WO2021169550A1 - 信息处理方法及装置 - Google Patents

信息处理方法及装置 Download PDF

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Publication number
WO2021169550A1
WO2021169550A1 PCT/CN2020/140158 CN2020140158W WO2021169550A1 WO 2021169550 A1 WO2021169550 A1 WO 2021169550A1 CN 2020140158 W CN2020140158 W CN 2020140158W WO 2021169550 A1 WO2021169550 A1 WO 2021169550A1
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Prior art keywords
information
reward
users
user
levels
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PCT/CN2020/140158
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English (en)
French (fr)
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王颖帅
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北京沃东天骏信息技术有限公司
北京京东世纪贸易有限公司
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Priority to US17/766,913 priority Critical patent/US20240062237A1/en
Publication of WO2021169550A1 publication Critical patent/WO2021169550A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0207—Discounts or incentives, e.g. coupons or rebates
    • G06Q30/0239—Online discounts or incentives
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0605—Supply or demand aggregation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0207—Discounts or incentives, e.g. coupons or rebates
    • G06Q30/0211—Determining the effectiveness of discounts or incentives
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0207—Discounts or incentives, e.g. coupons or rebates
    • G06Q30/0215—Including financial accounts
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0207—Discounts or incentives, e.g. coupons or rebates
    • G06Q30/0224—Discounts or incentives, e.g. coupons or rebates based on user history
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0631—Item recommendations

Definitions

  • the embodiments of the present application relate to the field of computer technology, and in particular to an information processing method and device.
  • community group buying is playing an increasingly important role in economic activities.
  • Community group buying is a new form of online group buying. It is a way in which the group leader organizes consumers to buy goods at low prices in a virtual community.
  • community group buying provides some aggregated consumers, and on the other hand, it can realize collaboration and mutual assistance among users.
  • the related information push method is usually that the group leader determines user needs according to the user input text of the user in the group, so as to push information to the group and obtain corresponding rewards.
  • the embodiments of the present application propose an information processing method and device.
  • the embodiments of the present application provide an information processing method, including: obtaining path information in the process of sharing information of online products by users at all levels, and operating information and path information performed by users at all levels on the shared information It is used to characterize the propagation path of product information among users at all levels, sharing information is used to characterize the purchase address of online products, and users at all levels are used to characterize the users indicated by each path node in the sharing process; according to the path information And operation information to generate user characteristic information corresponding to users at all levels.
  • the user characteristic information is used to characterize the user’s contribution to the online product sharing process corresponding to the user characteristic information; combine the user characteristic information and the product characteristic information of the online product Enter the pre-trained reward calculation model to obtain reward information corresponding to users at all levels; determine the information to be pushed based on the reward information of the user.
  • the method further includes: sending the reward corresponding to the reward information to the reward calculation model.
  • the above method further includes: analyzing the change trend information of the sales volume of the online commodity after the user obtains the reward corresponding to the reward information; and adjusting the reward information output by the reward calculation model according to the change trend information.
  • the above method further includes: analyzing the change trend information of the sharing frequency of the shared information after the user obtains the reward corresponding to the reward information; and adjusting the reward information output by the reward calculation model according to the change trend information.
  • the operations indicated by the operation information include: purchasing online commodities, collecting online commodities, browsing online commodities, and inputting shopping experience information of online commodities.
  • the above method further includes: in response to determining that the operation information is the shopping experience information of the input online product, associating the online product sharing information with the shopping experience information; while displaying the shared information, displaying the shopping experience related to the shared information Experience information.
  • an embodiment of the present application provides an information processing device, including: an information acquisition unit configured to acquire path information in the process of sharing information of online products by users at all levels, and users at all levels for sharing information
  • the operation information the path information is used to characterize the spreading path of the product information among users at all levels
  • the sharing information is used to characterize the purchase address of online products
  • the users at all levels are used to characterize the location of each path node in the sharing process.
  • feature information generating unit configured to generate user feature information corresponding to users at all levels according to path information and operation information, and user feature information is used to characterize the online product sharing process of users corresponding to user feature information
  • the reward information generation unit is configured to input user characteristic information and online product characteristic information into the pre-trained reward calculation model to obtain reward information corresponding to users at all levels;
  • the push information generation unit is configured to be based on users To determine the information to be pushed.
  • the above-mentioned apparatus further includes: a sharing unit configured to send the reward corresponding to the reward information to the account of the user corresponding to the reward information; generate reward summary information according to the reward information corresponding to the users at all levels, and transfer The reward summary information is sent to the respective accounts of users at all levels.
  • a sharing unit configured to send the reward corresponding to the reward information to the account of the user corresponding to the reward information; generate reward summary information according to the reward information corresponding to the users at all levels, and transfer The reward summary information is sent to the respective accounts of users at all levels.
  • the above-mentioned apparatus further includes: a first adjustment unit configured to analyze the change trend information of the sales volume of online commodities after the user obtains the reward corresponding to the reward information; and adjust the reward calculation model according to the change trend information Output reward information.
  • the above-mentioned apparatus further includes: a second adjustment unit configured to analyze the change trend information of the number of times of sharing information after the user obtains the reward corresponding to the reward information; adjust the output of the reward calculation model according to the change trend information Reward information.
  • the operations indicated by the foregoing operation information include: purchasing online commodities, collecting online commodities, browsing online commodities, and inputting shopping experience information of online commodities.
  • the above-mentioned apparatus further includes: an associating unit configured to, in response to determining that the operation information is the shopping experience information of the input online product, associate the shared information of the online product with the shopping experience information; while displaying the shared information, Display shopping experience information associated with shared information.
  • an associating unit configured to, in response to determining that the operation information is the shopping experience information of the input online product, associate the shared information of the online product with the shopping experience information; while displaying the shared information, Display shopping experience information associated with shared information.
  • an embodiment of the present application provides a computer-readable medium on which a computer program is stored, where the program is executed by a processor to implement the method described in any implementation manner of the first aspect.
  • an embodiment of the present application provides an electronic device, including: one or more processors; a storage device, on which one or more programs are stored, when one or more programs are used by one or more processors Execution enables one or more processors to implement the method described in any implementation manner of the first aspect.
  • the information processing method and device provided in the embodiments of this application firstly obtain the path information in the process of sharing information of online products by users at all levels, and the operation information performed by users at all levels on the shared information; then, according to the path information and The operation information generates the user characteristic information corresponding to the users at all levels; finally, the user characteristic information and the product characteristic information of the online products are input into the pre-trained reward calculation model to obtain the reward information corresponding to the users at all levels.
  • This application can determine the reward information corresponding to the users at all levels based on the user characteristic information and product characteristics of the users at all levels, which will help increase the frequency of users sharing information and increase the number of shopping users; based on the reward information of users,
  • the information to be pushed can be determined, so that information can be pushed more specifically.
  • Fig. 1 is an exemplary system architecture diagram to which an embodiment of the present application can be applied;
  • Fig. 2 is a flowchart of an embodiment of the information processing method according to the present application.
  • Fig. 3 is a schematic diagram of an application scenario of the information processing method according to this embodiment.
  • Fig. 4 is a flowchart of another embodiment of the information processing method according to the present application.
  • Fig. 5 is a structural diagram of an embodiment of an information processing device according to the present application.
  • Fig. 6 is a schematic structural diagram of a computer system suitable for implementing embodiments of the present application.
  • Fig. 1 shows an exemplary architecture 100 in which the information processing method and apparatus of the present application can be applied.
  • the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105.
  • the network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105.
  • the network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, and so on.
  • the terminal devices 101, 102, 103 may be hardware devices or software that support network connection to perform data interaction and data processing.
