of the present disclosure, the interactive request information of the client is obtained, and the traffic prediction value for the candidate delivery information is determined from the interactive request information. The cost constraint information and basic bidding information of the candidate delivery information are determined, and the basic bidding information is modified according to the traffic prediction value and the cost constraint information to obtain the bidding information of the candidate delivery information. Then, the target delivery information can be determined from the candidate delivery information according to the bidding information, and the target delivery information is delivered to the client. In the present disclosure, the bidding information is adjusted according to the traffic prediction value and the cost constraint information of the candidate delivery information, so as to optimize the traffic structure, attract potential users, improve the conversion efficiency of the target delivery information, and realize the control and optimization of the delivery cost.

[0138] In the technical solution disclosed herein, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0139] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0140] Figure 7 A schematic block diagram of an example electronic device 700 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0141] like Figure 7 As shown, the device 700 includes a computing unit 701, which can perform various appropriate actions and processes according to a computer program / instruction stored in a read-only memory (ROM) 702 or a computer program / instruction loaded from a storage unit 706 to a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0142] A number of components in the device 700 are connected to the I / O interface 705, including: an input unit 706 such as a keyboard, a mouse, etc.; an output unit 707 such as various types of displays, speakers, etc.; a storage unit 708 such as a disk, an optical disk, etc.; and a communication unit 709 such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0143] The computing unit 701 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 701 performs the various methods and processes described above, such as information processing methods. For example, in some embodiments, the information processing method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 706. In some embodiments, part or all of the computer program / instructions may be loaded and / or installed on the device 700 via ROM 702 and / or communication unit 709. When the computer program / instructions are loaded into RAM 703 and executed by the computing unit 701, one or more steps of the information processing method described above may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured to perform the information processing method in any other appropriate manner (e.g., by means of firmware).

[0144] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs / instructions that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0145] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0146] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0147] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0148] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain network.

[0149] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs / instructions running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0150] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in the disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in the disclosure can be achieved, and this document does not limit them here.

[0151] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. An information processing method, wherein: The method comprises: Receive interaction request information sent by the client, and obtain a traffic prediction value of the interaction request information for candidate delivery information; Obtaining cost constraint information and basic bidding information of the candidate delivery information; According to the cost constraint information and the traffic prediction value, the basic bidding information is modified to obtain the bidding information of the candidate delivery information; According to the bidding information, target delivery information is determined from the candidate delivery information, and the target delivery information is sent to the client.

2. The method according to claim 1, wherein: The step of determining target delivery information from the candidate delivery information according to the bid information includes: Obtaining a user matching prediction value of the interaction request information for the candidate delivery information; The bidding information of the candidate delivery information is sorted according to the user matching prediction value, and the target delivery information is determined from the candidate delivery information according to the sorting result of the bidding information.

3. The method according to claim 2, wherein: The method further comprises: Obtaining user information of the interaction request information; Obtain material information of the candidate delivery information; The traffic prediction value of the interactive request information for the candidate delivery information and the user matching prediction value are obtained according to the user information and the material information.

4. The method according to claim 1, wherein: The step of obtaining the cost constraint information of the candidate delivery information includes: Obtaining a target delivery cost and an actual delivery cost of the candidate delivery information; The cost constraint information is acquired according to the target delivery cost and the actual delivery cost.

5. The method according to claim 4, wherein: The acquiring the cost constraint information according to the target delivery cost and the actual delivery cost includes: Obtaining the relationship between the target delivery cost and the actual delivery cost; The cost constraint information is determined according to the size relationship.

6. The method according to claim 5, wherein: The step of determining the cost constraint information according to the size relationship includes: In response to the actual delivery cost being greater than the target delivery cost, determining the cost constraint information to be a first adjustment coefficient that is less than a set value; In response to the actual delivery cost being greater than the target delivery cost, determining the cost constraint information to be a second adjustment coefficient greater than the set value; In response to the actual delivery cost being equal to the target delivery cost, the cost constraint information is determined to be a third adjustment coefficient, and the third adjustment coefficient is the set value.

7. The method according to any one of claims 1 to 6, wherein: Obtaining basic bidding information of the candidate delivery information includes: According to the candidate materials corresponding to the candidate delivery information and the advertiser identifier corresponding to the candidate delivery information; Acquire historical delivery data corresponding to the candidate delivery information according to at least one dimension information in the candidate material and the advertiser identifier; According to the historical delivery data, average bidding information is obtained as basic bidding information for the candidate delivery information.

8. The method according to any one of claims 1 to 6, wherein: The step of modifying the basic bidding information according to the cost constraint information and the traffic prediction value to obtain the bidding information of the candidate delivery information includes: According to the traffic prediction value, the basic bidding information is modified to obtain modified bidding information; The modified bidding information is modified a second time according to the cost constraint information to obtain the bid information.

9. The method according to any one of claims 1 to 6, wherein: After sending the target delivery information to the client, the method further includes: Monitoring the delivery status of the target delivery information and obtaining delivery data of the target delivery information; Obtaining order data of the target delivery information; The bidding information of the target delivery information is dynamically adjusted according to the order data and the delivery data.

