WO2018153176A1 - 一种订单处理方法及设备 - Google Patents

一种订单处理方法及设备 Download PDF

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Publication number
WO2018153176A1
WO2018153176A1 PCT/CN2018/072272 CN2018072272W WO2018153176A1 WO 2018153176 A1 WO2018153176 A1 WO 2018153176A1 CN 2018072272 W CN2018072272 W CN 2018072272W WO 2018153176 A1 WO2018153176 A1 WO 2018153176A1
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WIPO (PCT)
Prior art keywords
purchase
target item
target
user
item
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PCT/CN2018/072272
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English (en)
French (fr)
Inventor
付丽琴
王慧民
周小丽
袁磊
阳翰凌
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中兴通讯股份有限公司
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Publication of WO2018153176A1 publication Critical patent/WO2018153176A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • 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
    • 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

Definitions

  • This document relates to, but is not limited to, the field of computer technology, and in particular, to an order processing method and device.
  • the embodiment of the invention provides an order processing method and device.
  • an embodiment of the present invention provides an order processing method, where the method includes:
  • the target item When the next order time of the target item arrives, the target item is automatically placed or a shopping reminder is sent to the user.
  • an embodiment of the present invention provides an order processing device, where the device includes:
  • a first determining module configured to determine identification information of the target item and identification information of the user who purchased the target item
  • a second determining module configured to determine, according to the identification information of the target commodity and the identification information of the user who purchases the target commodity, a next ordering time of the target commodity
  • the order module is configured to automatically place an order for the target item or send a shopping reminder to the user when the next order time of the target item arrives.
  • An embodiment of the present invention provides an order processing method and device, which first determines identification information of a target product and identification information of a user who purchases the target product; and then, according to the identification information of the target product and the purchase of the target product Determining, by the user, the purchase record of the target product, and determining the next order time of the target item according to the purchase record of the user purchasing the target item; the next time the target item is reached When placing an order, the target item is automatically placed or a shopping reminder is sent to the user. In this way, according to the user's purchase record, the user's next purchase time can be predicted, and the user is prompted to make a purchase or automatically place an order, thereby improving the user experience.
  • FIG. 1 is a schematic flowchart of an implementation process of an order processing method according to an embodiment of the present invention
  • FIG. 2 is a schematic flowchart of an implementation process of another order processing method according to an embodiment of the present invention.
  • FIG. 3 is a schematic structural diagram of an order processing device according to an embodiment of the present invention.
  • 4-1 is a schematic flowchart of an implementation process of another order processing method according to an embodiment of the present invention.
  • Figure 4-2 is a schematic diagram showing the implementation process of the second implementation manner of adding goods to the smart purchase list
  • 4-3 is a schematic flowchart of implementing an intelligent purchase data according to an embodiment of the present invention.
  • 4-4 is a schematic diagram of a time axis for calculating a next purchase time of an item according to an embodiment of the present invention
  • FIGS. 4-5 are schematic diagrams showing a time axis in which a user randomly purchases according to an embodiment of the present invention
  • FIG. 5 is a schematic structural diagram of an order processing device according to an embodiment of the present invention.
  • FIG. 1 is a schematic flowchart of an implementation process of an order processing method according to an embodiment of the present invention. As shown in FIG. 1 , the method includes:
  • Step S101 determining identification information of the target item and identification information of the user who purchased the target item;
  • the order processing list includes identification information of the target item, identification information of the user who purchased the target item, a next order time of the target item, and a purchase method.
  • the identification information of the target product may be a product code
  • the identification information of the user who purchases the target product may be an identification code (Identification, ID).
  • Step S102 determining, according to the identification information of the target commodity and the identification information of the user who purchases the target commodity, the next ordering time of the target commodity;
  • step S102 includes:
  • Step S102a determining, according to the identification information of the target commodity and the identification information of the user who purchases the target commodity, the historical record of the user purchasing the target commodity;
  • the history of the user purchasing the target item includes at least: a purchase time, a quantity of purchase, and a specification of the target item of the target item purchased by the user.
  • Step S102b Determine a next order time of the target item according to the historical record of the user purchasing the target item.
  • Step S103 when the next order time of the target item arrives, the target item is automatically placed or sent to the user.
  • step S103 the method further includes: determining whether the next order time of the target item arrives.
  • determining whether the next order time of the target item arrives may be implemented by means of message triggering, or may be implemented by means of polling.
  • a message timing clock of the next order time of the target item may be set.
  • a message is triggered which is used to indicate the next order time for the arrival of the target item.
  • the timed query task (such as 8:00 every day) is started to query the target item. Whether the next order will arrive.
  • the preset purchase time may be set as the next order time of the target item is today, or may be set to the next order time of the target item is advanced N days, wherein N is greater than or equal to 1 Natural number.
  • identification information of a target product and identification information of a user who purchases the target product are first determined; and then, according to the identification information of the target product and the user who purchases the target product Identification information, determining a purchase record of the target product purchased by the user, and determining a next order time of the target item according to the purchase record of the user purchasing the target item; when the target item is reached next time In a single time, the target item is automatically placed or a shopping reminder is sent to the user. In this way, according to the user's purchase record, the user's next purchase time can be predicted, and the user is prompted to make a purchase or automatically place an order, thereby improving the user experience.
  • an embodiment of the present invention further provides an order processing method, which is applied to an order processing device.
  • 2 is a schematic flowchart of an implementation process of another order processing method according to an embodiment of the present invention. As shown in FIG. 2, the method includes:
  • step S201 the order processing device determines whether the identification information of the item that the user has purchased is in the order processing list.