  • the terminal devices 101, 102, 103 are hardware, they can be various electronic devices that support information interaction, network connection, image capture and other functions, including but not limited to smart phones, tablet computers, cameras, camcorders, e-book readers , Laptop portable computers and desktop computers, etc.
  • the terminal devices 101, 102, 103 are software, they can be installed in the electronic devices listed above. It can be implemented as multiple software or software modules for providing distributed services, or as a single software or software module. There is no specific limitation here.
  • the server 105 may be a server that provides various services, for example, a server that provides functions such as data analysis processing and data transmission for the terminal devices 101, 102, and 103.
  • the server can store or analyze various received data, and feed back the processing result to the terminal device.
  • the information processing methods provided by the embodiments of the present disclosure may be executed by the terminal devices 101, 102, 103, or executed by the server 105, or part of the information processing methods may be executed by the terminal devices 101, 102, 103, and The other part is executed by the server 105.
  • the information processing apparatus may be set in the terminal devices 101, 102, 103, or may be set in the server 105, and may also be partially set in the terminal devices 101, 102, 103 and the other portion is set in the server 105. There is no specific limitation here.
  • the server can be hardware or software.
  • the server can be implemented as a distributed server cluster composed of multiple servers, or as a single server.
  • the server is software, it can be implemented as multiple software or software modules for providing distributed services, or as a single software or software module. There is no specific limitation here.
  • terminal devices, networks, and servers in FIG. 1 are merely illustrative. According to implementation needs, there can be any number of terminal devices and servers.
  • a flow 200 of an embodiment of an information processing method is shown, including the following steps:
  • Step 201 Obtain path information in the process of sharing information of online products by users at all levels, and information about operations performed by users at all levels on the shared information.
  • the executive body of the information processing method (such as the terminal device or server in Figure 1) can obtain the path information in the process of sharing information of online commodities by users at all levels, and the information that users at all levels perform on the shared information. Operational information.
  • the shared information is used to characterize the purchase address of the online commodity, for example, it may be information such as a network link or a QR code corresponding to the purchase address of the online commodity. Sharing information is shared to other users through sharing operations on terminal devices by users at all levels.
  • the operations represented by the operation information may be various operations performed by users at all levels according to the shared information, including but not limited to: purchasing online products, collecting online products, browsing online products, and inputting shopping experience information of online products.
  • the user level can be determined according to the sharing order of the shared information, and any number of users can be included in the same level.
  • user A is a first-level user
  • user B is a second-level user
  • user C is a third-level user, that is, user A is a superior user of user B
  • user B is a superior user of user C.
  • user D and user E in group X also browse the shopping QR code of the TV, then user D and user E are second-level users at the same level as user B.
  • identity information that uniquely identifies the user's identity information may be added to the shared information.
  • the execution subject of this step may be a terminal device or a server.
  • the execution subject of this step may be a terminal device with an information acquisition function; otherwise, the execution subject of this step may be a server with an information acquisition function.
  • Step 202 Generate user characteristic information corresponding to users at all levels according to the path information and the operation information.
  • the execution subject can generate user characteristic information corresponding to each level of users according to the acquired path information and operation information.
  • the user characteristic information is used to characterize the user's contribution to the online commodity sharing process corresponding to the user characteristic information.
  • the operation information of the users at all levels after a certain user can be shared based on the sharing information of the user. Therefore, in the sharing order indicated by the path information In, the user’s operation information shared at all levels after the user can be used as the user’s contribution.
  • user A’s contributions include: user B, user D, and user E browse the online product, and user C purchases the online product; user B’s contribution is: User C purchases the online product.
  • the contribution of users at all levels in the online commodity sharing process can be used as the characteristic information of the user.
  • the operation information may be normalized to obtain the digitized feature information. For example, corresponding numerical values can be preset according to various operation information to obtain numerical characteristic information.
  • Step 203 Input user characteristic information and product characteristic information of online products into a pre-trained reward calculation model to obtain reward information corresponding to users at all levels.
  • the obtained user characteristic information and online commodity characteristic information are used as inputs of the pre-trained reward calculation model, and reward information corresponding to users at all levels can be obtained.
  • the reward information may be, for example, electronic red envelopes, shopping coupons, coupons, and so on.
  • the product feature information may be, for example, attribute information such as the type of online product, price information, and the like.
  • the above-mentioned reward calculation model may be a two-dimensional table that stores user characteristic information, product characteristic information of online commodities, reward information of users at all levels, and corresponding relationship information of user characteristic information, commodity characteristic information, and reward information.
  • a database it can also be a convolutional neural network trained by a machine learning algorithm (such as an extreme gradient boosting algorithm, a mini-batch gradient descent algorithm).
  • the above-mentioned reward calculation model may be obtained by training through the above-mentioned executive body or an electronic device communicatively connected with the above-mentioned executive body:
  • the training samples in the training sample set include user feature information, product feature information, and reward information.
  • the extreme gradient boosting algorithm XGBoost, eXtreme Gradient Boosting
  • the user feature information and product feature information included in the training samples in the training sample set are used as input, and the reward information corresponding to the input user feature information and product feature information As the expected output, the reward calculation model is trained.
  • user feature information and product feature information included in the training samples in the training sample set may be input to the initial model to obtain actual output data calculated by the initial model.
  • the actual output data may be the reward information actually output by the initial model.
  • the loss function in the extreme gradient boosting algorithm is used to calculate the difference between the actual output reward information and the corresponding reward information included in the training sample. If the difference value is less than or equal to the preset difference threshold, the current initial model can be used as the reward model; if the difference value is greater than the preset difference threshold, the model parameters of the current initial model can be adjusted, and the model after the parameter adjustment , Used as the initial model for the next training.
  • the initial model may be a convolutional neural network model with a network structure such as AlexNet, VGG, and ResNet.
  • this optional implementation adopts an extreme gradient boosting algorithm to train the reward calculation model, so that the reward calculation model obtained by training can generate more accurate reward information corresponding to users at all levels.
  • using the extreme gradient boosting algorithm requires fewer iterations, and multithreading can be enabled when the optimal segmentation point is selected, which greatly improves the efficiency of model iteration and calculation.
  • Step 204 Determine the information to be pushed based on the reward information of the user.
  • the executor can determine the information to be pushed based on the reward information obtained by the reward calculation model. Specifically, the information to be pushed about the online product can be determined according to the online product to which the reward represented by the reward information is applicable.
  • the reward information may be a coupon for an online product of an electrical appliance.
  • the executive body can determine that the message to be pushed is a message to be pushed about an appliance product, and then send the message to be pushed to the corresponding user.
  • FIG. 3 is a schematic diagram of an application scenario of the information processing method according to this embodiment.
  • the user A sends the sharing information 302 to the "community group buying group X" through the mobile terminal 301, where the sharing information 302 is a two-dimensional code representing the purchase address of a certain model of refrigerator.
  • the sharing information 302 is a two-dimensional code representing the purchase address of a certain model of refrigerator.
  • Five users in the "community group buying group X" browsed the shopping webpage of the refrigerator according to the instructions of the shared information 302, including user B who browsed the shopping webpage of the refrigerator through the terminal device 303.
  • the user C in the "community group buying group X" purchases the refrigerator of this model through the terminal device 304
  • the user D sends the shopping information 302 to the "community group buying group Y" through the terminal device 305, "community group buying group Y" 6 of the users browsed the shopping webpage of the refrigerator according to the instructions of the shared information 302, including user E who browsed the shopping webpage of the refrigerator through the terminal device 306.
  • the server 307 obtains the path information in the process of sharing the shared information 302 of the refrigerator by users at all levels, and the operation information performed by the users at all levels on the shared information; according to the path information and the operation information, it generates user characteristic information corresponding to the users at all levels.
  • the characteristic information of user A is: 11 browsing users and 1 purchasing user; the characteristic information of user B is: 6 browsing users.