10. The method according to claim 9, wherein: The dynamically adjusting the bid information of the target delivery information according to the order data and the delivery data includes: According to the order data, obtaining a target delivery time and a target delivery cost of the target delivery information; According to the delivery data, the delivery time and delivery cost of the target delivery information are obtained; The bid information of the target delivery information is dynamically adjusted according to the target delivery duration and the consumed delivery duration, as well as the target delivery cost and the consumed delivery cost.

11. The method according to claim 10, wherein: The dynamically adjusting the bid information of the target delivery information according to the target delivery duration and the consumed delivery duration, as well as the target delivery cost and the consumed delivery cost, includes: According to the target delivery time and the consumed delivery time, obtaining the time consumption progress of the target delivery information; According to the target delivery cost and the consumed delivery cost, obtaining the cost consumption progress of the target delivery information; The bidding information of the target delivery information is dynamically adjusted according to the time consumption progress and the cost consumption progress.

12. The method according to claim 11, wherein: The dynamically adjusting the bid information of the target delivery information according to the time consumption progress and the cost consumption progress includes: In response to the time consumption progress being greater than the cost consumption progress, increasing the bid information of the target delivery information; In response to the time consumption progress being less than the cost consumption progress, the bid information of the target delivery information is reduced.

13. An information processing device, wherein: The device comprises: A first acquisition module is used to receive the interaction request information sent by the client, and obtain the traffic prediction value of the interaction request information for the candidate delivery information; A second acquisition module is used to acquire cost constraint information and basic bidding information of the candidate delivery information; A correction module, used to correct the basic bidding information according to the cost constraint information and the traffic prediction value, to obtain the bidding information of the candidate delivery information; A determination module is used to determine target delivery information from the candidate delivery information according to the bidding information, and send the target delivery information to the client.

14. The device according to claim 13, wherein: The determining module is further used for: Obtaining a user matching prediction value of the interaction request information for the candidate delivery information; The bidding information of the candidate delivery information is sorted according to the user matching prediction value, and the target delivery information is determined from the candidate delivery information according to the sorting result of the bidding information.

15. The device according to claim 14, wherein: The first acquisition module is further used for: Obtaining user information of the interaction request information; Obtain material information of the candidate delivery information; The traffic prediction value of the interactive request information for the candidate delivery information and the user matching prediction value are obtained according to the user information and the material information.

16. The device according to claim 13, wherein: The second acquisition module is further used for: Obtaining a target delivery cost and an actual delivery cost of the candidate delivery information; The cost constraint information is acquired according to the target delivery cost and the actual delivery cost.

17. The device according to claim 16, wherein: The second acquisition module is further used for: Obtaining the relationship between the target delivery cost and the actual delivery cost; The cost constraint information is determined according to the size relationship.

18. The device according to claim 17, wherein: The second acquisition module is further used for: In response to the actual delivery cost being greater than the target delivery cost, determining the cost constraint information to be a first adjustment coefficient that is less than a set value; In response to the actual delivery cost being greater than the target delivery cost, determining the cost constraint information to be a second adjustment coefficient greater than the set value; In response to the actual delivery cost being equal to the target delivery cost, the cost constraint information is determined to be a third adjustment coefficient, and the third adjustment coefficient is the set value.

19. The device according to any one of claims 13 to 18, wherein: The second acquisition module is further used for: According to the candidate materials corresponding to the candidate delivery information and the advertiser identifier corresponding to the candidate delivery information; Acquire historical delivery data corresponding to the candidate delivery information according to at least one dimension information in the candidate material and the advertiser identifier; According to the historical delivery data, average bidding information is obtained as basic bidding information for the candidate delivery information.

20. The device according to any one of claims 13 to 18, wherein: The correction module is further used for: According to the traffic prediction value, the basic bidding information is modified to obtain modified bidding information; The modified bidding information is modified a second time according to the cost constraint information to obtain the bid information.

21. The device according to any one of claims 13 to 18, wherein: The determining module is further used for: Monitoring the delivery status of the target delivery information and obtaining delivery data of the target delivery information; Obtaining order data of the target delivery information; The bidding information of the target delivery information is dynamically adjusted according to the order data and the delivery data.

22. The device according to claim 21, wherein The determining module is further used for: According to the order data, obtaining a target delivery time and a target delivery cost of the target delivery information; According to the delivery data, the delivery time and delivery cost of the target delivery information are obtained; The bid information of the target delivery information is dynamically adjusted according to the target delivery duration and the consumed delivery duration, as well as the target delivery cost and the consumed delivery cost.

23. The device according to claim 22, wherein: The determining module is further used for: According to the target delivery time and the consumed delivery time, obtaining the time consumption progress of the target delivery information; According to the target delivery cost and the consumed delivery cost, obtaining the cost consumption progress of the target delivery information; The bidding information of the target delivery information is dynamically adjusted according to the time consumption progress and the cost consumption progress.

24. The device according to claim 23, wherein: The determining module is further used for: In response to the time consumption progress being greater than the cost consumption progress, increasing the bid information of the target delivery information; In response to the time consumption progress being less than the cost consumption progress, the bid information of the target delivery information is reduced.

25. An electronic device comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 12.

26. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-12.

27. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the method according to any one of claims 1 to 12 is implemented.

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