WO2023097749A1 - Procédé et système de régulation et de contrôle de débit, terminal intelligent, et support d'informations - Google Patents

Procédé et système de régulation et de contrôle de débit, terminal intelligent, et support d'informations Download PDF

Info

Publication number
WO2023097749A1
WO2023097749A1 PCT/CN2021/137091 CN2021137091W WO2023097749A1 WO 2023097749 A1 WO2023097749 A1 WO 2023097749A1 CN 2021137091 W CN2021137091 W CN 2021137091W WO 2023097749 A1 WO2023097749 A1 WO 2023097749A1
Authority
WO
WIPO (PCT)
Prior art keywords
regulation
commodity
data
control
order
Prior art date
Application number
PCT/CN2021/137091
Other languages
English (en)
Chinese (zh)
Inventor
於陈慧
郑富德
刘硕
Original Assignee
同程网络科技股份有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 同程网络科技股份有限公司 filed Critical 同程网络科技股份有限公司
Publication of WO2023097749A1 publication Critical patent/WO2023097749A1/fr

Links

Images

Classifications

    • 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]
    • G06Q30/0607—Regulated
    • 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]
    • G06Q30/0603—Catalogue ordering
    • 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 computer technology, and in particular to a traffic control method, system, intelligent terminal and storage medium.
  • E-commerce refers to the high-efficiency trading activities conducted by buyers and sellers online through the Internet in the open network environment of the Internet in the wide range of commercial and trade activities around the world, which can realize online shopping, Online transactions and online electronic payments between merchants and various commercial activities.
  • the rapid development of mobile applications has spawned a large number of application platforms for realizing e-commerce services, enabling users to select and trade merchants and their products according to the merchant information placed in mobile applications.
  • the application platform that provides e-commerce services can help stores obtain a huge source of customers, attracting a large number of stores to settle in, leading to fierce competition for commodities.
  • the display order of merchants on the application platform that is, the exposure position of merchants, has a great impact on the number of clicks and orders of merchants.
  • Stores with a high exposure position can obtain higher user traffic and thus make more orders.
  • the platform can realize the control of store traffic by adjusting the exposure position.
  • the platform usually adopts fixed rules to control the exposure position of the store, such as top, bottom and adjustment to a specified position.
  • the order volume of different commodity transactions is affected by the exposure position in different procedures. Using a single rule to regulate the exposure position of all stores cannot accurately achieve the expected regulatory effect.
  • the present application provides a traffic regulation method, system, intelligent terminal and storage medium.
  • a traffic control method provided by the present application adopts the following technical solution:
  • a flow control method comprising the following steps:
  • the initial product list is sorted twice to obtain the list of regulated products.
  • the initial product list is obtained, which is convenient for formulating and implementing the corresponding control plan based on the current product list, instead of adjusting according to fixed rules, which helps to improve the traffic control plan. Pertinence and accuracy.
  • the setting of the control plan is based on the control needs of the target product, which helps to intuitively meet the control needs of the product and reduces the possibility that the control plan cannot achieve the effect.
  • the acquisition of the control requirements of the target commodity, and the acquisition of the target commodity based on the regulation requirements before the control scheme under the search request further includes:
  • the exposure order data of the target product at least including the historical exposure position of the target product and the order conversion data corresponding to the historical exposure position;
  • a conversion rate prediction model is generated based on the exposure data.
  • the acquiring historical order data of the target commodity, and acquiring an order prediction model based on the historical order data includes:
  • An order forecasting model is obtained based on the historical order data and supplementary reference features.
  • adding supplementary reference features when training and generating the order prediction model will help to add factors related to product sales, such as product quality and holidays, into the analysis of order prediction, which will help improve order forecasting. Predict the accuracy of the results output by the model.
  • the acquisition of the control requirements of the target commodity, and the acquisition of the control scheme of the target commodity under the search request based on the regulation requirements include:
  • the control scheme is used to adjust the ranking of the target commodity in the commodity list output under the same search request.
  • the method before generating the conversion rate prediction model based on the exposure-to-single data, the method further includes:
  • the simulated conversion data corresponding to the exposure positions of missing exposure single data are obtained based on the fitted exponential curve.
  • the secondary sorting of the initial product list based on the control scheme, and after obtaining the control product list further includes:
  • obtaining the adjusted actual order data according to the time window is helpful for analyzing the actual order data, and further helps to analyze the effect of traffic regulation through the actual order data.
  • the method further includes:
  • a control compensation scheme is obtained based on the control deviation data.
  • the present application provides a traffic control system, which adopts the following technical solution:
  • a flow control system comprising:
  • An initial sorting module configured to obtain a user's search request, and obtain an initial commodity list based on the search request, and the initial commodity list performs commodity sorting based on a preset sorting rule;
  • a regulation scheme module configured to obtain regulation requirements of the target commodity, and obtain a regulation scheme of the target commodity under the search request based on the regulation requirements
  • the regulation output module is used to perform secondary sorting on the initial commodity list based on the regulation scheme to obtain the regulation commodity list.
