WO2018036307A1 - Procédé de traitement d'informations utilisé en poussant un ordre d'informations, procédé d'attribution, dispositif et support de stockage de données - Google Patents

Procédé de traitement d'informations utilisé en poussant un ordre d'informations, procédé d'attribution, dispositif et support de stockage de données Download PDF

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WO2018036307A1
WO2018036307A1 PCT/CN2017/093510 CN2017093510W WO2018036307A1 WO 2018036307 A1 WO2018036307 A1 WO 2018036307A1 CN 2017093510 W CN2017093510 W CN 2017093510W WO 2018036307 A1 WO2018036307 A1 WO 2018036307A1
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order
inventory
ratio
exposure
dimension
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PCT/CN2017/093510
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English (en)
Chinese (zh)
Inventor
徐澜
陈戈
金伟
江志
赵鹏昊
张弘
刘磊
黄伟
黄东波
姜磊
黄浩
朱思宇
谷俊青
游乐
魏望
洪福兴
陈怡然
李世强
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腾讯科技（深圳）有限公司
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Publication of WO2018036307A1 publication Critical patent/WO2018036307A1/fr

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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
    • 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]
    • G06Q30/0633—Lists, e.g. purchase orders, compilation or processing
    • G06Q30/0635—Processing of requisition or of purchase orders
    • 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
    • G06Q30/0241—Advertisements
    • G06Q30/0251—Targeted advertisements
    • G06Q30/0255—Targeted advertisements 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
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0251—Targeted advertisements
    • G06Q30/0269—Targeted advertisements based on user profile or attribute
    • G06Q30/0271—Personalized advertisement
    • 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]
    • G06Q30/0623—Item investigation

Definitions

  • the present application relates to the field of the Internet, and in particular, to an information processing method, a distribution method, and corresponding devices and storage media for pushing information orders.
  • the present application provides an information processing method for pushing an information order, comprising: acquiring historical user data; wherein the historical user data includes exposure data that has occurred by each user; and according to the historical user data, for each dimension predetermined Or a combination of dimensions, determining a corresponding number of exposures, and determining a proportion of a set of exposures, wherein each exposure quantity corresponds to a frequency; according to each dimension or combination of dimensions and the corresponding number of exposures and Calculating a set of exposure quantity, establishing an inventory model, the inventory model describing each supply node and its corresponding inventory quantity and a set of inventory proportions; wherein one supply node corresponds to one dimension or one dimension combination, the supply node
  • the corresponding inventory quantity is the exposure quantity corresponding to the dimension or the combination of the dimensions, and the corresponding set of inventory proportions of the supply node includes the ratio of the set of exposure quantity corresponding to the dimension or the combination of the dimensions.
  • the application also provides a service allocation method for pushing information orders, comprising: extracting information of each order; extracting the above inventory model; generating an allocation plan according to the information of each order and the inventory model, the distribution plan includes The service ratio for each order, where the service ratio for each order is determined as follows:
  • the allocation plan is provided to the push server to cause the push server to perform a menu process according to the service ratio in the allocation plan.
  • the application also provides an inquiry method for pushing information orders.
  • the method includes: extracting information of each existing order; extracting the above inventory model; The new order and the orientation of each existing order determine the order of allocation of the new order and the existing orders; in the order of allocation, the existing orders before the new order are sequentially processed as follows:
  • the inventory model determining an inventory ratio corresponding to the frequency limit of the current order corresponding to all supply nodes corresponding to the orientation of the current order; and the inventory amount corresponding to each supply node according to the orientation of the current order, The current estimated inventory remaining amount, the one inventory share ratio, and the current bookable quantity detection value, attempting to determine the service ratio of the current order, updating the current estimated stock remaining amount, and up-regulating according to whether the current order service ratio can be determined.
  • the lower limit of the reservation quantity or the value of the upper limit of the reservation quantity is adjusted, and the bookable quantity detection value is adjusted according to the lower limit of the reservation quantity and the upper limit of the reservation quantity; wherein the initial value of the reservation quantity upper limit is taken as Determining an initial value of the recordable quantity detection value;
  • the final value of the upper limit of the reservation amount is taken as the maximum amount of the bookable amount of the new order.
  • an information processing apparatus for pushing an information order including:
  • One or more memories are One or more memories
  • One or more processors among them,
  • the one or more memories storing one or more instruction modules configured to be executed by the one or more processors;
  • the one or more instruction modules include:
  • a data extraction module which acquires historical user data; wherein the historical user data includes exposure data that has occurred by each user; and a calculation module, according to the historical user data, the needle Determining a corresponding exposure quantity for each predetermined dimension or combination of dimensions, and determining a proportion of exposure quantity, wherein each exposure quantity corresponds to a frequency; a model building module, according to each dimension or dimension combination Corresponding to the ratio of the exposure quantity to the set of exposure quantity, an inventory model is established, and the inventory model describes each supply node and its corresponding inventory quantity and a group of inventory proportions; wherein one supply node corresponds to one dimension Or a combination of dimensions, the inventory quantity corresponding to the supply node is the exposure quantity corresponding to the dimension or the combination of the dimensions, and the set of inventory proportions corresponding to the supply node includes the set of exposures corresponding to the dimension or the combination of the dimensions The proportion is proportional.
  • the present application provides a service distribution device for pushing information orders, including:
  • One or more memories are One or more memories
  • One or more processors among them,
  • the one or more memories storing one or more instruction modules configured to be executed by the one or more processors;
  • the one or more instruction modules include:
  • a data extraction module extracting information of each order, extracting the above inventory model; and assigning a planning module, generating an allocation plan according to the information of each order and the inventory model, where the distribution plan includes a service ratio of each order, wherein each The service ratio of an order is determined by using the inventory model to determine an inventory ratio corresponding to the frequency limit of the order corresponding to all the supply nodes corresponding to the order of the order; and according to the orientation of the order Determining the service ratio of the order corresponding to the inventory quantity, the current estimated inventory remaining quantity, the determined one inventory share ratio, and the order quantity of the order; determining an output ratio of the order; The allocation plan is given to the push server to cause the push server to perform a menu process according to the service ratio in the allocation plan.