  • the order processing device may be an electronic device such as a smart phone, a tablet computer, a notebook computer, a desktop computer or the like.
  • the order processing device determines whether the identification information of the commodity that the user has purchased is in the order processing list, and if the identification information of the purchased commodity is in the order processing list, then proceeds to step S204, if the purchased If the identification information of the item is not in the order processing list, the process proceeds to step S202.
  • a user with a user ID of 123 purchases a barrel of peanut oil encoded as HS456. After the purchase is completed, the order processing device determines whether the HS 456 is in the order processing list.
  • Step S202 If the identification information of the item that the user has purchased is not in the order processing list, the order processing device determines whether the number of times the user purchases the purchased item reaches a preset threshold.
  • step S203 if the number of times the user purchases the purchased item reaches a preset threshold, then the process proceeds to step S203, and if the number of times the user purchases the purchased item does not reach the preset threshold, the process ends.
  • the identification information of the purchased product of the user is not in the order processing list, determining, according to the identification information of the purchased product and the identification information of the user, the history record of the purchased product by the user, and then according to The user purchases a history record of the purchased product, determines the number of times the user purchases the purchased product, and further determines whether the number of times the user purchases the purchased product reaches a preset threshold.
  • the order processing device queries the history record of the user ID 123, calculates the number of times the user purchases the product coded as HS 456, and determines that the user purchases the product coded as HS 456. Whether the number of times reaches a preset threshold, for example, the preset threshold is 5.
  • Step S203 if the number of purchases of the purchased item reaches a preset threshold, the order processing device adds the identification information of the item that the user has purchased and the identification information of the user to the order processing list.
  • the user ID 123 and the article code HS 456 are added to the order processing list.
  • Step S204 the order processing device determines, according to the identification information of the purchased product and the identification information of the user, a history record of the user purchasing the purchased product;
  • the purchased merchandise in the embodiment of the present invention is the target merchandise in other embodiments of the present invention.
  • Step S205 the order processing device determines the next order time of the target item according to the history record of the user purchasing the purchased item.
  • the exemplary embodiment of the present invention provides an exemplary calculation method.
  • the first calculation method determining the next order time of the purchased item according to the average consumption speed of the purchased item, including the following steps:
  • Step S2051a confirming, according to the history record of the purchased product by the user, confirming the purchase information that the user purchases the purchased product for the first time to the nth purchase of the purchased product;
  • the purchase information of the purchased item of the nth time is the purchase information of the purchased item that was purchased last time
  • the purchase information of the purchased item of the i-th purchase is the purchase time t i , the quantity of purchase n i and
  • the specification s i , i of the purchased product is a natural number between 1 and n;
  • Step S2051b determining, according to the purchase information of the first purchase of the purchased item by the user to the nth purchase of the purchased item, the average consumption speed V′ of the purchased item between t 1 and t n ;
  • the total purchase amount of the target commodity between t 1 and t n is determined according to the purchase information of the first purchase of the target merchandise by the user to the nth purchase of the target merchandise; according to t 1 to t n the target product between the total amount of the purchase and the time t t. 1 to determine the difference between the t n and t. 1 n between the average consumption rate of the target product V '.
  • the average consumption speed V' of the purchased goods between t 1 and t n can be determined according to the formula (2-1).
  • t i is the purchase time of the purchased purchase of the i-th purchase
  • n i is the purchase quantity of the purchased product of the i-th purchase
  • s i is the i-th purchase
  • Step S2051c determining the next order time of the purchased item according to the average consumption speed of the purchased item and the purchase information of the target item purchased for the nth time.
  • the usage time of the target item of the nth purchase is determined according to the average speed of the target item and the purchase information of the target item for the nth purchase; and the purchase time of the target item according to the nth purchase is further The usage duration of the target item purchased for the nth time determines the next order time of the target item.
  • V n represents the n-th time is later purchased goods to the first n T n + 1 times later time the purchased items consumed t n + n n S n velocity between 1 and n be the V Obtained by the formula (2-2).
  • n n is the n th later purchased quantity of purchases, S n of the n-th later purchased goods specifications.
  • a second calculation method determining that the average acceleration of the purchased commodity is consumed between the average speeds V′ and t 1 to t n of the purchased commodity between the t 1 and t n-1
  • the next purchase time of the purchased item including the following steps:
  • Step S2052a confirming, according to the history record of the purchased item by the user, confirming the purchase information of the purchased item to the nth purchase of the purchased item for the first time;
  • the purchase information of the purchased item of the nth time is the purchase information of the purchased item that was purchased last time
  • the purchase information of the purchased item of the i-th purchase is the purchase time t i , the quantity of purchase n i and
  • the specification s i , i of the purchased product is a natural number between 1 and n;
  • Step S2052b determining, according to the purchase information of the first purchase of the purchased item by the user to the nth purchase of the purchased item, determining an average speed V′ of the purchased item between t 1 and t n-1 And consuming an average acceleration of the purchased item between t 1 and t n ;
  • the average speed V' of the purchased commodity between t 1 and t n-1 is determined according to the formula (2-5).
  • the average acceleration of the target commodity consumed between t 1 and t n is determined according to the formula (2-8).
  • Step S2052c according to the consumption of between 1 and t n-1 t is the average velocity purchases V 'and t 1 to t n between said average acceleration consumption goods has been purchased, the purchased items is determined The next purchase time.
  • the average velocity V' of the purchased commodity between t 1 and t n-1 is taken as v n-1 into the formula (2-11), and the quadratic equation of the formula (2-11) is solved.
  • ⁇ t is determined, and according to formula (2-12), the next order time t n+1 of the purchased item is determined. If there is no solution, the first calculation method can be used to determine the next order time t n+1 of the purchased product.