  • the initial product list is obtained, which is convenient for formulating and implementing the corresponding control plan based on the current product list, instead of adjusting according to fixed rules, which helps to improve the traffic control plan. Pertinence and accuracy.
  • the setting of the control plan is based on the control needs of the target product, which helps to intuitively meet the control needs of the product and reduces the possibility that the control plan cannot achieve the effect.
  • the present application provides an intelligent terminal, which adopts the following technical solution:
  • An intelligent terminal the intelligent terminal includes a processor and a memory, at least one instruction, at least one program, code set or instruction set are stored in the memory, the at least one instruction, the at least one program, the code The set or instruction set is loaded and executed by the processor to implement the traffic regulation method as described in any one of the first aspect.
  • the processor in the smart terminal can implement the above flow control method according to the relevant computer program stored in the memory, and further improve the accuracy of flow control.
  • the present application provides a computer-readable storage medium, which adopts the following technical solution:
  • a computer-readable storage medium wherein at least one instruction, at least one program, code set or instruction set is stored in the storage medium, and the at least one instruction, the at least one program, the code set or the instruction set are processed by The device is loaded and executed to implement a traffic control method as described in any one of the first aspect.
  • the corresponding program can be stored, thereby improving the accuracy of traffic control.
  • the present application includes at least one of the following beneficial technical effects:
  • the initial product list is obtained, which is convenient for formulating and implementing the corresponding control plan based on the current product list, instead of adjusting according to fixed rules, which helps to improve the pertinence and accuracy of the traffic control plan
  • the setting of the control plan is based on the control needs of the target product, which helps to intuitively meet the control needs of the product and reduces the possibility that the control plan cannot achieve the effect;
  • Fig. 1 is a method flowchart of a traffic control method shown in the embodiment of the present application
  • Fig. 2 is a block flow diagram of a traffic control method shown in the embodiment of the present application.
  • Fig. 3 is a system block diagram of a traffic control system shown in the embodiment of the present application.
  • Fig. 4 is a schematic structural diagram of a smart terminal shown in an embodiment of the present application.
  • the embodiment of the present application provides a traffic control method, the method can be applied to a smart terminal, and the smart terminal is used as an execution body to control the exposure position of a product on a search result list page in an online search scenario.
  • the exposure position of a product on the search result list page is usually related to various factors, such as the degree of matching with the search conditions, specifically, under the same traffic control scheme, the higher the degree of matching with the search conditions, the higher the exposure. The higher the position.
  • the search result list pages including the target commodities described in the embodiments of the present application are all generated based on the same search conditions. Based on this premise, the present application provides a traffic control method, including the following steps:
  • step 101 a user's search request is obtained, and an initial product list is obtained based on the search request, and the initial product list is sorted based on a preset sorting rule.
  • the smart terminal obtains the user's search request, and based on the user's search request, the smart terminal can obtain an initial product list matching the search request.
  • the initial product list includes the target product, and the target product is displayed in the initial product list according to a preset sorting rule.
  • the preset sorting rules may be based on the correlation degree between the target product and the search request.
  • the smart terminal can obtain the initial product list to grasp the current exposure position of the target product, which in turn helps to implement a corresponding traffic control plan for the current situation of the target product.
  • Step 102 Obtain regulation requirements of the target commodity, and obtain regulation schemes of the target commodity under the search request based on the regulation requirements.
  • the regulatory demand for the target product can have multiple demand dimensions, such as the increment of orders, the increment of followers of the store where the commodity is located, or the increment of collection of commodities, etc.
  • This embodiment uses the increment of orders as an example to illustrate. Other situations are similar and will not be described in detail.
  • the smart terminal obtains the control requirements for the target product. After the target product generates a certain order increment, it obtains the preset control plan that matches the target product.
  • the control plan corresponds to the target product and can target the target product itself. Product characteristics are designed.
  • the control scheme can adjust the exposure position of the target product, increase the exposure of the target product, and then realize the order growth to realize the control requirement of the target product.
  • step 102 obtain the historical order data of the target commodity, based on the Obtain an order prediction model for the historical order data; obtain the exposure order data of the target product, the exposure order data at least includes the historical exposure position of the target product and the order conversion data corresponding to the historical exposure position; based on the exposure cost Single data generation conversion rate prediction model.
  • the historical order data refers to the order data of the target product on different dates in history, with the change in date as the baseline, reflecting the change in the order volume of the target product on different days;
  • the exposed order data includes at least the historical exposure position of the target product and the order conversion data corresponding to the historical exposure position, taking the change of the exposure position of the product as the baseline, and reflecting the order conversion volume of the target product at different exposure positions.