  • the present application provides an inquiry device for pushing information orders, when demanding When the party receives a request for a new order, the device includes:
  • One or more memories are One or more memories
  • One or more processors among them,
  • the one or more memories storing one or more instruction modules configured to be executed by the one or more processors;
  • the one or more instruction modules include:
  • a data extraction module extracting information of each existing order, extracting the above inventory model; and assigning a planning module, determining an order of assigning the new order and the existing orders according to the new order and the orientation of each existing order;
  • a planning module determining an order of assigning the new order and the existing orders according to the new order and the orientation of each existing order;
  • the apparatus further includes: a query boundary module, using the inventory model to determine an inventory ratio corresponding to a frequency limit of the new order corresponding to all supply nodes corresponding to the orientation of the new order; according to the orientation with the new order
  • the corresponding inventory quantity corresponding to each supply node, the current estimated inventory remaining quantity, and the one inventory proportion determine the initial value of the reservation quantity upper limit, and set the initial value of the reservation quantity lower limit to a preset value
  • the reservation quantity detection module In the order of allocation, the following processing is performed on each order in order from the new order until the lower limit of the reservation amount is equal to the upper limit of the reservation amount: using the inventory model, all supply nodes corresponding to the orientation of the current order are determined Corresponding inventory ratio that meets the frequency limit of the current order; and the inventory amount corresponding to each supply node corresponding to the orientation of the current order, the current estimated inventory remaining amount, the one inventory ratio, and the current
  • the amount of the detection value can be reserved, an attempt is made to determine the service ratio of the current order,
  • the reservation quantity detection module And adjusting, according to the lower limit of the reservation quantity and the upper limit of the reservation quantity, the bookable quantity detection value; wherein the reservation quantity upper limit initial value is used as an initial value of the bookable quantity detection value; the reservation quantity detection module The final value of the reservation amount upper limit is taken as the maximum bookable amount of the new order.
  • the present application also proposes a non-transitory computer readable storage medium storing computer readable instructions that enable at least one processor to perform the above method.
  • FIG. 1 is a system architecture diagram related to an example of the present application
  • Figure 2 shows the relationship between the supply node and the demand node
  • FIG. 3 is a flow chart of an information processing method for an order in an example of the present application.
  • FIG. 4 is a flow chart of a service allocation method for an order in an example of the present application.
  • FIG. 6 is a schematic diagram of an inventory model establishing apparatus in an example of the present application.
  • FIG. 7 is a schematic diagram of a service allocation apparatus in an example of the present application.
  • FIG. 8 is a schematic diagram of an interrogation device in an example of the present application.
  • FIG. 9 is a schematic structural diagram of a computing device in an example of the present application.
  • the online push information display service (such as the display of online advertisements) can be realized by the order guaranteed by the flow (ie, the exposure quantity).
  • the media party (Publisher, also known as the supplier) responsible for displaying the push information guarantees a predetermined amount of exposure (ie, inventory) that satisfies the ordering predicates to the demanding party (such as the advertiser Advertiser).
  • the orientation describes the target demographic of the push information corresponding to the order, and the impression of the push information to the user is referred to as an exposure.
  • the sales phase purchases a predetermined amount of exposure for an order from the media (ie, purchases a predetermined flow or exposure amount for an order);
  • the sales stage it is necessary to determine whether the predetermined quantity of the new order to be added currently can be satisfied based on the current inventory estimation result; in the service stage, it is necessary to select an order to be exposed based on the current inventory estimation result and determine Prepare for each exposure How much exposure is allocated by the light order. Therefore, the inventory forecast will have certain impact on these two stages. Inaccurate inventory estimation results and imperfect inventory models may cause the exposure flow of some orders to be unguaranteed or some orders to be overexposed (ie, actual exposure). The amount exceeds the predetermined amount of the order).
  • the core issue in the CPM (Cost Per Impressions) contract advertising system is how to allocate an available ad exposure, that is, a set of orders with contractual and audience targeting constraints. Under the estimated inventory, each order is allocated advertising stock according to its audience targeting constraints and demand, so that all orders are not lacking or the overall deficiency is minimal.
  • This allocation scheme can be used to:
  • Guided delivery (ie the second phase above): Provide a basic allocation plan, guide the delivery engine to deliver and adjust the distribution plan according to the real-time feedback data.
  • Auxiliary Inquiries Provides residual exposure information for various audience targeting constraints to help advertisers optimize their advertising plans.
  • FIG. 1 is a structural diagram of a system involved in an example of the present application.
  • the system includes at least an inventory allocation module 101, a data platform 102, a push server 103, and an order management module 104.
  • the inventory allocation module 101 may include an inventory estimation module 111, a sales distribution module 121, and a service distribution module 131.
  • the data platform 102 may include an offline data module 112 and a real-time data module 122.
  • each user uses a client to access some websites, such as browsing a webpage or watching online videos, etc.
  • the push server 103 for example, an advertisement service area for placing Internet advertisements
  • the push server 103 can collect which pages are currently accessed by which users. (URL), which in turn determines which users need to push information and what information to push.
  • the push server 103 generates a respective exposure request for the user currently accessing the network and returns it to the client of the corresponding user, and transmits it to the data platform 102 for recording as log data, such as the real-time data module 122 transmitted thereto.
  • Real-time data module 122 will pass these exposure requests to the offline data module 112 as historical exposure data, and will also update the current subscription amount (or demand amount) of each order based on these exposure requests and pass the latest push amount of each order to the inventory allocation.