  • the server 303 inputs the user feature information and the product feature information of the online product into the pre-trained reward calculation model to obtain the reward information corresponding to the users at all levels.
  • the reward information of user A is a 30 yuan voucher
  • the reward of user E The information is a 10 yuan voucher.
  • the server determines the information to be pushed based on the user's reward information.
  • the method provided by the above-mentioned embodiment of the present disclosure obtains the path information in the process of sharing information of online products by users at all levels, and the operation information performed by users at all levels on the shared information; then, according to the path information and operation information, Generate user characteristic information corresponding to users at all levels; finally, input user characteristic information and product characteristic information of online products into the pre-trained reward calculation model to obtain reward information corresponding to users at all levels.
  • Corresponding reward information helps to increase the frequency of users sharing information and increase the number of shopping users; based on the user’s reward information, the information to be pushed can be determined for more targeted information push.
  • the above-mentioned execution subject may also perform the following steps:
  • the reward corresponding to the reward information is sent to the account of the user corresponding to the reward information.
  • the account information of the user corresponding to the reward information can be obtained in advance, and the reward corresponding to the reward information can be sent to the account of the user corresponding to the reward information.
  • the reward summary information is generated, and the reward summary information is sent to the respective accounts of the users at all levels.
  • the executive body can share the reward summary information among users at all levels, so that users at all levels can know the characteristic information of other users and the rewards obtained, so as to encourage users to actively share information about online products and improve The sales volume of online products.
  • the above-mentioned execution subject may also perform the following steps:
  • the reward information output by the reward calculation model can be adjusted according to the change trend represented by the change trend information of the sales volume of online commodities, so that the reward information can better motivate users' desire to share and further improve online purchases.
  • the number of users of the product can be adjusted according to the change trend represented by the change trend information of the sales volume of online commodities, so that the reward information can better motivate users' desire to share and further improve online purchases. The number of users of the product.
  • the sales volume of the product has a downward trend, and the reward needs to be increased.
  • the reward weight for the browsing operation In the information about the reward for the collection operation or reduction of the reward information, the reward weight for the browsing operation.
  • the pre-trained reward calculation model is adjusted according to the change trend represented by the change trend information of the online merchandise sales volume, which improves the degree of intelligence of the application and can obtain more correct reward information.
  • the above-mentioned execution subject may also perform the following steps:
  • FIG. 4 a schematic flow 400 of another embodiment of the information processing method according to the present application is shown, including the following steps:
  • Step 401 Obtain path information in the process of sharing information of online products by users at all levels, and operation information performed by users at all levels with respect to the shared information.
  • step 401 is performed in a manner similar to step 201, and will not be repeated here.
  • Step 402 In response to the determination that the operation information indicates that the shopping experience information of the online product is input, the online product sharing information and shopping experience information are associated; and in response to displaying the sharing information, the shopping experience information associated with the sharing information is displayed.
  • the shopping experience information of the online product may be displayed in the interface displaying the shared information at the same time.
  • the shared user does not have to browse the shopping webpage of the online product, and can intuitively view the shopping experience information of the online product while viewing the shared information.
  • the user can quickly determine whether to purchase or share the shared information, thereby improving sharing Information sharing efficiency.
  • Step 403 According to the path information and the operation information, generate user characteristic information corresponding to each level of users.
  • step 403 is performed in a manner similar to step 202, and will not be repeated here.
  • Step 404 Input the user characteristic information and the product characteristic information of the online product into a pre-trained reward calculation model to obtain reward information corresponding to users at all levels.
  • step 404 is performed in a manner similar to step 203, and will not be repeated here.
  • Step 405 Determine the information to be pushed based on the reward information of the user.
  • step 405 is performed in a manner similar to step 204, and will not be repeated here.
  • the flow 400 of the information processing method in this embodiment specifically illustrates that in the process of sharing information, the interface that displays the shared information can be displayed at the same time.
  • the shopping experience information of the online product The shared user does not have to browse the shopping webpage of the online product, and can intuitively view the shopping experience information of the online product while viewing the shared information. The user can quickly determine whether to purchase or share the shared information, thereby improving sharing Information sharing efficiency.
  • the present disclosure provides an embodiment of an information processing device.
  • the device embodiment corresponds to the method embodiment shown in FIG. Used in various electronic devices.
  • the information processing device includes: an information acquisition unit 501, configured to acquire path information in the process of sharing information of online commodities by users at all levels, and information about operations performed by users at all levels on the shared information.
  • Information is used to characterize the propagation path of product information among users at all levels, sharing information is used to characterize the purchase address of online products, and users at all levels are used to characterize the users indicated by each path node in the sharing process of sharing information; feature information
  • the generating unit 502 is configured to generate user characteristic information corresponding to users at all levels according to the path information and operation information.
  • the user characteristic information is used to characterize the user's contribution to the online product sharing process corresponding to the user characteristic information; reward information
  • the generating unit 503 is configured to input user characteristic information and online product characteristic information into a pre-trained reward calculation model to obtain reward information corresponding to users at all levels; the push information generating unit 504 is configured to be based on user reward information To confirm the information to be pushed.
  • the above-mentioned apparatus further includes: a sharing unit (not shown in the figure) configured to send the reward corresponding to the reward information to the user corresponding to the reward information; and generate the reward according to the reward information corresponding to the users at all levels Summarize the information and send the reward summary information to users at all levels.
  • a sharing unit (not shown in the figure) configured to send the reward corresponding to the reward information to the user corresponding to the reward information; and generate the reward according to the reward information corresponding to the users at all levels Summarize the information and send the reward summary information to users at all levels.
  • the above-mentioned apparatus further includes: a first adjustment unit (not shown in the figure) configured to analyze the change trend information of the sales volume of online commodities after the user obtains the reward corresponding to the reward information; Trend information, adjust the reward information output by the pre-trained reward calculation model.
  • a first adjustment unit (not shown in the figure) configured to analyze the change trend information of the sales volume of online commodities after the user obtains the reward corresponding to the reward information
  • Trend information adjust the reward information output by the pre-trained reward calculation model.
  • the above-mentioned device further includes: a second adjustment unit (not shown in the figure), configured to analyze the change trend information of the number of sharing information after the user obtains the reward corresponding to the reward information; according to the change trend Information, adjust the reward information output by the pre-trained reward calculation model.
  • a second adjustment unit (not shown in the figure), configured to analyze the change trend information of the number of sharing information after the user obtains the reward corresponding to the reward information; according to the change trend Information, adjust the reward information output by the pre-trained reward calculation model.
  • the operations indicated by the foregoing operation information include: purchasing online commodities, collecting online commodities, browsing online commodities, and inputting shopping experience information of online commodities.
  • the above-mentioned apparatus further includes: an associating unit (not shown in the figure), configured to, in response to determining that the operation information is inputting shopping experience information of an online product, associate the sharing information of the online product with the shopping experience information ; While displaying the shared information, display the shopping experience information associated with the shared information.
  • an associating unit (not shown in the figure), configured to, in response to determining that the operation information is inputting shopping experience information of an online product, associate the sharing information of the online product with the shopping experience information ; While displaying the shared information, display the shopping experience information associated with the shared information.
  • the detection device can more accurately determine the reward information corresponding to the users at all levels based on the user feature information and product features of the users at all levels, which enriches the information generation methods.
  • FIG. 6 shows a schematic structural diagram of a computer system 600 suitable for implementing the devices of the embodiments of the present application (for example, the devices 101, 102, 103, 105 shown in Fig. 1).
  • the device shown in FIG. 6 is only an example, and should not bring any limitation to the function and scope of use of the embodiments of the present application.
  • the computer system 600 includes a processor (for example, a CPU, a central processing unit) 601, which can be loaded into a random access memory (RAM) according to a program stored in a read-only memory (ROM) 602 or from a storage part 608
  • the program in 603 executes various appropriate actions and processing.