  • the conversion rate refers to the probability that the user will generate an actual order after clicking on the product.
  • the smart terminal can use the exposed single data as the training data set and train the ESMM (Entire Space Multi Task) twin-tower model to achieve this.
  • the data used in the ESMM twin-tower model can include user search click logs, user click data, and corresponding order information. In addition, it can also include the basic information of the target product, including product price, product use, store address, etc.; user behavior Data, including data in dimensions such as the number of orders placed, favorites, or reposts after the user clicks to browse the product.
  • the ESMM twin-tower model shows the introduction of CTR (Click-Through-Rate, click-through rate) and CTCVR (Click-Through-Conversion- Rate, click and convert) is used as an auxiliary task to learn CVR (Conversion Rate, conversion rate) in a detour, so as to realize the training and prediction work of the conversion rate prediction model.
  • CTR Click-Through-Rate, click-through rate
  • CTCVR Click-Through-Conversion- Rate, click and convert
  • the AUC value can also be used to evaluate the effect of the conversion rate prediction model.
  • the accuracy of the model calculation results may be reduced. Therefore, correspondingly, the above conversion rate
  • the following processing may also be included during the prediction model training: if the sample size of the exposure data of the target commodity is lower than the preset sample threshold, then fitting the exposure data to obtain the fitting exponential curve of the exposure data; The fitting exponential curve obtains the simulated transformation data corresponding to the exposure positions where the single exposure data is missing.
  • the smart terminal after the smart terminal obtains the data associated with the target commodity for training the conversion rate prediction model, it can compare the obtained sample size with the preset sample threshold. If the sample size is lower than the sample threshold, it needs to The data can be supplemented, and the simulated transformation data can be obtained at the exposure position where the missing exposure becomes single data by means of exponential curve fitting.
  • the sample threshold can be set based on the exposure position, and the sample threshold can be set to 20, 25, or 30, etc., that is, the smart terminal needs to at least obtain the target product at the exposure position of 1-20, 1-25, 1-30 All exposures in between are single data.
  • the exposure position of the target product can be used as the X axis, and the conversion rate corresponding to the target product at different exposure positions is the Y axis, and R2 can be 0.9801.
  • the exponential curve can be made close to the relationship between the average exposure position and the conversion rate, and the formula can be as follows:
  • the smart terminal can obtain the historical order data of the target product and the basic information of the target product itself, including product price, product use, store address, etc., and use this as a training data set to train and obtain order predictions.
  • Model Since order forecasting has high requirements on the update performance of the forecasting model, the order forecasting model can be obtained by training with the LightGBM model, and can be forecasted in a rolling iterative manner, that is, the data within a certain time window can be selected as the training data set to predict the next The order volume in a time window to be predicted, as time rolls, the order volume in the next time window to be predicted is reconstructed into the training data set, and then forecasted again. In this embodiment, rolling iterative training can be performed with one week as the time window.
  • the order quantity of the target commodity may be affected by various factors, so the training process of the order prediction model may include the following processing: obtaining the historical order data of the target commodity and at least one supplementary reference feature,
  • the supplementary reference features include at least holiday features and commodity quality; an order prediction model is obtained based on the historical order data and supplementary reference features.
  • the smart terminal when it builds the training data set of the order prediction model, it can add supplementary reference features to the training data set.
  • the supplementary reference features can be set from multiple dimensions associated with the order quantity of the target product, for example: target product Quality fluctuations, time window adjustments for data statistics, product order fluctuation data and corresponding fluctuation factors, historical order volume and corresponding order time, holidays and other characteristic dimensions.
  • the training data set of the order prediction model built by the smart terminal can be based on historical order data, supplemented with the basic information of the target product itself and supplementary reference features, which is conducive to increasing the accuracy of order prediction.
  • the following processing can be performed: obtain the control requirements of the target commodity; obtain a control plan that meets the control requirements based on the order prediction model and the conversion rate prediction model;
  • the regulation scheme is used to perform ranking adjustment of the target product in the product list output under the same search request.
  • the smart terminal after the smart terminal obtains the user's control needs, it can generate a corresponding control plan through the order prediction model and the conversion rate prediction model.
  • the control requirement mentioned above in this embodiment as an example to generate an order increment A for the target commodity within the next time window
  • the smart terminal when the smart terminal obtains the regulation requirement to generate an order increment A, it first obtains the target commodity currently in the default order. Exposure position, the smart terminal can use the order prediction model to predict the order volume of the current target product in the next time window. Assuming that the forecast result is that the default order volume is B, the smart terminal can obtain the final demand for the target product in the next time window. The order volume is A+B.
  • the smart terminal can use the conversion rate prediction model to predict the conversion rate of the product at different exposure positions, and how many exposure positions need to be increased to obtain the order volume of A+B.