  • Module 101 such as service distribution module 131, is passed to it.
  • the inventory allocation module 101 may estimate the inventory amount based on historical exposure data acquired from the data platform 102 (such as the offline data module 112 therein) to obtain an estimated inventory amount, and based on the pre- The inventory model and historical exposure data are used to establish an inventory model.
  • the inventory allocation module 101 (such as the service distribution module 131 therein) may extract information for each order from the order management module 104, extract an inventory model from the inventory estimation module 111, and determine an allocation plan based on the inventory model and information for each order.
  • the inventory allocation module 101 (such as the service distribution module 131 therein) can update the subscription of each order when the latest push amount of each order (ie, the amount of exposure, such as the amount of played of an advertisement) is received from the real-time data module 122. Quantity, which in turn can update the allocation plan.
  • the push server 103 can extract information from the order management module 104 that it is directed to a plurality of orders that match those users for the currently received exposure requests of the plurality of users.
  • the service ratios corresponding to the respective orders are determined according to the distribution plan acquired from the inventory allocation module 101, and the push server 103 can perform menu processing on the orders according to the service ratio in the distribution plan, and can provide information push services based on the menu results (for example, advertisements)
  • the server can push the corresponding advertisement to each user according to the menu result, or determine the unselected order without having to push the advertisement to the user).
  • the inventory allocation module 101 (such as the sales distribution module 121 therein), when receiving a request for a new order from the demand side (such as an advertiser), extracts information of each existing order from the order management module 104, from the inventory
  • the estimation module 111 extracts the inventory model, and determines the most bookable quantity of the new order based on the information of each existing order and the inventory model. Great value.
  • the order management module 104 can send a query request to the stock allocation module 101, and then the demander can know the maximum amount of bookable quantity that can be set for the order, and the stock allocation. 121 also records the maximum amount of bookable amount for the order.
  • the inventory allocation module 101 automatically determines whether the order quantity (or the booked exposure amount or demand amount) of the order is acceptable.
  • the inventory model described above describes each supply node and its corresponding inventory quantity, where a supply node (also referred to as a flow unit) corresponds to a dimension or a combination of dimensions ( Combination of dimensions), the inventory quantity corresponding to the supply node is the exposure quantity corresponding to the dimension or the combination of the dimensions, and various information of the supply node is determined according to historical exposure data (can be obtained by statistics or estimated by an algorithm).
  • a supply node also referred to as a flow unit
  • the inventory quantity corresponding to the supply node is the exposure quantity corresponding to the dimension or the combination of the dimensions
  • various information of the supply node is determined according to historical exposure data (can be obtained by statistics or estimated by an algorithm).
  • an order can also be characterized by a demand node, which corresponds to the ordering of the order and the demand quantity (ie, the order quantity of the order).
  • Figure 2 shows the relationship between the supply node and the demand node.
  • supply nodes there are 6 supply nodes, they have their own dimension/dimension combination and inventory quantity, and there are N demand nodes, which have their own orientation and demand.
  • the dimension combination of supply node 1 is ⁇ Beijing, Sports ⁇ , which represents the user who visits the sports channel from Beijing, and the corresponding inventory amount is 8M, representing the number of user visits with this dimension combination ⁇ Beijing, Sports ⁇ (ie The number of exposure opportunities, also known as the number of exposures, based on historical exposure data is 8M.
  • the orientation of the demand node 1 is ⁇ sports ⁇ , which represents the user who accesses the sports channel, and the corresponding subscription amount is 15M, which means that the number of times the corresponding order is required to be exposed to the user who accesses the sports channel is 15M.
  • the dimension/dimension combination of the supply node is consistent with the orientation of the demand node, and it may be considered to expose the corresponding node corresponding to the user corresponding to the supply node.
  • Order Regarding how to allocate the inventory quantity of each supply node to each demand node, and to meet the orientation constraint and the reservation quantity requirement of the demand node, the following will be elaborated.
  • the present application proposes a series of technical solutions aimed at optimizing the processing of the inventory model, service allocation and sales distribution to ensure the exposure flow of the order (ie, the booked amount) and avoid overexposure, thereby improving the performance of the information push system.
  • FIG. 3 is a flow chart of an information processing method for an order in an example of the present application.
  • the method is applicable to the inventory allocation module 101 of FIG. 1, and specifically to the inventory estimation module 111. As shown in FIG. 3, the method may include the following steps:
  • Step 301 Acquire historical user data; wherein the historical user data includes exposure data that has occurred by each user.
  • historical user data may be acquired from the data platform 102, such as obtaining historical user data from the offline data module 112 therein, wherein the exposure data includes exposure opportunity data that has occurred, and the exposure opportunity for a certain user access is a pointer to this.
  • the secondary user accesses the generated exposure request, but after the service allocation process, the actual exposure is not necessarily generated for the exposure request.
  • the exposure data described above may include page exposure data and media content exposure data (eg, advertisement exposure), page exposure refers to user access to the page, and multiple media content exposure may occur during a user's page visit. .
  • page exposure refers to user access to the page
  • media content exposure may occur during a user's page visit.
  • Step 302 Determine, according to the acquired historical user data, a corresponding exposure quantity for each predetermined dimension or combination of dimensions, and determine a set of exposure quantity ratio, wherein each exposure quantity ratio corresponds to one frequency.
  • the ratio of the number of exposures corresponding to one frequency may be the ratio of the number of exposures of the frequency to the total amount of exposure of the corresponding dimension or the combination of dimensions, or may be the number of exposures that meet the frequency limit when the frequency is used as the frequency limit.
  • Dimension or dimension combination The ratio of the total amount of exposure.