  • various programs and data required for the operation of the system 600 are also stored.
  • the processor 601, the ROM602, and the RAM603 are connected to each other through a bus 604.
  • An input/output (I/O) interface 605 is also connected to the bus 604.
  • the following components are connected to the I/O interface 605: an input part 606 including a keyboard, a mouse, etc.; an output part 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and speakers, etc.; a storage part 608 including a hard disk, etc. ; And a communication section 609 including a network interface card such as a LAN card, a modem, and the like. The communication section 609 performs communication processing via a network such as the Internet.
  • the driver 610 is also connected to the I/O interface 605 as needed.
  • a removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that the computer program read from it is installed into the storage part 608 as needed.
  • an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart.
  • the computer program may be downloaded and installed from the network through the communication part 609, and/or installed from the removable medium 611.
  • the computer program executes the above-mentioned functions defined in the method of the present application.
  • the computer-readable medium of the present application may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two.
  • the computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or a combination of any of the above. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable removable Programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.
  • the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be used by or in combination with an instruction execution system, apparatus, or device.
  • a computer-readable signal medium may include a data signal propagated in a baseband or as a part of a carrier wave, and a computer-readable program code is carried therein. This propagated data signal can take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.
  • the computer-readable signal medium may also be any computer-readable medium other than the computer-readable storage medium, and the computer-readable medium may send, propagate, or transmit the program for use by or in combination with the instruction execution system, apparatus, or device .
  • the program code contained on the computer-readable medium can be transmitted by any suitable medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.
  • the computer program code used to perform the operations of the present application can be written in one or more programming languages or a combination thereof.
  • the programming languages include object-oriented programming languages—such as Java, Smalltalk, C++, and also conventional procedures.
  • the program code can be executed entirely on the client computer, partly on the client computer, executed as an independent software package, partly executed on the client computer and partly executed on a remote computer, or entirely executed on the remote computer or server.
  • the remote computer can be connected to the client computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to pass Internet connection).
  • LAN local area network
  • WAN wide area network
  • Internet service provider for example, using an Internet service provider to pass Internet connection.
  • each block in the flowchart or block diagram may represent a module, program segment, or part of code, and the module, program segment, or part of code contains one or more for realizing the specified logical function Executable instructions.
  • the functions marked in the block may also occur in a different order from the order marked in the drawings. For example, two blocks shown in succession can actually be executed substantially in parallel, or they can sometimes be executed in the reverse order, depending on the functions involved.