  • the smart terminal can obtain a control scheme for the control requirements of the target commodity, that is, an adjustment scheme for exposure positions in different time windows. And then precisely control the regulation and control demand of the target commodity.
  • Step 103 Perform secondary sorting on the initial product list based on the control scheme to obtain a list of regulated products.
  • the intelligent terminal after the intelligent terminal generates the control plan through the order prediction model and the conversion rate prediction model, it can implement the control plan for the target product.
  • the control plan can include one or more The adjustment of the position of the second exposure, so that the total number of order increments obtained by the target commodity in one or more time windows reaches the increment required in the regulation demand.
  • the regulatory demand of the target product involves three time windows, which are time windows 1, 2, and 3.
  • the regulatory demand of the target product is order increment A.
  • the smart terminal assists the smart terminal to generate a control plan by training the order prediction model and the conversion rate prediction model obtained from the product-related data, and guides the adjustment of the exposure position of the product, so that the smart terminal obtains the regulated product list after traffic control.
  • the smart terminal will return the list of regulated products to the user, so that the regulation needs of the target product can be realized.
  • the adjustment plan involving multiple exposure position adjustments spans multiple time windows, which may lead to inaccurate predictions, thereby reducing the accuracy of traffic control. Therefore, correspondingly, the following processing can be performed after step 103: according to the preset The set time window periodically obtains the actual order data of the product, and obtains the control deviation data based on the actual order data of the target product and the control demand; obtains the control compensation plan based on the control deviation data.
  • the smart terminal can obtain the actual order data Xi in the current time window and the difference ⁇ Xi between the target order and the actual order of the previous day, and set the initial control coefficient ⁇ i.
  • each time window can be calculated
  • the update value ⁇ of the control coefficient in the formula is as follows:
  • the smart terminal can update the update value of the control coefficient in the next time window, and the smart terminal can update the control scheme according to the update value, so that the control requirements can be met.
  • the embodiment of the present invention also provides a traffic control system, referring to Figure 3, the system includes:
  • the initial sorting module 1 is used to obtain a user's search request, and obtain an initial commodity list based on the search request, and the initial commodity list performs commodity sorting based on a preset sorting rule;
  • the regulation scheme module 2 is used to obtain the regulation requirements of the target commodity, and obtain the regulation scheme of the target commodity under the search request based on the regulation requirements;
  • the regulation output module 3 is configured to perform secondary sorting on the initial commodity list based on the regulation scheme, and obtain the regulation commodity list.
  • the system also includes:
  • An order forecasting model module configured to acquire historical order data of the target commodity, and acquire an order forecasting model based on the historical order data
  • the conversion rate data module is used to obtain the exposure order data of the target product, and the exposure order data at least includes the historical exposure position of the target product and the order conversion data corresponding to the historical exposure position;
  • a conversion rate prediction model module configured to generate a conversion rate prediction model based on the exposure data.
  • the order forecasting model module includes:
  • the supplementary feature submodule is used to obtain the historical order data of the target commodity and at least one supplementary reference feature, the supplementary reference feature includes at least holiday features and commodity quality;
  • the model generation submodule is used to obtain an order forecasting model based on the historical order data and supplementary reference features.
  • control scheme module 2 includes:
  • a demand acquisition module configured to acquire the regulatory demand of the target commodity
  • the scheme generation module is used to obtain a control scheme that meets the control requirements based on the order prediction model and the conversion rate prediction model; the control scheme is used to implement the ranking adjustment of the target commodity in the commodity list output under the same search request.
  • the conversion rate prediction model module includes:
  • the data fitting sub-module is used to fit the exposure data to obtain the fitting exponential curve of the exposure data if the sample size of the exposure data of the target commodity is lower than the preset sample threshold;
  • the data filling sub-module is used to obtain, based on the fitting exponential curve, the simulated conversion data corresponding to the exposure positions where the missing exposures become single data.
  • the actual data acquisition module is used to periodically acquire the actual order data of the commodity according to the preset time window
  • the deviation acquisition module is used to obtain control deviation data based on the actual order data and control requirements of the target commodity
  • a regulation compensation module configured to obtain a regulation compensation scheme based on the regulation deviation data.
  • the embodiment of the present application also discloses a smart terminal.
  • the smart terminal includes a memory and a processor, and the memory stores a computer program that can be loaded by the processor and execute the traffic control method as described above.
  • the embodiment of the present application also discloses a computer-readable storage medium, which includes various steps in the flow of the above-mentioned traffic control method that can be implemented when loaded and executed by a processor.
  • the computer-readable storage medium includes, for example, a USB flash drive, a mobile hard disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk or an optical disk, etc., which can store program codes. medium.