  • the foregoing determining a set of exposure quantity ratios may include: determining, for each dimension or combination of dimensions, an exposure frequency of each user corresponding to the dimension or combination of dimensions, and The exposure quantity ratio is determined separately for each of the determined exposure frequencies to obtain a set of exposure quantity ratios corresponding to the dimension or the combination of dimensions.
  • the frequency of access may be referred to as frequency
  • the frequency of access may be determined.
  • Each access frequency can correspond to an exposure quantity. For example, there are 100 users who can be determined once every five days (that is, there are 100 exposures), 50 users who have 3 times three times (that is, there are 50 exposures), etc. .
  • the ratio of the number of exposures corresponding to each access frequency to the total number of exposures in the dimension or combination of dimensions is the ratio of the number of exposures for that access frequency. Further, according to the ratio of the number of exposures of each access frequency, the ratio of the number of exposures that meet the frequency limit of each access frequency as the frequency limit to the total number of exposures can be calculated.
  • Step 303 Establish an inventory model according to each dimension or combination of dimensions and its corresponding exposure quantity and a set of exposure quantity, the inventory model describes each supply node and its corresponding inventory quantity and a group of inventory proportion .
  • one supply node corresponds to one dimension or one dimension combination
  • the inventory quantity corresponding to the supply node is the exposure quantity corresponding to the dimension or the dimension combination
  • the corresponding group of inventory proportions of the supply node includes the dimension or the combination of the dimensions
  • each supply node and its corresponding set of inventory ratios may also be referred to as a frequency model of inventory (for example, a frequency limit scale model, Frequency Capping) Ratio Model)
  • the frequency model can be considered as part of the inventory model, that is, the inventory model established in the above example is an inventory model that considers the frequency, or an inventory model that includes the frequency model.
  • the established inventory model not only takes into account the inventory of each supply node, but also takes into account the inventory ratio corresponding to each frequency, so that it can be used in subsequent service allocation or sales distribution using this inventory model. Based on the inventory ratio of each frequency, the distribution result is more accurate and reasonable, which can better ensure the order exposure of the order and avoid over-exposure of the order, thereby improving the information push effect and improving system performance.
  • step 302 the above process of determining the exposure frequency of each user corresponding to a certain dimension or combination of dimensions and separately counting the proportion of exposures for each determined frequency of exposure may be performed in several ways:
  • the frequency model established in this way can be referred to as a static frequency model.
  • PV media content exposure
  • AV Advertisement View
  • the PV ratio of each frequency can be determined, that is, the ratio of the number of PVs satisfying x days and y times to the total number of PVs. It can be seen that the first method can solve the problem of exposure limitation of the same media content in the same PV, and the calculation complexity of the statistical PV ratio is lower, and the data accuracy can be ensured.
  • the page access frequency can be expressed as (n, k), where n is a time parameter and k is a number of times.
  • V PV the total number of PVs occurring during that time period
  • UV the number of users contributing to k PVs
  • P UV (n, k) the ratio of the UV contributing to the PV to the total PV number
  • the frequency control requirement (ie, frequency limit) of an order is expressed as (x, y), where x is the time parameter and y is the number of times, such as the frequency limit is x days y times
  • the PV inventory that can satisfy the frequency control requirement The ratio is expressed as Q PV (x, y) (ie, the aforementioned second ratio, indicating the proportion of exposures of the user whose number of page visits is less than or equal to y times within a specified time period x days), and can be expressed by the following formula (2) ) Calculated:
  • the frequency model (that is, the set of stock ratios corresponding to each supply node) can be described as the following formula (3):
  • step 2 according to each V i PV (u) in the exposure data of each user u, the probability p PV (x, r) of x exposures is calculated from the historical data for each remaining inventory ratio r, The V i PV (u) is updated according to p PV (x, r).
  • the foregoing method 1 can be used to count the proportion of the exposure amount.
  • the frequency of the exposure determined in the foregoing step 3 is the page access frequency of each user in the specified time period
  • the step 4 includes: determining the total number of page visits of each user in the specified time period; determining the frequency of access for each page.
  • the number of users corresponding to the frequency of access to the page in each remaining inventory ratio accounts for the first proportion of the total number of visits to the page, and the number of page visits satisfying the access frequency limit of the page for each remaining inventory ratio is calculated by using the first ratio.
  • the second ratio of the total number of page visits, and the second ratio under each remaining inventory ratio is taken as the proportion of the exposure amount corresponding to the page access frequency under each remaining inventory ratio.
  • the expectation, and updating the V i PV (u) according to the calculated expected number of deducted exposures may specifically include the following processing:
  • the PVs of different CV numbers are used in the push log (such as the advertisement log), and a regression algorithm is established to learn.
  • the q PV (x, y, r) obtained in the above mode 2 is a frequency model considering the influence of the remaining stock ratio.
  • This frequency model can be referred to as a dynamic frequency model (such as a dynamic frequency-restricted scale model).
  • the frequency variation in the case of inventory consumption can be simulated, that is, the inventory structure is restored according to the historical log data, the inventory consumption is simulated, and the proportion of exposures corresponding to each frequency under different inventory remaining ratios is learned, so that the service distribution is performed subsequently.
  • the distribution is distributed, the number of exposures of each frequency after the inventory is estimated according to the inventory model is more accurate, which can further optimize the distribution result, and can more accurately allocate the order exposure of the order, and better guarantee the order. Book exposure and avoid over-exposure of orders, which improves information push and improves system performance.
  • the inventors also found in the study that the proportion of exposures of each frequency is directly calculated from each supply node i, and is applied to the corresponding supply node set ⁇ (j) corresponding to the order orientation to generate an error. Because usually ⁇ (j) contains multiple supply nodes, the direct summation of the number of exposures to each supply node will cause a problem of overlapping traffic, resulting in a larger proportion of exposures corresponding to the calculated frequency. For example, for the frequency 7 times 3 times, the exposures of the dimensions ⁇ movie ⁇ and ⁇ television ⁇ account for 20%, but when the order is directed to "movie + TV series", there must be some users watching movies and TV shows.