  • each block in the block diagram and/or flowchart, and the combination of the blocks in the block diagram and/or flowchart can be implemented by a dedicated hardware-based system that performs the specified functions or operations Or it can be realized by a combination of dedicated hardware and computer instructions.
  • the units involved in the embodiments described in the present application can be implemented in software or hardware.
  • the described unit may also be provided in the processor, for example, it may be described as: a processor including an information acquisition unit, a feature information generation unit, a reward information generation unit, and a push information generation unit.
  • the names of these units do not constitute a limitation on the unit itself under certain circumstances.
  • the reward information generating unit can also be described as "input user characteristic information and online product characteristic information into pre-trained rewards Calculate the model to obtain the unit of reward information corresponding to users at all levels.
  • the present application also provides a computer-readable medium, which may be included in the device described in the above embodiment; or it may exist alone without being assembled into the device.
  • the above-mentioned computer-readable medium carries one or more programs.
  • the computer device obtains the path information in the process of obtaining the sharing information of the online commodity and being shared by users at all levels, and Operational information of users at all levels for sharing information.
  • Path information is used to characterize the propagation path of product information among users at all levels
  • sharing information is used to characterize the purchase address of online products
  • users at all levels are used to characterize the sharing process of shared information.

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Abstract

一种信息处理方法及装置。方法包括：获取线上商品的分享信息被各级用户分享过程中的路径信息，以及各级用户针对分享信息进行的操作信息（201）；根据路径信息和操作信息，生成各级用户各自对应的用户特征信息（202）；将用户特征信息、线上商品的商品特征信息输入预先训练的奖励计算模型，得到各级用户对应的奖励信息（203）；基于用户的奖励信息，确定待推送信息（204）。根据各级用户的用户特征信息和商品特征，可以确定出与各级用户对应的奖励信息，有助于提高用户关于分享信息的分享频次，增加购物用户的数量，更具针对性地进行信息推送。

Description

信息处理方法及装置
本专利申请要求于2020年2月28日提交的、申请号为202010129833.3、申请人为北京沃东天骏信息技术有限公司及北京京东世纪贸易有限公司、发明名称为“信息处理方法及装置”的中国专利申请的优先权，该申请的全文以引用的方式并入本申请中。
技术领域
本申请实施例涉及计算机技术领域，具体涉及一种信息处理方法及装置。
背景技术
随着大数据和互联网的发展，社区团购在经济活动中扮演着越来越重要的角色。社区团购是网络团购的一种新形态，是一种在虚拟社区中团长组织消费者以低价购买商品的方式。社区团购一方面提供了一些聚合的消费者，另一方面可以实现用户之间的协同互助。在社区团购场景中，相关的信息推送方式通常是由团长根据用户在群组中的用户输入文本确定用户需求，从而向群组进行信息推送，获得相应的奖励。
发明内容
本申请实施例提出了一种信息处理方法及装置。
第一方面，本申请实施例提供了一种信息处理方法，包括：获取线上商品的分享信息被各级用户分享过程中的路径信息，以及各级用户针对分享信息进行的操作信息，路径信息用于表征商品信息在各级用户间的传播路径，分享信息用于表征线上商品的购买地址，各级用户用于表征分享信息在分享过程中的各路径节点所指示的用户；根据路径信息和操作信息，生成各级用户各自对应的用户特征信息，用户特征信息用于表征与用户特征信息对应的用户在线上商品的分享过程中的贡献；将用户特征信息、线上商品的商品特征信息输入预先训练 的奖励计算模型，得到各级用户对应的奖励信息；基于用户的奖励信息，确定待推送信息。
在一些实施例中，在将用户特征信息、线上商品的商品特征信息输入预先训练的奖励计算模型，得到各级用户对应的奖励信息之后，还包括：将奖励信息对应的奖励发送至与奖励信息对应的用户的账号；根据各级用户对应的奖励信息，生成奖励汇总信息，以及将奖励汇总信息发送至各级用户各自对应的账号。
在一些实施例中，上述方法还包括：分析用户获取奖励信息对应的奖励后的、线上商品的销售量的变化趋势信息；根据变化趋势信息，调整奖励计算模型输出的奖励信息。
在一些实施例中，上述方法还包括：分析用户获取奖励信息对应的奖励后，针对分享信息的分享次数的变化趋势信息；根据变化趋势信息，调整奖励计算模型输出的奖励信息。
在一些实施例中，操作信息指示的操作包括：购买线上商品、收藏线上商品、浏览线上商品、输入线上商品的购物体验信息。
在一些实施例中，上述方法还包括：响应于确定操作信息为输入线上商品的购物体验信息，关联线上商品的分享信息和购物体验信息；显示分享信息的同时，显示关联分享信息的购物体验信息。
第二方面，本申请实施例提供了一种信息处理装置，包括：信息获取单元，被配置成获取线上商品的分享信息被各级用户分享过程中的路径信息，以及各级用户针对分享信息进行的操作信息，路径信息用于表征商品信息在各级用户间的传播路径，分享信息用于表征线上商品的购买地址，各级用户用于表征分享信息在分享过程中的各路径节点所指示的用户；特征信息生成单元，被配置成根据路径信息和操作信息，生成各级用户各自对应的用户特征信息，用户特征信息用于表征与用户特征信息对应的用户在线上商品的分享过程中的贡献；奖励信息生成单元，被配置成将用户特征信息、线上商品的商品特征信息输入预先训练的奖励计算模型，得到各级用户对应的奖励信息；推送信息生成单元，被配置成基于用户的奖励信息，确定待推送信息。
在一些实施例中，上述装置还包括：分享单元，被配置成将奖励 信息对应的奖励发送至与奖励信息对应的用户的账号；根据各级用户对应的奖励信息，生成奖励汇总信息，以及将奖励汇总信息发送至各级用户各自对应的账号。
在一些实施例中，上述装置还包括：第一调整单元，被配置成分析用户获取奖励信息对应的奖励后的、线上商品的销售量的变化趋势信息；根据变化趋势信息，调整奖励计算模型输出的奖励信息。
在一些实施例中，上述装置还包括：第二调整单元，被配置成分析用户获取奖励信息对应的奖励后，针对分享信息的分享次数的变化趋势信息；根据变化趋势信息，调整奖励计算模型输出的奖励信息。
在一些实施例中，上述操作信息指示的操作包括：购买线上商品、收藏线上商品、浏览线上商品、输入线上商品的购物体验信息。
在一些实施例中，上述装置还包括：关联单元，被配置成响应于确定操作信息为输入线上商品的购物体验信息，关联线上商品的分享信息和购物体验信息；显示分享信息的同时，显示关联分享信息的购物体验信息。
第三方面，本申请实施例提供了一种计算机可读介质，其上存储有计算机程序，其中，程序被处理器执行时实现如第一方面任一实现方式描述的方法。