  • the t between the consumption. 1 to t n and t is the average acceleration of purchases n-1 and t n between the consuming speed v commodity n-1, the determination has been The next purchase time of the purchased item, including the following steps:
  • Step S2053a confirming, according to the history record of the purchased product by the user, confirming purchase information of the purchased product to the nth purchase of the purchased product for the first time;
  • the purchase information of the purchased item of the nth time is the purchase information of the purchased item that was purchased last time
  • the purchase information of the purchased item of the i-th purchase is the purchase time t i , the quantity of purchase n i and
  • the specification s i , i of the purchased product is a natural number between 1 and n;
  • Step S2053b according to the first user to purchase the goods purchased to the n-th information for later purchase the goods purchased and to determine an average acceleration.
  • the consumption speed of the commodity between 1 and t n is v n-1 ;
  • the consumption speed v n-1 of the article between t n-1 and t n is determined according to the formula (2-7), and is determined according to the formulas (2-6), (2-7), and (2-8).
  • the average acceleration of the purchased item is consumed between t 1 and t n .
  • Step S2054c according to t. 1 between the t n and t are average acceleration consuming the purchased items to t n-1 of the product between the consuming speed v n n-1, determining the purchased commodity Next purchase time.
  • the formula (2-7) is substituted into the formula (2-11), and the quadratic equation of the formula (2-11) is solved to obtain ⁇ t, and then according to the formula (2-12), the purchased product is determined.
  • Order time t n+1 at a time. If there is no solution, the first calculation method can be used to determine the next order time t n+1 of the purchased product.
  • Step S206 the order processing device determines whether the next order time of the purchased item is reached.
  • Step S207 if the next order time of the purchased item arrives, the order processing device determines the purchase mode set by the user;
  • Step S208 the order processing device performs the purchase according to the purchase mode set by the user.
  • identification information of a target product and identification information of a user who purchases the target product are first determined; and then, according to the identification information of the target product and the user who purchases the target product Identification information, determining a purchase record of the target product purchased by the user, and determining a next order time of the target item according to the purchase record of the user purchasing the target item; when the target item is reached next time In a single time, the target item is automatically placed or sent to the user according to the purchase mode set by the user. In this way, according to the user's purchase record, the user's next purchase time can be predicted, and the user is prompted to make a purchase or automatically place an order, thereby improving the user experience.
  • an embodiment of the present invention further provides an order processing method, which is applied to an order processing device.
  • the identification information of the target item purchased by the user already exists in the order processing list, and the next purchase time of the target item has been calculated.
  • the order processing method provided by the embodiment of the present invention includes the following steps:
  • the order processing device determines whether the time when the user last purchased the target item is earlier than the next purchase time of the target item in the order processing list; if the time when the user last purchased the target item If the next purchase time of the target item is earlier than the order processing list, the process proceeds to the second step if the user purchases the target item last time no earlier than the next purchase of the target item in the order processing list. Time, the process ends.
  • the product may be discounted, the user may not have purchased the next purchase time of the target product, and then the next purchase of the target product in the order processing list needs to be updated. time.
  • the user is determined according to the historical record of the user purchasing the target item. The remaining amount of the target commodity before the purchase time of the last purchase of the commodity;
  • the remaining amount of the target item before the time when the user last purchased the item is determined according to the formula (3-1).
  • m is the remaining amount of the target commodity before the purchase time of the user's most recent purchase of the commodity
  • v n- 1 is between t n-1 and t' n
  • the consumption speed of the commodity t n-1 is the time when the user purchases the target commodity for the n-1th time
  • t' n is the next purchase time of the target in the order processing list
  • t n is the latest time of the user The time to purchase the target item at a time.
  • the next purchase time of the target item is updated according to the remaining amount of the target item and the history record of the user purchasing the target item.
  • next purchase time of the target item is calculated according to the formula (3-2), and the next purchase time of the target item in the order processing list is updated.
  • the average velocity V' calculated according to the formula (2-1) is taken as v n and substituted into the formula (3-2) to calculate t n+1 .
  • the second calculation method or the third calculation method provided by the foregoing embodiment may also be used to calculate when the user purchases the target item before the next purchase time of the target item in the order processing list. The next purchase time of the target item.
  • the next purchase time of the target item in the order processing list is recalculated and updated. In this way, the user's next purchase time can be predicted more accurately.
  • FIG. 3 is a schematic structural diagram of an order processing device according to an embodiment of the present invention.
  • the order processing device includes: a data module 301, a setting module 302, and intelligent decision purchase. Module 303, reminder module 304, and order purchase module 305, wherein:
  • the data module 301 is configured to provide data support.
  • the data stored in the data module includes at least:
  • the product information includes a product code, a product identification code, and other information of the product.
  • the item information is usually stored in the form of a table as follows.
  • Commodity code A code that uniquely identifies an item in the system. For example, the brand 1 kg (kilogram, kg) is loaded with laundry detergent, coded as 10001, and the brand 2 kg is loaded with laundry detergent, and the code is 10002.
  • Commodity identification code It is the category identification code of the product in the system.
  • the only code indicating the type of the product is the mark that the product can be replaced by other brands of the same kind.
  • the brand 1kg laundry liquid the product identification code is XYY01
  • the brand 2kg laundry liquid the product identification code is also XYY01
  • when the smart purchase can be replaced as the same type of goods. It can be used with official HS code or system customization.
  • Product specifications The packaging specifications of the product, such as 500 grams (gram, g), 1 kg, 52 tablets, 500 ml (milliliter, ml), 1 liter (Liter, L).