  • the following methods are used to obtain the above predetermined dimensions or combinations of dimensions:
  • the exposure data across the order-oriented constraints can be counted, and the problem of overlapping UVs of multiple flow units can be solved, which can improve the accuracy of statistics, reduce the calculation amount, and improve the system efficiency.
  • the above clustering calculation method can be specifically as follows:
  • V(x) represents the number of page visits (which can be considered as the number of exposures) determined for the supply node x
  • the similarity between any two orders can be calculated.
  • all the orientations that have appeared in history can be divided into multiple orientation groups. .
  • an orientation is determined as an orientation representation of the orientation group, such as taking a union of orientations within the group or selecting one of the orientations as an orientation representation, and combining the orientation representation as a dimension or dimension combination,
  • the frequency model represented by the orientation is to combine the orientation representation as a dimension or a dimension and learn the corresponding frequency model according to the foregoing method.
  • the orientation group most similar to the orientation of the order is found according to the above similarity formula (6), and the frequency model of the orientation group is used as the frequency model of the order.
  • the frequency model corresponding to each dimension/dimension combination is established, and on this basis, the frequency model corresponding to the orientation of each historical order can be determined, wherein the frequency model corresponding to the orientation of an order is The frequency model corresponding to the dimension or dimension combination that is aligned.
  • the above solution solves the problem of user overlap of different traffic units, and also greatly reduces the algorithm complexity and computational overhead by losing the accuracy of a small number of orders.
  • the data shows that dozens of orientations can accurately serve all orders in history; at the same time, the more similar the orientation, the more similar the frequency structure. Therefore, the impact of this scheme on system accuracy is very small.
  • the establishment of the frequency model described above can be calculated offline and the results stored in a cache.
  • the mitigation results can be directly used when online, and there is no additional time overhead for online calculation.
  • the above frequency model can be calculated online, making the settlement result more real-time and more accurate.
  • the average order quantity of the order in the sales distribution can be increased by 20%, and the weighted deviation of distribution and delivery in the service allocation is reduced by 35%, which greatly improves The accuracy of the order for pushing information during the sale and delivery process.
  • the present application also proposes an allocation method based on the above-mentioned consideration of the inventory model, including the service allocation method of the order and the sales distribution method of the order.
  • FIG. 4 is a flow chart of a service allocation method for an order in an example of the present application.
  • the method is applicable to the inventory allocation module 101 of FIG. 1, and specifically to the service allocation module 131. As shown in FIG. 4, the method includes the following steps:
  • Step 401 Extract information of each order from the order management module 104.
  • Step 402 Extract the inventory model established by the foregoing method from the inventory estimation module 111.
  • Step 403 Generate an allocation plan according to the information of each order and the inventory model, and the allocation plan includes a service rate of each order.
  • Step 404 Providing the above-mentioned allocation plan to the push server 103, so that the push server 103 performs the menu processing according to the service ratio in the allocation plan.
  • the push server 103 when an exposure request for a plurality of users is received from the push server 103, information of a plurality of orders directed to the users is extracted from the order management module 104, and then determined according to the distribution plan obtained from the stock allocation module 101. The service ratios corresponding to each of these orders are extracted to make a menu for these orders.
  • the push server 103 can provide an information push service based on the menu result, for example, according to the menu result, pushing information to the corresponding user (such as placing an advertisement) or determining that the menu fails does not have to push information to any user.
  • the order when the order is fetched, one is to perform directional filtering, that is, to extract each order that matches the users, and the second is to perform frequency filtering, that is, to extract the frequency-constrained requirements from the orders that are aligned with the users.
  • the order that is to say, for each of the orders, determines whether the order has reached the frequency limit number of times for the corresponding user, and then extracts the order that has not reached the frequency limit number.
  • the service ratio of each order can be calculated based on the inventory ratio of the frequency restriction condition extracted from the inventory model, so that the service ratio is more accurate, thereby making the exposure received in real time.
  • the requested menu results are more accurate and more able to meet the information push requirements, which can better guarantee the order flow and prevent overexposure.
  • the inventory quantity of each order's supply node that matches its orientation may be further determined based on the inventory model, and each order is sorted by inventory quantity to determine an allocation order. Then, in this order of allocation, the service ratio of each order is determined in turn.
  • the service ratio is expressed as ⁇ j , and each order may be sorted in a certain order of allocation, and then the service ratio of each order is sequentially calculated in this order. There are two order of this assignment:
  • the order between the order quantity and the stock quantity of the supply node corresponding to the above is arranged in descending order, wherein the order quantity (or demand quantity) of the order j is expressed as d j , and the ratio is expressed as d j /S j .
  • orders with the same orientation but with different booking quantities can be prioritized.
  • the set of inventory ratios corresponding to each of the supply nodes described by the inventory model includes: an inventory share corresponding to each frequency limit under each remaining inventory ratio.
  • the service ratio of each order j in the above step 403 is determined as follows.
  • the estimated remaining inventory quantity of each supply node i is defined as r i
  • the specific processing flow for determining the service ratio ⁇ j for each order j is as follows:
  • an inventory ratio f( ⁇ (j), n j , m j , p) corresponding to the frequency restriction condition (n j , m j ) of the order j can be determined, It can be simplified as f * (j, p).
  • the inventory ratio of each frequency under different inventory residual ratios is considered in the inventory model, so that when the service is allocated, the exposure quantity of each frequency after the inventory is estimated according to the inventory model is more accurate, and then It can further optimize the distribution result, and can more accurately allocate the order exposure of the order, better guarantee the order exposure of the order and avoid over-exposure of the order, thereby improving the information push effect and improving the system performance.