第四方面，本申请实施例提供了一种电子设备，包括：一个或多个处理器；存储装置，其上存储有一个或多个程序，当一个或多个程序被一个或多个处理器执行，使得一个或多个处理器实现如第一方面任一实现方式描述的方法。
本申请实施例提供的信息处理方法及装置，首先，获取线上商品的分享信息被各级用户分享过程中的路径信息，以及各级用户针对分享信息进行的操作信息；然后，根据路径信息和操作信息，生成各级用户各自对应的用户特征信息；最后，将用户特征信息、线上商品的商品特征信息输入预先训练的奖励计算模型，得到各级用户对应的奖励信息。本申请根据各级用户的用户特征信息和商品特征，可以确定出与各级用户对应的奖励信息，有助于提高用户关于分享信息的分享频次，增加购物用户的数量；基于用户的奖励信息，可以确定待推送 信息，以更具针对性地进行信息推送。
附图说明
通过阅读参照以下附图所作的对非限制性实施例所作的详细描述，本申请的其它特征、目的和优点将会变得更明显：
图1是本申请的一个实施例可以应用于其中的示例性系统架构图；
图2是根据本申请的信息处理方法的一个实施例的流程图；
图3是根据本实施例的信息处理方法的应用场景的示意图；
图4是根据本申请的信息处理方法的又一个实施例的流程图；
图5是根据本申请的信息处理装置的一个实施例的结构图；
图6是适于用来实现本申请实施例的计算机系统的结构示意图。
具体实施方式
下面结合附图和实施例对本申请作进一步的详细说明。可以理解的是，此处所描述的具体实施例仅仅用于解释相关发明，而非对该发明的限定。另外还需要说明的是，为了便于描述，附图中仅示出了与有关发明相关的部分。
需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。下面将参考附图并结合实施例来详细说明本申请。
图1示出了可以应用本申请的信息处理方法及装置的示例性架构100。
如图1所示，系统架构100可以包括终端设备101、102、103，网络104和服务器105。网络104用以在终端设备101、102、103和服务器105之间提供通信链路的介质。网络104可以包括各种连接类型，例如有线、无线通信链路或者光纤电缆等等。
终端设备101、102、103可以是支持网络连接从而进行数据交互和数据处理的硬件设备或软件。当终端设备101、102、103为硬件时，其可以是支持信息交互、网络连接、图像拍摄等功能的各种电子设备，包括但不限于智能手机、平板电脑、相机、摄像机、电子书阅读器、 膝上型便携计算机和台式计算机等等。当终端设备101、102、103为软件时，可以安装在上述所列举的电子设备中。其可以实现成例如用来提供分布式服务的多个软件或软件模块，也可以实现成单个软件或软件模块。在此不做具体限定。
服务器105可以是提供各种服务的服务器，例如对终端设备101、102、103提供数据分析处理、数据传输等功能的服务器。服务器可以对接收到的各种数据进行存储或分析，并将处理结果反馈给终端设备。
需要说明的是，本公开的实施例所提供的信息处理方法可以由终端设备101、102、103执行，也可以由服务器105执行，或者，也可以一部分由终端设备101、102、103执行，而另一部分由服务器105执行。相应地，信息处理装置可以设置于终端设备101、102、103中，也可以设置于服务器105中，还可以一部分设置于终端设备101、102、103中而另一部分设置于服务器105中。在此不做具体限定。
需要说明的是，服务器可以是硬件，也可以是软件。当服务器为硬件时，可以实现成多个服务器组成的分布式服务器集群，也可以实现成单个服务器。当服务器为软件时，可以实现成例如用来提供分布式服务的多个软件或软件模块，也可以实现成单个软件或软件模块。在此不做具体限定。
应该理解，图1中的终端设备、网络和服务器的数目仅仅是示意性的。根据实现需要，可以具有任意数目的终端设备和服务器。
继续参考图2，示出了信息处理方法的一个实施例的流程200，包括以下步骤：
步骤201，获取线上商品的分享信息被各级用户分享过程中的路径信息，以及各级用户针对分享信息进行的操作信息。
本实施例中，信息处理方法的执行主体(例如图1中的终端设备或服务器)可以获取线上商品的分享信息被各级用户分享过程中的路径信息，以及各级用户针对分享信息进行的操作信息。
分享信息用于表征线上商品的购买地址，例如可以是该线上商品的购买地址对应的网络链接、二维码等信息。分享信息通过各级用户在终端设备上的分享操作分享至其他的用户。
各级用户用于表征分享信息在分享过程中的各路径节点所指示的用户，路径信息用于表征商品信息在各级用户间的传播路径。操作信息所表征的操作可以是各级用户根据分享信息进行的各种操作，包括但不限于：购买线上商品、收藏线上商品、浏览线上商品、输入线上商品的购物体验信息。
作为示例，假如用户A将某型号的电视机这一线上商品的购物二维码通过智能手机分享至一即时通讯应用的群组X中，该群组X中的用户B浏览了购物二维码所指示的电视机，并将电视机的购物二维码信息分享至一即时通讯应用的另一群组Y中，该群组Y中的用户C根据购物二维码信息购买了该型号的一台电视机。则关于该型号的电视机的传播路径为“用户A—>用户B—>用户C”，各级用户中的各个用户分别为用户A、用户B、用户C，对应于用户A的操作信息为分享该线上商品，对应于用户B的操作信息为浏览和分享该线上商品，对应于用户C的操作信息为购买该线上商品。
本实施例中，由分享该分享信息的初始用户开始，根据分享信息的分享顺序可以确定用户的等级，同一等级中可以包括任意个数的用户。继续参考上述示例，用户A为一级用户，用户B为二级用户，用户C为三级用户，也即，用户A为用户B的上级用户，用户B为用户C的上级用户。若群组X中的用户D、用户E也浏览了电视机的购物二维码，则用户D、用户E是与用户B同级的二级用户。
本实施例中，在分享信息被用户分享时，可以在分享信息中加入唯一标识该用户身份信息的身份标识信息。
需要说明的是，本步骤的执行主体可以是终端设备，也可以是服务器。当终端设备具有信息获取功能时，本步骤的执行主体则可以是具有信息获取功能的终端设备；否则，本步骤的执行主体则可以是具有信息获取功能的服务器。
步骤202，根据路径信息和操作信息，生成各级用户各自对应的用户特征信息。
本实施例中，执行主体根据获取的路径信息和操作信息，可以生成各级用户各自对应的用户特征信息。
用户特征信息用于表征与该用户特征信息对应的用户在线上商品的分享过程中的贡献。
在本实施例中，由于在路径信息所指示的分享顺序中，某一用户后的各级分享用户的操作信息是基于该用户的分享信息才得以进行，因此，在路径信息所指示的分享顺序中，该用户后的各级分享用户的操作信息可以作为该用户的贡献。
继续参考上述示例，关于该型号的电视机的分享过程中，用户A的贡献包括：用户B、用户D、用户E浏览该线上商品，用户C购买该线上商品；用户B的贡献为：用户C购买该线上商品。
本实施例中，可以将各级用户在线上商品的分享过程中的贡献作为该用户的特征信息。在一些可选的实现方式中，可以根据将操作信息归一化，得到数值化后的特征信息。例如，可以根据各种操作信息，预先设置对应的数值，以得到数值化后的特征信息。
步骤203，将用户特征信息、线上商品的商品特征信息输入预先训练的奖励计算模型，得到各级用户对应的奖励信息。
本实施例中，将得到的用户特征信息、线上商品的商品特征信息作为预先训练的奖励计算模型的输入，可以得到各级用户对应的奖励信息。奖励信息例如可以是电子红包、购物券、优惠券等。商品特征信息例如可以是线上商品的种类等属性信息、价格信息等。
在这里，上述奖励计算模型可以是关联存储有用户特征信息、线上商品的商品特征信息、各级用户的奖励信息，以及用户特征信息、商品特征信息和奖励信息的对应关系信息的二维表或数据库；也可以是采用机器学习算法(例如极端梯度提升算法、小批量梯度下降算法)训练得到的卷积神经网络。
在一些可选的实现方式中，上述奖励计算模型可以经由上述执行主体或者与上述执行主体通信连接的电子设备，通过如下步骤训练得到：
首先，获取训练样本集。其中，训练样本集中的训练样本包括用户特征信息、商品特征信息和奖励信息。然后，采用极端梯度提升算法(XGBoost，eXtreme Gradient Boosting)，将训练样本集中的训练样 本包括的用户特征信息、商品特征信息作为输入，将与输入的用户特征信息、商品特征信息相对应的奖励信息作为期望输出，训练得到奖励计算模型。
示例性的，可以将训练样本集中的训练样本包括的用户特征信息、商品特征信息输入至初始模型，获得初始模型计算得到的实际输出数据。其中，实际输出数据可以是初始模型实际输出的奖励信息。然后，再用极端梯度提升算法中的损失函数，计算实际输出的奖励信息与训练样本中包括的相应的奖励信息之间的差异值。若差异值小于或等于预设差异阈值，则可以将当前的初始模型作为奖励模型；若差异值大于上述预设差异阈值，则可以调整当前的初始模型的模型参数，以及将参数调整后的模型，用作下次训练的初始模型。
其中，初始模型可以是具有AlexNet、VGG、ResNet等网络结构的卷积神经网络模型。
可以理解，相对于现有技术而言，本可选的实现方式采用极端梯度提升算法来训练奖励计算模型，可以使得训练得到的奖励计算模型生成更准确的、对应于各级用户的奖励信息，并且，在达到相同的训练效果的情况下，采用极端梯度提升算法所需要的迭代次数更少，在选取最佳切分点时可以开启多线程进行，大大提高了模型迭代和计算的效率。
步骤204，基于用户的奖励信息，确定待推送信息。
本实施例中，执行主体根据奖励计算模型得到的奖励信息，可以确定待推送信息。具体的，可以根据奖励信息所表征的奖励所适用的线上商品，确定关于线上商品的待推送信息。