  • Other information about the product includes information such as price and inventory, and no restrictions are imposed.
  • the historical order information includes information such as a user identification code, purchased product information, a quantity of goods, and an order time.
  • the historical order information is usually stored in the form of a table as follows.
  • Order Number The number of each order.
  • the commodity code has the same meaning as the commodity code representation in the product information.
  • User ID Uniquely identifies a user and can be USER_ID.
  • Quantity refers to the number of purchases of this item in this order.
  • Order time The date and time of purchase.
  • the user smart purchase list includes a user identification code, a product identification code, a product code, a consumption speed, a possible inventory amount, and a next purchase time.
  • the user smart purchase list is typically stored in a table format as follows.
  • the product identification code, the product code, and the user identification code have the same meanings as the product identification code, the commodity code, and the user identification code in the historical order information.
  • Next purchase time Estimated users need to make up the goods at this time, used to remind users or purchase.
  • the method of purchase the method of “automatically adding a shopping cart and reminding the user” or “purchasing the automatic order”, the embodiment of the invention is not limited or can be extended.
  • the user smart purchase list can be one table or multiple tables.
  • the user smart purchase list records the smart purchase data of the user purchasing a certain product (such as laundry detergent).
  • a certain product such as laundry detergent
  • the user numbered 1234 needs to purchase the laundry detergent intelligently. It has purchased the brand 1kg laundry liquid (coded as 10001) and the brand 2kg laundry liquid (coded as 10002), the next time for its smart purchase. For December 12, 2016, the purchase method is automatic order purchase (02).
  • the setting module 302 is configured to set a purchase mode in the smart purchase list or add the product selected by the user to the smart purchase list or delete the product selected by the user from the smart purchase list.
  • the system may provide an entry for the product to be added to the smart purchase.
  • the product data is added to the “user smart purchase list” in the data module.
  • the system For the frequently purchased item that has been added to the smart purchase, the system provides an entry for removing the item from the smart purchase, and after the user operates, the item data is removed from the “user smart purchase list” in the data module.
  • the system can also provide an entry for all smart purchases to set up purchase methods. After setup, all smart purchases are in a uniform manner.
  • the smart decision purchasing module 303 is configured to determine whether the merchandise reaches the smart buying opportunity. When the timing is up, the user will be based on the smart purchasing method set by the setting module or the “purchase method” in the “user smart purchase list” in the system. The product is automatically added to the shopping cart and notified by SMS, message or email, or automatically placed to purchase.
  • the expired smart purchase can be performed in a message-triggered manner or in a polling manner.
  • the polling method it is possible to determine whether the smart purchase of the product meets the timing for each user in the “user smart purchase list” by turning on the timed task (for example, 00:00 every day), and the present invention does not limit the present invention. .
  • the timing of the present invention may be that the "next time of purchase" is today, or may be reminded or purchased by the user N days in advance, and is not limited in the embodiment of the present invention.
  • the reminding module 304 is configured to automatically add the expired smart purchased item to the shopping cart, and notify the user by means of a short message, information or mail. Notifications can also be attached to recommendations.
  • the order purchase module 305 is configured to generate an order for purchasing an item, and complete the order follow-up process.
  • FIG. 4-1 is a schematic flowchart of an implementation of an order processing method according to an embodiment of the present invention. As shown in FIG. 4-1, the method includes:
  • step S401 the item is added to the smart purchase list.
  • step S401 can be implemented in the following two ways:
  • an item is added to the smart purchase list according to an operation on the portal provided by the user based on the order processing device for the regular purchase item (which can be provided only to the frequently purchased item).
  • the product is added to the smart purchase list according to the purchase information of the product.
  • FIG. 4-2 is a schematic diagram of an implementation process of the second implementation manner of adding an item to the smart purchase list. As shown in FIG. 4-2, the following steps are included:
  • step S421 it is determined whether the item is purchased or not.
  • step S422 if the purchase of the product is completed, the process proceeds to step S422, and if the item is not purchased, the process ends.
  • Step S422 determining whether the product identification code of the product exists in the smart purchase list.
  • step S402 if the product identification code of the product exists in the smart purchase list, the process proceeds to step S402, and if the product identification code of the product does not exist in the smart purchase list, the process proceeds to step S423.
  • Step S423 determining whether the number of purchases of the item is greater than a preset threshold.
  • the item identification code of the item does not exist in the smart purchase list, searching for the history of the user purchasing the item according to the item identification code of the item and the user identification code of the user who purchased the item Recording, determining whether the number of purchases of the commodity is greater than a preset threshold N, and if the number of purchases of the commodity is greater than a preset threshold N, proceeding to step S424, if the number of purchases of the commodity is not greater than a preset threshold, Then the process ends.
  • the item is a normal purchase (the item identification code is not in the smart purchase list), the item is automatically added to the smart purchase list according to a preset rule; if the item is a smart purchase (the item identification code is in the smart purchase) Checklist), directly adjust the smart purchase data.
  • the rule for automatic purchase of goods is “history purchases are greater than N times”, N system is customized.
  • Step S424 adding the item to the smart purchase list.
  • step S402 the smart purchase data is adjusted.
  • step S402 adjusts the smart purchase data to include:
  • step S402a it is determined whether the product identification code of the added product exists in the smart purchase list.
  • the smart purchase list in the embodiment of the present invention is the same as the content and function stored in the order processing list in other embodiments of the present invention.
  • step S402c If the product identification code of the product exists in the smart purchase list, the process proceeds to step S402c, and if the product identification code of the product does not exist in the smart purchase list, the process proceeds to step S402b.
  • step S401 is implemented by the first implementation, the product identification code and the product code are directly added to the smart purchase list, and the smart purchase list data is calculated and set.