  • the above process of determining the ratio of each order service can be calculated while offline. After receiving the online exposure request, information of a plurality of orders corresponding to the exposure request is extracted, and the service ratio of the orders is determined according to the generated distribution plan, so that the push server 103 can perform online based on the service ratio of the orders.
  • Menu processing for an order, the service ratio of the order for the online menu determined according to the distribution plan may be the same as or slightly smaller than the service ratio of the order included in the distribution plan. That is to say, the service ratio in the allocation plan generated in step 403 represents the service ratio value that the order may select during the actual online menu selection process, but the actual online menu does not necessarily use the service ratio in the distribution plan, which may be based on actual conditions. Adjustment.
  • J ⁇ c 1 ,...,c
  • FIG. 5 is a flow chart of an inquiry method of an order in an example of the present application.
  • This polling method can The sales distribution process that belongs to the order.
  • the method is applicable to the inventory allocation module 101 of FIG. 1, and specifically to the sales distribution module 121.
  • a request for a new order (such as a maximum orderable query request) is received from the demanding party, the query processing of the maximum orderable amount for this new order is required, which is part of the sales allocation.
  • the demand side refers to the party who wants to purchase an order (for example, the advertiser who wants to purchase an advertising order), and needs to make a bookable quantity inquiry before determining the purchase to determine the maximum amount of the orderable quantity of the order.
  • An inquiry request is sent to the inventory allocation module 101 by the order management module 103, which carries information of the new order to be purchased.
  • the method is divided into three phases, including the following steps:
  • Step 501 Extract the information of each existing order from the order management module 103, and extract the inventory model established by the foregoing method from the inventory estimation module 111.
  • Step 502 Determine the order of allocation of the new order and the existing orders according to the new order and the orientation of each existing order.
  • the process of determining an allocation order may include determining an inventory quantity of each order's supply node that matches its orientation based on the inventory model, and ordering each order by inventory quantity to determine an allocation order.
  • Step 503 Perform the following processing for each existing order before the new order in the determined allocation order:
  • Step 504 Using the inventory model, determine an inventory ratio corresponding to the frequency limit of the order corresponding to all the supply nodes that match the orientation of the new order.
  • Step 505 Determine an initial value of the reservation quantity upper limit according to the inventory quantity corresponding to each supply node corresponding to the orientation of the new order and an inventory ratio, and set the initial value of the reservation quantity lower limit to a preset value (for example, set to 0). .
  • Step 506 Perform the following processing on each order in order from the new order in the order of allocation until the lower limit of the reservation quantity is greater than or equal to the upper limit of the reservation quantity:
  • the service ratio of the current order based on the inventory amount corresponding to each supply node corresponding to the orientation of the current order, the current estimated inventory remaining amount, the above-mentioned inventory occupancy ratio, and the current orderable quantity detection value, and update the current Estimating the remaining amount of the stock, adjusting the lower limit of the predetermined booking amount or lowering the upper limit of the predetermined amount according to whether the service ratio of the current order can be determined, and adjusting the minimum amount according to the predetermined amount of reservation and the upper limit of the predetermined amount The amount of reservation detection value.
  • the initial value of the reservation amount upper limit is taken as the initial value of the recordable amount detection value.
  • Step 507 The final value of the reservation amount upper limit is taken as the maximum bookable amount of the new order.
  • the maximum amount of the reservation can be used to determine whether the reservation amount of the new order is acceptable.
  • the maximum amount of the reservation can be used as the sales distribution module 121 as an output parameter.
  • the number is fed back to the order management module 104, and the order management module 104 can determine whether the subscription amount of the new order can be allowed; or, the sales distribution module 121 directly determines whether the reservation amount of the new order is allowed according to the maximum amount of the reservation amount, The judgment result is fed back to the order management module 104 as an output parameter.
  • the order of each order before the new order can be allocated based on the inventory proportion of the frequency restriction condition extracted from the inventory model.
  • the inventory define the query boundary, and detect the maximum amount of bookable quantity, so that the maximum amount of the bookable quantity obtained by the detection is more accurate, and it can better meet the requirements of the order sale distribution, and can better limit the reservation quantity in the order sale (ie, Order flow or order exposure) to prevent over-selling or under-selling of order traffic, thereby better ensuring order traffic in information push and improving the performance of information push services.
  • a set of inventory ratios corresponding to all supply nodes that are consistent with a certain orientation described by the inventory model may include: an inventory ratio corresponding to each frequency limit under each remaining inventory ratio, at this time, in step 503 1)
  • the inventory ratio corresponding to the current order determined in the point may include: the frequency of all the supply nodes in the inventory model that match the orientation of the current order j, and the frequency of the order j in the current estimated remaining inventory ratio p Restricted inventory ratio
  • ⁇ (j) is a set of supply nodes corresponding to the orientation of the order j
  • the frequency limit is expressed as (n j, m j )
  • n j is a time parameter
  • m j is a number of times.
  • the estimated remaining inventory for each supply node i is defined as r i and the new order is order x.
  • step 503 The specific processing of step 503 is as follows:
  • Step 504 specifically includes processing:
  • step 505 the lower limit of the reservation amount d lower initial value is set to 0, and the initial value of the upper limit of the reservation amount d upper can be determined by the following formula (9):
  • step 506 includes:
  • step c) order The upcoming amount of detection value d x is lowered to the mean of the upper and lower limits.
  • the current estimated remaining inventory r i of all supply nodes i is restored to r' i saved in step 1.
  • the process returns to step a) to re-process the new order x and each of the subsequent orders j to perform the processing of i to iv in the above step a).
  • the inventory ratio of each frequency under different inventory residual ratios is considered in the inventory model, so that when the order is inquired, the exposure quantity of each frequency after the inventory is estimated according to the inventory model is more accurate.