Landscapes

  • Business, Economics & Management (AREA)
  • Accounting & Taxation (AREA)
  • Finance (AREA)
  • Development Economics (AREA)
  • Economics (AREA)
  • Marketing (AREA)
  • Strategic Management (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

La présente invention se rapporte au champ technique des ordinateurs, et en particulier à un procédé et un système de régulation et de contrôle de débit, à un terminal intelligent, et à un support d'informations, visant à résoudre le problème selon l'état de la technique où parce que la quantité d'ordre de différentes transactions de marchandises est affectée par des positions d'exposition à différents degrés et que les positions d'exposition de toutes les boutiques sont régulées et contrôlées au moyen d'une seule règle, les effets de régulation et de contrôle prévus ne peuvent pas tous être obtenus avec précision. La solution technique selon la présente invention est un procédé de régulation et de contrôle de débit, dont les étapes consistent : à obtenir une requête de recherche d'un utilisateur, à obtenir une liste initiale de marchandises sur la base de la requête de recherche, et à procéder à un tri de marchandises sur la liste initiale de marchandises sur la base d'une règle de tri prédéfinie ; à obtenir une demande de régulation et de contrôle d'une marchandise cible, et à obtenir une solution de régulation et de contrôle de la marchandise cible selon la requête de recherche, sur la base de la demande de régulation et de contrôle ; et à procéder à un tri secondaire sur la liste initiale de marchandises sur la base de la solution de régulation et de contrôle pour obtenir une liste de marchandises de régulation et de contrôle. La présente invention a pour effet d'améliorer la précision de régulation et de contrôle de débit.
PCT/CN2021/137091 2021-11-30 2021-12-10 Procédé et système de régulation et de contrôle de débit, terminal intelligent, et support d'informations WO2023097749A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202111446833.7A CN114255097A (zh) 2021-11-30 2021-11-30 一种流量调控方法、系统、智能终端及存储介质
CN202111446833.7 2021-11-30

Publications (1)

Publication Number Publication Date
WO2023097749A1 true WO2023097749A1 (fr) 2023-06-08

Family

ID=80791462

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/137091 WO2023097749A1 (fr) 2021-11-30 2021-12-10 Procédé et système de régulation et de contrôle de débit, terminal intelligent, et support d'informations

Country Status (2)

Country Link
CN (1) CN114255097A (fr)
WO (1) WO2023097749A1 (fr)