  • Step S402b adding the product identification code of the product to the smart purchase list.
  • the product identification code does not exist in the smart list, that is, if the product has not been purchased (for example, the laundry liquid has not been purchased)
  • the product identification code and the product are added to the smart purchase list. , calculate and reset smart purchase data.
  • Step S402c determining whether the commodity code of the commodity exists in the smart purchase list.
  • step S402e if the product code of the item exists in the smart purchase list, the process proceeds to step S402d.
  • the process proceeds to step S402e to calculate and reset the smart purchase data.
  • Step S402d adding the product code of the product to the smart purchase list.
  • step S402e the smart purchase data is calculated and reset, in particular, the next purchase time.
  • the embodiment of the present invention recommends a method, but is not limited thereto.
  • the next purchase time in the embodiment of the present invention is the same as the next order time in the other embodiments.
  • FIG. 4-4 is a schematic diagram of a time axis for calculating the next purchase time of an item according to an embodiment of the present invention. For ease of understanding, the identifier in FIG. 4-4 is first described.
  • t indicates the purchase time, which is the time of a purchase.
  • n indicates the quantity purchased, which is the quantity of goods purchased at a time.
  • s indicates the specifications of the purchased product.
  • t 1 , n 1 , s 1 are the time, quantity and product specifications of the first purchase of a certain product; t n , n n , s n are the nth purchase of a certain product respectively. Time, quantity and product specifications.
  • T is the time interval
  • T1 is the time interval of the second purchase and the first purchase
  • Tn-1 is the time interval of the nth purchase and the n-1th purchase.
  • the speed v is the speed at which the user consumes the product.
  • v is the speed of consumption of the product, specifically That is, in time t, n s specifications of goods are consumed, and v n is the speed at which n n s n is consumed between the nth and n+1th purchases, and is calculated by the formula (4-1); v n-1 is the speed at which n n-1 s n-1 is consumed between the n-1th and the nth purchase, and is calculated by the formula (4-2).
  • n+1th purchase time t n+1 can be as follows:
  • the average speed V' of the purchased commodity between t 1 and t n-1 is determined according to the formula (4-12).
  • the average velocity V' of the purchased commodity between t 1 and t n-1 is taken as v n-1 into the formula (4-11), and the quadratic equation of the formula (4-11) is solved.
  • ⁇ t is determined, and according to formula (4-13), the next purchase time t n+1 of the purchased product is determined. If there is no solution, the first calculation method can be used to determine the next purchase time t n+1 of the purchased product.
  • Substituting the formula (4-2) into the formula (4-11) and solving the quadratic equation of the formula (4-11) can obtain ⁇ t, and then determining the purchased product next time according to the formula (4-13). Purchase time t n+1 . If there is no solution, the first calculation method can be used to determine the next purchase time t n+1 of the purchased product.
  • the nth purchase is a random purchase before the arrival of its smart purchase time t n '.
  • the judgment condition may be that the purchase time t n is earlier than the next purchase time t n 'M days calculated by the system and the commodity is a discount promotion, and the M may be customized by the system, such as half a month or the like.
  • the margin m of the user possessing the commodity at time t n can be obtained by the formula (4-14):
  • step S403 the smart purchase is performed due to expiration.
  • step S403 is a function performed by the intelligent decision purchase module in other embodiments of the present invention, and determines whether the commodity reaches the smart purchase timing. If the purchase timing of the commodity is reached, the smart purchase method set by the user in the setting module or The “purchase method” in the “user smart purchase list” in the system is for the user to automatically add the product to the shopping cart and send a notification by means of SMS, information or mail, or automatically place an order to purchase. It can also be recommended.
  • expired smart purchases may be performed in a message triggered manner or in a polled manner.
  • the polling method it is possible to determine whether the smart purchase item meets the timing for each user in the “user smart purchase list” by turning on the timed task (for example, 00:00 every day), and the time condition can be met. It is "the next purchase time” is today, or it may be a reminder or purchase for the user N days in advance, and the present invention is not limited.
  • the system can automatically purchase A or automatically purchase. B, you can also choose which item to buy according to certain rules (buy more, or recently purchased).
  • the time of the product is calculated and predicted (ie, the next purchase) Time), automatic reminder or automatic purchase at the end, to achieve the purpose of making up the supply for the user in time.
  • an embodiment of the present invention provides an order processing method, which is applied to an order processing device, where the method includes the following steps:
  • the order processing device After the purchase of the same item 5 times, the order processing device provides an entry for the item to be added to the smart purchase. The user clicks on the portal and sets the smart purchase method for the item as "purchase reminder"
  • the order processing device directly adds the product identification code and the product code to the smart purchase list, and calculates and sets the time of the next smart purchase.
  • the order processing device calculates the next smart purchase time of the item in accordance with a method provided in other embodiments of the present invention.
  • the order processing device intelligently makes a purchase.
  • the order processing device confirms the smart purchase time of the product, the product is added to the shopping cart according to the setting of the user, and information or mail is used. Reminder, at the same time, you can also recommend similar products.
  • the user can be automatically supplemented with the supply, which saves the user's effort and effort. At the same time, avoid situations where nothing is available because you forgot to buy.
  • an embodiment of the present invention further provides an order processing method, which is applied to an order processing device, and the method includes the following steps:
  • the first step after purchasing the same item 5 times, the order processing device automatically adds the item to the smart purchase list.
  • the order processing device automatically adds the item to the smart purchase list including the order processing device adding at least the item identification code and the item code of the item to the smart purchase list.
  • the next smart purchase time is calculated and set.