  • the detection of the maximum amount of reservations is more accurate, more able to meet the requirements of order sales distribution, can better limit the amount of reservations in the order sale (ie order flow or order exposure), to prevent over-sale or sale of order traffic Insufficient, in order to better ensure the order flow in the information push, improve the performance of the information push service.
  • the present application also proposes an information processing apparatus for pushing information orders.
  • the device can be located in an inventory allocation module 101, such as inventory estimation module 111 therein.
  • the information processing apparatus 600 includes:
  • the data extraction module 601 acquires historical user data; wherein the historical user data includes exposure data that has occurred by each user.
  • historical user data is obtained from data platform 102 (eg, offline data module 112).
  • the calculation module 602 determines, according to the historical user data acquired by the data extraction module 601, a corresponding exposure quantity for each predetermined dimension or combination of dimensions, and determines a proportion of exposure quantity, wherein each exposure quantity corresponds to one frequency.
  • the model establishing module 603 establishes an inventory model according to each dimension or combination of dimensions determined by the calculation module 602 and its corresponding exposure quantity and the set of exposure quantity, the inventory model describes each supply node and Corresponding stock quantity and a group of stock ratio.
  • one supply node corresponds to one dimension or one dimension combination
  • the inventory quantity corresponding to the supply node is the exposure quantity corresponding to the dimension or the dimension combination
  • the corresponding group of inventory proportion of the supply node includes the dimension or the dimension The ratio of the set of exposures corresponding to the combination is proportioned.
  • the calculation module 602 determines, for each dimension or combination of dimensions, the frequency of exposure of each user corresponding to the dimension or combination of dimensions, and determines the proportion of exposures for each of the determined exposure frequencies to obtain the dimension. Or a proportion of the number of exposures corresponding to a combination of dimensions.
  • the calculating module 602 determines, according to the dimension or the combination of the users in the specified time period, the user and the page access frequency thereof; and determines the total number of page visits corresponding to the dimension or the dimension combination in the specified time period; Frequency of page visits, determining a first ratio of the number of users corresponding to the frequency of access to the page to the total number of times of accessing the page, and using the first ratio to calculate the number of page visits satisfying the access frequency limit of the page as the total number of page visits The second ratio is used as the ratio of the exposure amount.
  • the calculation module 602 determines exposure data of each user in the user set corresponding to the dimension or combination of dimensions; for each user's exposure data, estimates the number of exposures consumed under each remaining inventory ratio, and Updating the exposure data of the user according to the estimated number of exposures consumed; determining an exposure frequency of each user according to the updated exposure data of each user; for each exposure frequency, according to each updated user The exposure data determines the proportion of exposures corresponding to the frequency of exposures at each remaining inventory ratio.
  • the apparatus 600 further includes:
  • the clustering module 604 extracts multiple orientations of the historical order from the historical user data acquired by the data extraction module 601, performs clustering calculation on the multiple orientations to obtain at least one orientation group, and uses the at least one orientation group as a location Said predetermined dimensions and/or said dimensions Degree combination.
  • the apparatus 600 may be a computing device, wherein each module may be an instruction module, such that the apparatus 600 may include one or more memories and one or more processors; wherein the one or more memories store one or The one or more instruction modules are configured to be executed by the one or more processors; wherein the one or more instruction modules comprise: any one or any combination of the above modules 601-604.
  • the present application also proposes a service distribution device for pushing information orders.
  • the device can be located in an inventory allocation module 101, such as the service distribution module 131 therein.
  • the service distribution device 700 includes:
  • the data extraction module 701 extracts information of each order and extracts the aforementioned inventory model. For example, the information of each order is extracted from the order management module 104, and the inventory model is extracted from the inventory estimation module 111.
  • the distribution planning module 702 generates an allocation plan according to the information of each order and the inventory model extracted by the data extraction module 701, the distribution plan includes a service ratio of each order, wherein the service ratio of each order is determined as follows :
  • the service ratio of the order is determined based on the inventory amount corresponding to each supply node corresponding to the orientation of the order, the current estimated inventory remaining amount, the determined one inventory share ratio, and the booked quantity of the order.
  • the output module 703 provides an allocation plan generated by the distribution planning module 702 to the push server 103 to cause the push server 103 to perform a menu process according to the service ratio in the distribution plan.
  • the allocation plan module 702 when generating the allocation plan, further The inventory quantity of each order corresponding to the orientation of each order is determined according to the inventory model, and each order is sorted according to the inventory quantity to determine an allocation order; then, in this allocation order, the service ratio of each order is determined in turn.
  • each module can be an instruction module, such that the apparatus 700 can include one or more memories and one or more processors; wherein the one or more memories store one or The one or more instruction modules are configured to be executed by the one or more processors; wherein the one or more instruction modules comprise: any one or any combination of the above modules 701-703.
  • the present application also proposes an inquiry device for pushing information orders, which may be located in the inventory allocation module 101 (such as the sales distribution module 121 therein).
  • the polling device 800 includes:
  • the data extraction module 801 extracts information of each existing order and extracts the above inventory model. For example, the information of each order is extracted from the order management module 104, and the inventory model is extracted from the inventory estimation module 111.
  • the distribution planning module 802 determines the order of allocation of the new order and the existing orders according to the new order and the orientation of each existing order; in the order of the allocation, the following orders are sequentially processed for each existing order before the new order :
  • a query boundary module 803 using the inventory model, to determine an inventory ratio corresponding to the frequency limit of the new order corresponding to all the supply nodes corresponding to the orientation of the new order; each according to the orientation of the new order
  • the inventory quantity corresponding to the supply node and the one inventory ratio are determined, the initial value of the reservation quantity upper limit is determined, and the initial value of the reservation quantity lower limit is set to a preset value.