作为示例，奖励信息可以是电器类在线商品的优惠券，根据该优惠券，执行主体可以确定待推送消息为关于电器类商品的待推送消息，然后将待推送消息发送至对应的用户。
继续参见图3，图3是根据本实施例的信息处理方法的应用场景的一个示意图。在图3的应用场景中，用户A通过移动终端301将分享信息302发送至“社区团购群X”中，其中，分享信息302为表征某一型号的电冰箱的购买地址的二维码。“社区团购群X”中的5个用 户根据分享信息302的指示浏览了电冰箱的购物网页，其中包括通过终端设备303浏览了电冰箱的购物网页的用户B。而且，“社区团购群X”中的用户C通过终端设备304购买了该型号的电冰箱，用户D通过终端设备305将购物信息302发送至“社区团购群Y”中，“社区团购群Y”中的6个用户根据分享信息302的指示浏览了电冰箱的购物网页，其中，包括通过终端设备306浏览了电冰箱的购物网页的用户E。服务器307获取电冰箱的分享信息302被各级用户分享过程中的路径信息，以及各级用户针对分享信息进行的操作信息；根据路径信息和操作信息，生成各级用户各自对应的用户特征信息。其中，用户A的特征信息为：11个浏览用户，1个购买用户；用户B的特征信息为：6个浏览用户。然后，服务器303将用户特征信息、线上商品的商品特征信息输入预先训练的奖励计算模型，得到各级用户对应的奖励信息，例如，用户A的奖励信息为30元代金券，用户E的奖励信息为10元的代金券。最后，服务器基于用户的奖励信息，确定待推送信息。
本公开的上述实施例提供的方法，通过获取线上商品的分享信息被各级用户分享过程中的路径信息，以及各级用户针对分享信息进行的操作信息；然后，根据路径信息和操作信息，生成各级用户各自对应的用户特征信息；最后，将用户特征信息、线上商品的商品特征信息输入预先训练的奖励计算模型，得到各级用户对应的奖励信息，可以确定出与各级用户各自对应的奖励信息，有助于提高用户关于分享信息的分享频次，增加购物用户的数量；基于用户的奖励信息，可以确定待推送信息，以更具针对性地进行信息推送。
在本实施例的一些可选的实现方式中，上述执行主体还可以执行如下步骤：
首先，将奖励信息对应的奖励发送至与奖励信息对应的用户的账号。
本实现方式中，可以预先获取奖励信息对应的用户的账号信息，并将奖励信息对应的奖励发送至与奖励信息对应的用户的账号中。
然后，根据各级用户对应的奖励信息，生成奖励汇总信息，以及将奖励汇总信息发送至各级用户各自对应的账号。
本实施例中，执行主体可以将奖励汇总信息在各级用户之间共享，使得各级用户可以知晓其他用户的特征信息和所得的奖励，以激励用户积极分享关于线上商品的分享信息，提高线上商品的销售量。
在本实施例的一些可选的实现方式中，上述执行主体还可以执行如下步骤：
首先，分析用户获取奖励信息对应的奖励后的、线上商品的销售量的变化趋势信息；然后，根据变化趋势信息，调整预先训练的奖励计算模型输出的奖励信息。
本实现方式中，根据线上商品的销售量的变化趋势信息所表征的变化趋势可以调整奖励计算模型输出的奖励信息，以使得奖励信息可以更好的激励用户的分享欲望，进一步提高购买线上商品的用户数量。
例如，针对用户的特征信息，当提高某商品对应的奖励信息中，关于浏览操作的奖励权重，降低奖励信息中关于收藏操作的奖励时，该商品的销售量有下降的趋势，则需要提高奖励信息中关于收藏操作的奖励或降低奖励信息中，关于浏览操作的奖励权重。
本实施例中，根据线上商品的销售量的变化趋势信息所表征的变化趋势调整预先训练的奖励计算模型，提高了本申请的智能化程度，可以得到更正确的奖励信息。
在本实施例的一些可选的实现方式中，上述执行主体还可以执行如下步骤：
首先，分析用户获取奖励信息对应的奖励后，针对分享信息的分享次数的变化趋势信息；然后，根据变化趋势信息，调整预先训练的奖励计算模型输出的奖励信息。
继续参考图4，示出了根据本申请的信息处理方法的另一个实施例的示意性流程400，包括以下步骤：
步骤401，获取线上商品的分享信息被各级用户分享过程中的路径信息，以及各级用户针对分享信息进行的操作信息。
本实施例中，步骤401按照与步骤201类似的方式执行，在此不再赘述。
步骤402，响应于确定操作信息指示输入所述线上商品的购物体 验信息，关联线上商品的分享信息和购物体验信息；以及响应于显示分享信息，显示关联分享信息的购物体验信息。
本实施例中，在分享信息的分享过程中，在显示分享信息的界面中可以同时显示该线上商品的购物体验信息。被分享的用户不必浏览线上商品的购物网页，在查看分享信息的同时就可以直观的观看该线上商品的购物体验信息，用户可以快速地确定是否购买或分享该分享信息，从而可以提高分享信息的分享效率。
步骤403，根据路径信息和操作信息，生成各级用户各自对应的用户特征信息。
本实施例中，步骤403按照与步骤202类似的方式执行，在此不再赘述。
步骤404，将用户特征信息、线上商品的商品特征信息输入预先训练的奖励计算模型，得到各级用户对应的奖励信息。
本实施例中，步骤404按照与步骤203类似的方式执行，在此不再赘述。
步骤405，基于用户的奖励信息，确定待推送信息。
本实施例中，步骤405按照与步骤204类似的方式执行，在此不再赘述。
从本实施例中可以看出，与图2对应的实施例相比，本实施例中的信息处理方法的流程400具体说明了在分享信息的分享过程中，显示分享信息的界面中可以同时显示该线上商品的购物体验信息。被分享的用户不必浏览线上商品的购物网页，在查看分享信息的同时就可以直观的观看该线上商品的购物体验信息，用户可以快速地确定是否购买或分享该分享信息，从而可以提高分享信息的分享效率。
继续参考图5，作为对上述各图所示方法的实现，本公开提供了一种信息处理装置的一个实施例，该装置实施例与图2所示的方法实施例相对应，该装置具体可以应用于各种电子设备中。
如图5所示，信息处理装置包括：信息获取单元501，被配置成获取线上商品的分享信息被各级用户分享过程中的路径信息，以及各级用户针对分享信息进行的操作信息，路径信息用于表征商品信息在各 级用户间的传播路径，分享信息用于表征线上商品的购买地址，各级用户用于表征分享信息在分享过程中的各路径节点所指示的用户；特征信息生成单元502，被配置成根据路径信息和操作信息，生成各级用户各自对应的用户特征信息，用户特征信息用于表征与用户特征信息对应的用户在线上商品的分享过程中的贡献；奖励信息生成单元503，被配置成将用户特征信息、线上商品的商品特征信息输入预先训练的奖励计算模型，得到各级用户对应的奖励信息；推送信息生成单元504，被配置成基于用户的奖励信息，确定待推送信息。
在一些实施例中，上述装置还包括：分享单元(图中未示出)，被配置成将奖励信息对应的奖励发送至与奖励信息对应的用户；根据各级用户对应的奖励信息，生成奖励汇总信息，并将奖励汇总信息发送至各级用户。
在一些实施例中，上述装置还包括：第一调整单元(图中未示出)，被配置成分析用户获取奖励信息对应的奖励后的、线上商品的销售量的变化趋势信息；根据变化趋势信息，调整预先训练的奖励计算模型输出的奖励信息。
在一些实施例中，上述装置还包括：第二调整单元(图中未示出)，被配置成分析用户获取奖励信息对应的奖励后，针对分享信息的分享次数的变化趋势信息；根据变化趋势信息，调整预先训练的奖励计算模型输出的奖励信息。
在一些实施例中，上述操作信息指示的操作包括：购买线上商品、收藏线上商品、浏览线上商品、输入线上商品的购物体验信息。
在一些实施例中，上述装置还包括：关联单元(图中未示出)，被配置成响应于确定操作信息为输入线上商品的购物体验信息，关联线上商品的分享信息和购物体验信息；显示分享信息的同时，显示关联分享信息的购物体验信息。
本实施例中，检测装置根据各级用户的用户特征信息和商品特征，可以更准确地确定出与各级用户对应的奖励信息，丰富了信息的生成方式。
下面参考图6，其示出了适于用来实现本申请实施例的设备(例如 图1所示的设备101、102、103、105)的计算机系统600的结构示意图。图6示出的设备仅仅是一个示例，不应对本申请实施例的功能和使用范围带来任何限制。
如图6所示，计算机系统600包括处理器(例如CPU，中央处理器)601，其可以根据存储在只读存储器(ROM)602中的程序或者从存储部分608加载到随机访问存储器(RAM)603中的程序而执行各种适当的动作和处理。在RAM603中，还存储有系统600操作所需的各种程序和数据。处理器601、ROM602以及RAM603通过总线604彼此相连。输入/输出(I/O)接口605也连接至总线604。
以下部件连接至I/O接口605：包括键盘、鼠标等的输入部分606；包括诸如阴极射线管(CRT)、液晶显示器(LCD)等以及扬声器等的输出部分607；包括硬盘等的存储部分608；以及包括诸如LAN卡、调制解调器等的网络接口卡的通信部分609。通信部分609经由诸如因特网的网络执行通信处理。驱动器610也根据需要连接至I/O接口605。可拆卸介质611，诸如磁盘、光盘、磁光盘、半导体存储器等等，根据需要安装在驱动器610上，以便于从其上读出的计算机程序根据需要被安装入存储部分608。
特别地，根据本公开的实施例，上文参考流程图描述的过程可以被实现为计算机软件程序。例如，本公开的实施例包括一种计算机程序产品，其包括承载在计算机可读介质上的计算机程序，该计算机程序包含用于执行流程图所示的方法的程序代码。在这样的实施例中，该计算机程序可以通过通信部分609从网络上被下载和安装，和/或从可拆卸介质611被安装。在该计算机程序被处理器601执行时，执行本申请的方法中限定的上述功能。