  • the order processing device calculates the next smart purchase time of the item in accordance with a method provided in other embodiments of the present invention.
  • the order processing device intelligently makes a purchase, and when the order processing device determines that the smart purchase time of the product is reached, according to the unified setting of the user in the system of the order processing device (for example, the user is set to automatic Purchase), generate orders for goods, automatically purchase for users, payment methods can be cash on delivery or automatic deductions set by the user in the system.
  • the embodiment of the invention further provides an order processing method, which is applied to a shopping device.
  • the method includes the following steps:
  • the order processing device performs a smart purchase, and the smart purchase of the product ends.
  • the order processing device calculates and sets the time of the next smart purchase of the item.
  • the order processing device calculates the next smart purchase time of the item in accordance with a method provided in other embodiments of the present invention.
  • the smart order processing device performs intelligent decision purchase, and when confirming the smart purchase time of the product, the product is added to the shopping cart according to the unified setting of the user in the system (for example, the user equipment is a reminder purchase) And remind you by means of information or email, and you can also recommend similar products.
  • FIG. 5 is a schematic structural diagram of an order processing device according to an embodiment of the present invention.
  • the order processing device 500 includes: a first determining module 501 and a second determining module. 502 and an order module 503, wherein:
  • the first determining module 501 is configured to determine identification information of the target item and identification information of the user who purchased the target item;
  • the second determining module 502 is configured to determine a next purchase time of the target commodity according to the identification information of the target commodity and the identification information of the user who purchases the target commodity;
  • the second determining module 502 includes:
  • a first determining unit configured to determine, according to the identification information of the target commodity and the identification information of the user who purchases the target commodity, the history record of the user purchasing the target commodity;
  • the second determining unit is configured to determine a next purchase time of the target item according to the history record of the user purchasing the target item.
  • the second determining unit includes:
  • a first determining subunit configured to determine purchase information of the first purchase of the target item by the user to the nth purchase of the target item according to a history record of the user purchasing the target item; wherein, the nth The purchase information of the target product is the purchase information of the target product purchased for the last time, and the purchase information of the target product for the i-th purchase is the purchase time t i , the purchase quantity n i and the specification of the target product s i , i is a natural number between 1 and n;
  • a second determining subunit configured to determine an average consumption speed V′ of the target item between t 1 and t n according to purchase information of the first purchase of the target item by the user to the nth purchase of the target item ;
  • the third determining subunit is configured to determine a next purchase time of the target item according to an average consumption speed of the target item.
  • a fourth determining subunit configured to determine purchase information of the first purchase of the target item by the user to the nth purchase of the target item according to a history record of the user purchasing the target item; wherein, the nth The purchase information of the target product is the purchase information of the target product purchased for the last time, and the purchase information of the target product for the i-th purchase is the purchase time t i , the purchase quantity n i and the specification of the target product s i , i is a natural number between 1 and n;
  • Fifth determining sub-unit, provided to the user according to the first order to the n-th target commodity purchase commodity purchase information of the target is determined between t 1 to t n-1 of the target product of the average consumption rate V '. 1 and t to t n between the average consumption of the acceleration of the target product;
  • a sixth determining subunit configured to determine that the average acceleration of the target commodity is consumed between the average speeds V′ and t 1 to t n of the target commodity consumed between the t 1 and t n-1 The next purchase time of the target item.
  • a seventh determining subunit configured to confirm purchase information of the first purchase of the target item to the nth purchase of the target item according to a history record of the user purchasing the target item; wherein, the nth The purchase information of the target product is the purchase information of the target product purchased for the last time, and the purchase information of the target product for the i-th purchase is the purchase time t i , the purchase quantity n i and the specification of the target product s i , i is a natural number between 1 and n;
  • Determining an eighth sub-unit determines the first purchase of the target n-th product to later purchase information of the target product 1 and the average acceleration of the target commodity consumption t n t between t
  • the consumption speed of the commodity between n-1 and t n is v n-1 ;
  • the ordering module 503 is configured to automatically place an order for the target item or send a shopping reminder to the user when the next purchase time of the target item arrives.
  • the order processing device further includes:
  • a first determining module configured to determine whether the identification information of the purchased product is in the order processing list
  • a second determining module configured to determine whether the number of purchases of the purchased item reaches a preset threshold if the identification information of the purchased item is not in the order processing list
  • the adding module is configured to add the identification information of the purchased item to the order processing list if the number of purchases of the purchased item reaches a preset threshold.
  • a third determining module configured to determine whether a purchase time of the last purchase of the item by the user is earlier than a next purchase time of the target item in the order processing list
  • a third determining module configured to determine, if the purchase time of the last purchase of the item by the user is earlier than a next purchase time of the target item in the order processing list, according to the historical record of the user purchasing the target item The remaining amount of the target item before the purchase time of the user last purchased the item;
  • the update module is configured to update a next purchase time of the target item according to a remaining amount of the target item and a history of the user purchasing the target item.
  • the embodiment of the invention further provides a computer readable storage medium storing computer executable instructions, which are implemented by the processor to implement the method described in the foregoing embodiments.
  • computer storage medium includes volatile and nonvolatile, implemented in any method or technology for storing information, such as computer readable instructions, data structures, program modules, or other data. , removable and non-removable media.
  • Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridge, magnetic tape, magnetic disk storage or other magnetic storage device, or may Any other medium used to store the desired information and that can be accessed by the computer.
  • communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and can include any information delivery media.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.
  • the embodiment of the invention can predict the next purchase time of the user according to the purchase record of the user, and remind the user to make a purchase or automatically place an order, thereby improving the user experience.