  • the reservation amount detecting module 804 performs the following processing on each order in order from the new order in the order of allocation until the lower limit of the reservation amount is equal to the upper limit of the reservation amount:
  • the booking amount detection module 804 takes the final value of the reservation amount upper limit as the maximum amount of the new order's bookable amount.
  • the reservation amount detection module 804 can feed back the maximum amount of the orderable quantity of the new order to the order management module 104 for reference when the demand side sets the reservation amount of the new order.
  • the apparatus 800 may be a computing device, each of which may be an instruction module, such that the apparatus 800 may include one or more memories and one or more processors; wherein the one or more memories store one or One or more instruction modules configured to be executed by the one or more processors; wherein the one or more instruction modules comprise: the above modules 801-804 Either or any combination.
  • the present application also proposes an order distribution system for pushing information.
  • the system can include the inventory allocation module 101 shown in FIG.
  • the inventory allocation module 101 may include an inventory estimation module 111, a sales distribution module 121, and a service distribution module 131.
  • inventory estimation module 111 includes inventory model establishing device 600 described above.
  • the service distribution module 131 includes the service distribution device 700 described above.
  • the sale distribution module 121 includes the query device 800 described above.
  • Each of the modules in the inventory allocation module 101 can implement the processing in the various examples described above through interaction with the data platform 102, the push server 103, and the order management module 104.
  • the specific implementation principle has been described in the foregoing and will not be described here.
  • the devices and modules in the various examples of the present application may be integrated into one processing unit, or each module may exist physically separately, or two or more devices or modules may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.
  • the various devices described above can be run in various computing devices and loaded into the memory of the computing device.
  • the apparatus includes the computing device including one or more processors (CPUs) 902, a communication module 904, a memory 906, a user interface 910, and a communication bus 908 for interconnecting these components.
  • processors CPUs
  • communication module 904 a communication module 904
  • memory 906 a user interface 910
  • communication bus 908 for interconnecting these components.
  • the processor 902 can receive and send data through the communication module 904 to implement network communication. Letter and / or local communication.
  • User interface 910 includes one or more output devices 912 that include one or more speakers and/or one or more visual displays.
  • User interface 910 also includes one or more input devices 914 including, for example, a keyboard, a mouse, a voice command input unit or loudspeaker, a touch screen display, a touch sensitive tablet, a gesture capture camera or other input button or control, and the like.
  • the memory 906 can be a high speed random access memory such as DRAM, SRAM, DDR RAM, or other random access solid state storage device; or a non-volatile memory such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, Or other non-volatile solid-state storage devices.
  • a high speed random access memory such as DRAM, SRAM, DDR RAM, or other random access solid state storage device
  • non-volatile memory such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, Or other non-volatile solid-state storage devices.
  • the memory 906 stores a set of instructions executable by the processor 902, including at least:
  • Operating system client 916 includes programs for processing various basic system services and for performing hardware related tasks.
  • Application 918 includes an application for implementing a process flow of any or any combination of the above examples.
  • application 918 can include device 600 of FIG. 6, device 700 of FIG. 7, and/or device 800 of FIG. 8, each of devices 600, 700, and/or 800 can store a machine executable instruction.
  • the processor 902 can implement the functions of the various modules by executing machine executable instructions in the various modules in the memory 906.
  • the hardware modules in each example may be implemented in a hardware manner or a hardware platform plus software.
  • the above software includes machine readable instructions stored in a non-volatile storage medium. Therefore, each instance can also be embodied as a software product.
  • the present application also provides a storage medium in which is stored a data processing program for performing any of the above-described methods of the present application.
  • the hardware may be implemented by specialized hardware or hardware that executes machine readable instructions.
  • the hardware can be a specially designed permanent circuit or logic device (such as a dedicated processor such as an FPGA or ASIC) for performing a particular operation.
  • the hardware may also include programmable logic devices or circuits (such as including general purpose processors or other programmable processors) that are temporarily configured by software for performing particular operations.
  • the machine readable instructions corresponding to the modules of Figures 6-9 may cause an operating system or the like operating on a computer to perform some or all of the operations described herein.
  • the non-transitory computer readable storage medium may be inserted into a memory provided in an expansion board within the computer or written to a memory provided in an expansion unit connected to the computer.
  • the CPU or the like installed on the expansion board or the expansion unit can perform part and all of the actual operations according to the instructions.
  • the non-transitory computer readable storage medium includes a floppy disk, a hard disk, a magneto-optical disk, an optical disk (such as a CD-ROM, a CD-R, a CD-RW, a DVD-ROM, a DVD-RAM, a DVD-RW, a DVD+RW), and a magnetic tape. , non-volatile memory card and ROM.
  • the program code can be downloaded from the server computer by the communication network.

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Abstract

Un procédé de traitement d'informations utilisé en poussant un ordre d'informations consiste à : acquérir un historique de données d'utilisateur (301); déterminer, selon l'historique de données d'utilisateur, et par rapport à chacune des dimensions ou combinaisons de dimensions préconfigurées, des expositions correspondantes, et déterminer un ensemble de proportions d'exposition, dans lequel chacune des proportions d'exposition correspondent à une fréquence (302); et établir, selon chacune des dimensions ou des combinaisons de dimensions, et des expositions correspondantes et de l'ensemble des proportions d'exposition, un modèle d'inventaire décrivant chaque noeud d'alimentation et un stock correspondant de celui-ci et un ensemble de proportions d'inventaire (303). L'invention concerne également un procédé d'attribution, un procédé de détermination d'exposition, et un dispositif correspondant.
PCT/CN2017/093510 2016-08-23 2017-07-19 Procédé de traitement d'informations utilisé en poussant un ordre d'informations, procédé d'attribution, dispositif et support de stockage de données WO2018036307A1 (fr)

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