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160321716A1 (en) * 2015-04-30 2016-11-03 Wal-Mart Stores, Inc. System, method, and non-transitory computer-readable storage media for enhancing online product search through multiobjective optimization of product search ranking functions
CN107229728A (zh) * 2017-06-05 2017-10-03 努比亚技术有限公司 基于神经网络的搜索方法、设备及存储介质
CN108416649A (zh) * 2018-02-05 2018-08-17 北京三快在线科技有限公司 搜索结果排序方法、装置、电子设备及存储介质
CN110852818A (zh) * 2018-08-20 2020-02-28 北京京东尚科信息技术有限公司 商品排序方法、装置和计算机可读存储介质
CN111259272A (zh) * 2020-01-14 2020-06-09 口口相传(北京)网络技术有限公司 搜索结果排序方法及装置
CN113240487A (zh) * 2021-05-11 2021-08-10 北京沃东天骏信息技术有限公司 流量调控方法和装置
CN113627995A (zh) * 2021-09-17 2021-11-09 广州华多网络科技有限公司 商品推荐列表更新方法及其装置、设备、介质、产品

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160321716A1 (en) * 2015-04-30 2016-11-03 Wal-Mart Stores, Inc. System, method, and non-transitory computer-readable storage media for enhancing online product search through multiobjective optimization of product search ranking functions
CN107229728A (zh) * 2017-06-05 2017-10-03 努比亚技术有限公司 基于神经网络的搜索方法、设备及存储介质
CN108416649A (zh) * 2018-02-05 2018-08-17 北京三快在线科技有限公司 搜索结果排序方法、装置、电子设备及存储介质
CN110852818A (zh) * 2018-08-20 2020-02-28 北京京东尚科信息技术有限公司 商品排序方法、装置和计算机可读存储介质
CN111259272A (zh) * 2020-01-14 2020-06-09 口口相传(北京)网络技术有限公司 搜索结果排序方法及装置
CN113240487A (zh) * 2021-05-11 2021-08-10 北京沃东天骏信息技术有限公司 流量调控方法和装置
CN113627995A (zh) * 2021-09-17 2021-11-09 广州华多网络科技有限公司 商品推荐列表更新方法及其装置、设备、介质、产品

Also Published As

Publication number Publication date
CN114255097A (zh) 2022-03-29

Similar Documents

Publication Publication Date Title
Almahdi et al. An adaptive portfolio trading system: A risk-return portfolio optimization using recurrent reinforcement learning with expected maximum drawdown
Atkinson et al. The zero lower bound and estimation accuracy
US20040044505A1 (en) Method and system for identifying risk factors
US20090012912A1 (en) Method and System For Simulating Implied Volatility Surface For Basket Option Pricing
CN110751326B (zh) 一种光伏日前功率预测方法、装置以及存储介质
US20140258175A1 (en) Generating Personalized Investment Recommendations
SG189629A1 (en) Curve engine
CN105488163A (zh) 信息推送方法和装置
CN110598183A (zh) 一种流量分配方法、装置、设备及存储介质
Jung et al. An adaptively managed dynamic portfolio selection model using a time-varying investment target according to the market forecast
US20120143782A1 (en) Private Company Valuation
CN110852768A (zh) 动态定价方法及系统、设备、存储介质
Matsumoto et al. Pricing electricity day-ahead cap futures with multifactor skew-t densities
Dias et al. A note on options and bubbles under the CEV model: implications for pricing and hedging
JP2022079368A (ja) 情報処理装置、情報処理方法及びコンピュータプログラム
WO2023097749A1 (fr) Procédé et système de régulation et de contrôle de débit, terminal intelligent, et support d'informations
CN110619407A (zh) 对象销量的预测方法及系统、电子设备和存储介质
CN113191806A (zh) 确定流量调控目标的方法及装置
van den End et al. Central bank balance sheet policies and inflation expectations
Buccioli et al. Constant proportion portfolio insurance strategies in contagious markets
JP7335189B2 (ja) 情報処理装置、情報処理方法及びコンピュータプログラム
EP3876180A1 (fr) Appareil de traitement d'informations, procédé de traitement d'informations et programme informatique
Kacperczyk et al. A new class of Bayesian semi-parametric models with applications to option pricing
CN113421148A (zh) 商品数据处理方法、装置、电子设备及计算机存储介质
Breeden How heterogeneous wine lots result in a price discount relative to homogeneous lots

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21966174

Country of ref document: EP

Kind code of ref document: A1