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Abstract

一种订单处理方法及设备，其中，所述方法包括：确定目标商品的标识信息和购买所述目标商品的用户的标识信息(S101)；根据所述目标商品的标识信息和所述购买所述目标商品的用户的标识信息，确定所述目标商品的下一次下单时间(S102)；当所述目标商品的下一次下单时间到达时，将所述目标商品自动下单或向所述用户发送购物提醒(S103)。

Description

一种订单处理方法及设备 技术领域
本文涉及但不限于计算机技术领域，尤其涉及一种订单处理方法及设备。
背景技术
购物，是每个人、每个家庭日常重要且必须的行为。不管是对于个人，还是对于家庭，大多数购物都是对于消耗品的购买，如油、盐、酱、醋、茶，如奶粉、洗衣液等等，这些消耗品需要近乎于周期性的去购买。然而，当以上消耗品在消耗殆尽之时，可能会忘记购买。
移动互联网时代，网上购物已经越来越方便、智能，当消耗品用完时，通常需要用户自主的在电商网站进行重复下单购买，或者定期(固定周期)购买。
发明内容
以下是对本文详细描述的主题的概述。本概述并非是为了限制权利要求的保护范围。
本发明实施例提供一种订单处理方法及设备。
本发明实施例的技术方案是这样实现的：
第一方面，本发明实施例提供一种订单处理方法，所述方法包括：
确定目标商品的标识信息和购买所述目标商品的用户的标识信息；
根据所述目标商品的标识信息和所述购买所述目标商品的用户的标识信息，确定所述目标商品的下一次下单时间；
当所述目标商品的下一次下单时间到达时，将所述目标商品自动下单或向所述用户发送购物提醒。
第二方面，本发明实施例提供一种订单处理设备，所述设备包括：
第一确定模块，设置为确定目标商品的标识信息和购买所述目标商品的用户的标识信息；
第二确定模块，设置为根据所述目标商品的标识信息和所述购买所述目标商品的用户的标识信息，确定所述目标商品的下一次下单时间；
下单模块，设置为当所述目标商品的下一次下单时间到达时，将所述目标商品自动下单或向所述用户发送购物提醒。
本发明实施例提供一种订单处理方法及设备，首先确定目标商品的标识信息和购买所述目标商品的用户的标识信息；然后根据所述目标商品的标识信息和所述购买所述目标商品的用户的标识信息，确定用户购买所述目标商品的购买记录，进而根据所述用户购买所述目标商品的购买记录确定所述目标商品的下一次下单时间；当达到所述目标商品的下一次下单时间时，将所述目标商品自动下单或向所述用户发送购物提醒。这样，能够根据用户的购买记录，预测出用户下一次的购买时间，并提醒用户进行购买或者自动下单，提升了用户体验。
在阅读并理解了附图和详细描述后，可以明白其他方面。
附图概述
图1为本发明实施例订单处理方法的实现流程示意图；
图2为本发明实施例又一订单处理方法的实现流程示意图；
图3为本发明实施例订单处理设备的组成结构示意图；
图4-1为本发明实施例又一订单处理方法的实现流程示意图；
图4-2为将商品加入智能购买清单的第二种实现方式的实现流程示意图；
图4-3为本发明实施例调整智能购买数据的实现流程示意图；
图4-4为本发明实施例计算商品的下次购买时间的时间轴示意图；
图4-5为本发明实施例出现用户随机购买的时间轴示意图；
图5为本发明实施例订单处理设备的组成结构示意图。
本发明的实施方式
下面将结合本发明实施例中的附图，对发明的具体技术方案做进一步详细描述。以下实施例用于说明本发明，但不用来限制本发明的范围。
当消耗品用完时，需要用户自主的在电商网站进行重复下单购买，或者定期(固定周期)购买，不能实现智能地、自动地预测用户商品用完，提醒用户补足或自动为其下单购买
本发明实施例提供一种订单处理方法，应用于订单处理设备，所述订单处理设备在实际应用中可以包括手机、平板电脑、笔记本电脑等终端。图1为本发明实施例订单处理方法的实现流程示意图，如图1所示，所述方法包括：
步骤S101，确定目标商品的标识信息和购买所述目标商品的用户的标识信息；
这里，订单处理列表中包括目标商品的标识信息、购买所述目标商品的用户的标识信息、所述目标商品的下一次下单时间和购买方式。比如所述目标商品的标识信息可以是商品编码，购买所述目标商品的用户的标识信息可以是用户识别码(Identification，ID)。
步骤S102，根据所述目标商品的标识信息和所述购买所述目标商品的用户的标识信息，确定所述目标商品的下一次下单时间；
这里，所述步骤S102包括：
步骤S102a，根据所述目标商品的标识信息和所述购买所述目标商品的用户的标识信息，确定所述用户购买所述目标商品的历史记录；
在本发明其他实施例中，所述用户购买所述目标商品的历史记录至少包括：所述用户购买所述目标商品的购买时间、购买数量及所述目标商品的规格。
步骤S102b，根据所述用户购买所述目标商品的历史记录，确定所述目标商品的下一次下单时间。
步骤S103，当所述目标商品的下一次下单时间到达时，将所述目标商 品自动下单或向所述用户发送购物提醒。
这里，步骤S103之前，所述方法还包括：判断所述目标商品的下一次下单时间是否到达。
在本发明其他实施例中，所述判断所述目标商品的下一次下单时间是否到达可以是通过消息触发的方式来实现的，也可以是通过轮询的方式来实现的。
如果所述判断所述目标商品的下一次下单时间是否到达是通过消息触发的方式来实现的，在实际的应用过程中，可以设定一个目标商品的下一次下单时间的消息定时时钟，当***时间到达所述消息定时时钟的时间时，会触发一个消息，这个消息用于表明到达所述目标商品的下一次下单时间。