需要说明的是，本申请的计算机可读介质可以是计算机可读信号介质或者计算机可读存储介质或者是上述两者的任意组合。计算机可读存储介质例如可以是——但不限于——电、磁、光、电磁、红外线、或半导体的系统、装置或器件，或者任意以上的组合。计算机可读存储介质的更具体的例子可以包括但不限于：具有一个或多个导线的电连接、便携式计算机磁盘、硬盘、随机访问存储器(RAM)、只读存储 器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、光纤、便携式紧凑磁盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本申请中，计算机可读存储介质可以是任何包含或存储程序的有形介质，该程序可以被指令执行系统、装置或者器件使用或者与其结合使用。而在本申请中，计算机可读的信号介质可以包括在基带中或者作为载波一部分传播的数据信号，其中承载了计算机可读的程序代码。这种传播的数据信号可以采用多种形式，包括但不限于电磁信号、光信号或上述的任意合适的组合。计算机可读的信号介质还可以是计算机可读存储介质以外的任何计算机可读介质，该计算机可读介质可以发送、传播或者传输用于由指令执行系统、装置或者器件使用或者与其结合使用的程序。计算机可读介质上包含的程序代码可以用任何适当的介质传输，包括但不限于：无线、电线、光缆、RF等等，或者上述的任意合适的组合。
可以以一种或多种程序设计语言或其组合来编写用于执行本申请的操作的计算机程序代码，程序设计语言包括面向目标的程序设计语言—诸如Java、Smalltalk、C++，还包括常规的过程式程序设计语言—诸如”C”语言或类似的程序设计语言。程序代码可以完全地在客户计算机上执行、部分地在客户计算机上执行、作为一个独立的软件包执行、部分在客户计算机上部分在远程计算机上执行、或者完全在远程计算机或服务器上执行。在涉及远程计算机的情形中，远程计算机可以通过任意种类的网络——包括局域网(LAN)或广域网(WAN)—连接到客户计算机，或者，可以连接到外部计算机(例如利用因特网服务提供商来通过因特网连接)。
附图中的流程图和框图，图示了按照本申请各种实施例的装置、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段、或代码的一部分，该模块、程序段、或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个接连地表示的方框实际上可以基本并行地执行，它们有时 也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图和/或流程图中的每个方框、以及框图和/或流程图中的方框的组合，可以用执行规定的功能或操作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。
描述于本申请实施例中所涉及到的单元可以通过软件的方式实现，也可以通过硬件的方式来实现。所描述的单元也可以设置在处理器中，例如，可以描述为：一种处理器，包括信息获取单元、特征信息生成单元、奖励信息生成单元和推送信息生成单元。其中，这些单元的名称在某种情况下并不构成对该单元本身的限定，例如，奖励信息生成单元还可以被描述为“将用户特征信息、线上商品的商品特征信息输入预先训练的奖励计算模型，得到各级用户对应的奖励信息”的单元。
作为另一方面，本申请还提供了一种计算机可读介质，该计算机可读介质可以是上述实施例中描述的设备中所包含的；也可以是单独存在，而未装配入该设备中。上述计算机可读介质承载有一个或者多个程序，当上述一个或者多个程序被该装置执行时，使得该计算机设备：获取线上商品的分享信息被各级用户分享过程中的路径信息，以及各级用户针对分享信息进行的操作信息，路径信息用于表征商品信息在各级用户间的传播路径，分享信息用于表征线上商品的购买地址，各级用户用于表征分享信息在分享过程中的各路径节点所指示的用户；根据路径信息和操作信息，生成各级用户各自对应的用户特征信息，用户特征信息用于表征与用户特征信息对应的用户在线上商品的分享过程中的贡献；将用户特征信息、线上商品的商品特征信息输入预先训练的奖励计算模型，得到各级用户对应的奖励信息；基于用户的奖励信息，确定待推送信息。
以上描述仅为本申请的较佳实施例以及对所运用技术原理的说明。本领域技术人员应当理解，本申请中所涉及的发明范围，并不限于上述技术特征的特定组合而成的技术方案，同时也应涵盖在不脱离上述发明构思的情况下，由上述技术特征或其等同特征进行任意组合而形成的其它技术方案。例如上述特征与本申请中公开的(但不限于)具有类似功能的技术特征进行互相替换而形成的技术方案。

Claims (14)

  1. 一种信息处理方法，包括：
    获取线上商品的分享信息被各级用户分享过程中的路径信息，以及各级用户针对所述分享信息进行的操作信息，所述路径信息用于表征所述商品信息在各级用户间的传播路径，所述分享信息用于表征所述线上商品的购买地址，所述各级用户用于表征所述分享信息在分享过程中的各路径节点所指示的用户；
    根据所述路径信息和所述操作信息，生成各级用户各自对应的用户特征信息，所述用户特征信息用于表征与所述用户特征信息对应的用户在所述线上商品的分享过程中的贡献；
    将所述用户特征信息、所述线上商品的商品特征信息输入预先训练的奖励计算模型，得到各级用户对应的奖励信息；
    基于用户的所述奖励信息，确定待推送信息。
  2. 根据权利要求1所述的方法，其中，在所述将所述用户特征信息、所述线上商品的商品特征信息输入预先训练的奖励计算模型，得到各级用户对应的奖励信息之后，所述方法还包括：
    将所述奖励信息对应的奖励发送至与所述奖励信息对应的用户的账号；
    根据各级用户对应的奖励信息，生成奖励汇总信息，以及将所述奖励汇总信息发送至所述各级用户各自对应的账号。
  3. 根据权利要求1所述的方法，其中，所述方法还包括：
    分析用户获取所述奖励信息对应的奖励后的、所述线上商品的销售量的变化趋势信息；
    根据所述变化趋势信息，调整所述奖励计算模型输出的奖励信息。
  4. 根据权利要求1所述的方法，其中，所述方法还包括：
    分析用户获取所述奖励信息对应的奖励后，针对分享信息的分享 次数的变化趋势信息；
    根据所述变化趋势信息，调整所述奖励计算模型输出的奖励信息。
  5. 根据权利要求1-4任一所述的方法，其中，所述操作信息指示的操作包括：购买所述线上商品、收藏所述线上商品、浏览所述线上商品、输入所述线上商品的购物体验信息。
  6. 根据权利要求5所述的方法，其中，所述方法还包括：
    响应于确定所述操作信息指示输入所述线上商品的购物体验信息，关联所述线上商品的分享信息和所述购物体验信息；
    响应于显示所述分享信息，显示关联所述分享信息的所述购物体验信息。
  7. 一种信息处理装置，包括：
    信息获取单元，被配置成获取线上商品的分享信息被各级用户分享过程中的路径信息，以及各级用户针对所述分享信息进行的操作信息，所述路径信息用于表征所述商品信息在各级用户间的传播路径，所述分享信息用于表征所述线上商品的购买地址，所述各级用户用于表征所述分享信息在分享过程中的各路径节点所指示的用户；
    特征信息生成单元，被配置成根据所述路径信息和所述操作信息，生成各级用户各自对应的用户特征信息，所述用户特征信息用于表征与所述用户特征信息对应的用户在所述线上商品的分享过程中的贡献；
    奖励信息生成单元，被配置成将所述用户特征信息、所述线上商品的商品特征信息输入预先训练的奖励计算模型，得到各级用户对应的奖励信息；
    推送信息生成单元，被配置成基于用户的所述奖励信息，确定待推送信息。
  8. 根据权利要求7所述的装置，其中，所述装置还包括：
    分享单元，被配置成将所述奖励信息对应的奖励发送至与所述奖 励信息对应的用户的账号；根据各级用户对应的奖励信息，生成奖励汇总信息，以及将所述奖励汇总信息发送至所述各级用户各自对应的账号。
  9. 根据权利要求7所述的装置，其中，所述装置还包括：
    第一调整单元，被配置成分析用户获取所述奖励信息对应的奖励后的、所述线上商品的销售量的变化趋势信息；根据所述变化趋势信息，调整所述奖励计算模型输出的奖励信息。
  10. 根据权利要求7所述的装置，其中，所述装置还包括：
    第二调整单元，被配置成分析用户获取所述奖励信息对应的奖励后，针对分享信息的分享次数的变化趋势信息；根据所述变化趋势信息，调整所述奖励计算模型输出的奖励信息。
  11. 根据权利要求7-10任一所述的装置，其中，所述操作信息指示的操作包括：购买所述线上商品、收藏所述线上商品、浏览所述线上商品、输入所述线上商品的购物体验信息。
  12. 根据权利要求11所述的装置，其中，所述装置还包括：
    关联单元，被配置成响应于确定所述操作信息为输入所述线上商品的购物体验信息，关联所述线上商品的分享信息和所述购物体验信息；显示所述分享信息的同时，显示关联所述分享信息的所述购物体验信息。
  13. 一种计算机可读介质，其上存储有计算机程序，其中，所述程序被处理器执行时实现如权利要求1-6中任一所述的方法。
  14. 一种电子设备，包括：
    一个或多个处理器；
    存储装置，其上存储有一个或多个程序，
    当所述一个或多个程序被所述一个或多个处理器执行，使得所述一个或多个处理器实现如权利要求1-6中任一所述的方法。
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