如果所述判断所述目标商品的下一次下单时间是否到达是通过轮询的方式来实现的，在实际应用过程中，会开始定时查询任务(比如每天上午八点)查询所述目标商品的下一次下单时间是否到达。
预先设定的购买时间可以设定为所述目标商品的下一次下单时间是今天，也可以设定为所述目标商品的下一次下单时间提前N天，其中，N为大于或等于1的自然数。
在本发明实施例提供的订单处理方法中，首先确定目标商品的标识信息和购买所述目标商品的用户的标识信息；然后根据所述目标商品的标识信息和所述购买所述目标商品的用户的标识信息，确定用户购买所述目标商品的购买记录，进而根据所述用户购买所述目标商品的购买记录确定所述目标商品的下一次下单时间；当达到所述目标商品的下一次下单时间时，将所述目标商品自动下单或向所述用户发送购物提醒。这样，能够根据用户的购买记录，预测出用户下一次的购买时间，并提醒用户进行购买或者自动下单，提升了用户体验。
基于前述的实施例，本发明实施例再提供一种订单处理方法，应用于订单处理设备。图2为本发明实施例又一订单处理方法的实现流程示意图，如图2所示，所述方法包括：
步骤S201，订单处理设备判断用户已购买的商品的标识信息是否在订 单处理列表中。
这里，所述订单处理设备可以是智能手机、平板电脑、笔记本电脑、台式计算机等电子设备。
当商品购买结束后，所述订单处理设备判断用户已购买的商品的标识信息是否在订单处理列表中，如果已购买的商品的标识信息在订单处理列表中，则进入步骤S204，如果已购买的商品的标识信息不在订单处理列表中，则进入步骤S202。
比如，用户ID为123的用户购买了一桶商品编码为HS456的花生油，购买结束后，所述订单处理设备判断HS456是否在订单处理列表中。
步骤S202，如果所述用户已购买的商品的标识信息不在订单处理列表中，所述订单处理设备判断所述用户购买所述已购买的商品的次数是否达到预设的阈值。
这里，如果所述用户购买所述已购买的商品的次数达到预设的阈值，则进入步骤S203，如果所述用户购买所述已购买的商品的次数没有达到预设的阈值，流程结束。
如果所述用户已购买商品的标识信息不在所述订单处理列表中，根据已购买商品的标识信息以及所述用户的标识信息，确定所述用户购买所述已购买商品的历史记录，然后再根据所述用户购买所述已购买商品的历史记录，确定所述用户购买所述已购买商品的次数，进而判断所述用户购买所述已购买商品的次数是否达到预设的阈值。
比如，商品编码HS456不在订单处理列表中，则所述订单处理设备查询用户ID123的历史记录，计算所述用户购买商品编码为HS456的商品的次数，并判断所述用户购买商品编码为HS456的商品的次数是否达到预设的阈值，比如预设的阈值为5。
步骤S203，如果所述已购买的商品的购买次数达到预设的阈值，则所述订单处理设备将所述用户已购买的商品的标识信息和所述用户的标识信息添加至所述订单处理列表。
这里，比如用户ID为123的用户购买商品编码为HS456的花生油的次 数达到了5次，则将用户ID123和商品编码HS456添加至所述订单处理列表中。
步骤S204，所述订单处理设备根据所述已购买商品的标识信息和所述用户的标识信息，确定所述用户购买所述已购买商品的历史记录；
这里，因为已购买商品加入到了订单处理列表中，所述本发明实施里中已购买商品也就是在本发明其他实施里中的目标商品。
步骤S205，所述订单处理设备根据所述用户购买所述已购买商品的历史记录，确定所述目标商品的下一次下单时间。
这里，根据所述用户购买所述已购买商品的历史记录，确定所述已购买商品的下一次下单时间本发明实施例给出示例性的几种计算方法。
第一种计算方法：根据所述已购买商品的平均消耗速度确定所述已购买商品的下一次下单时间，包括以下步骤：
步骤S2051a，根据所述用户购买所述已购买商品的历史记录，确认所述用户第一次购买所述已购买商品到第n次购买所述已购买商品的购买信息；
这里，第n次购买所述已购买商品的购买信息为最近一次购买所述已购买商品的购买信息，第i次购买所述已购买商品的购买信息为购买时间t i，购买数量n i和所述已购买商品的规格s i，i为1到n之间的自然数；
步骤S2051b，根据所述用户第一次购买所述已购买商品到第n次购买所述已购买商品的购买信息确定t 1到t n之间所述已购买商品的平均消耗速度V’；
这里，根据所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息确定t 1到t n之间所述目标商品的购买总量；根据t 1到t n之间所述目标商品的购买总量和t 1到t n之间的时间差确定t 1到t n之间所述目标商品的平均消耗速度V’。
在实际应用中可以按照公式(2-1)确定t 1到t n之间所述已购买商品的平均消耗速度V’。
Figure PCTCN2018072272-appb-000001
其中，在公式(2-1)中，t i为第i次购买所述已购买商品的购买时间，n i为第i次购买所述已购买商品的购买数量，s i为第i次购买所述已购买商品的规格，i＝1,2，……，n。
步骤S2051c，根据所述已购买商品的平均消耗速度以及第n次购买所述目标商品的购买信息确定所述已购买商品的下一次下单时间。
这里，根据所述目标商品的平均速度以及第n次购买所述目标商品的购买信息确定第n次购买的所述目标商品的使用时长；再根据第n次购买所述目标商品的购买时间和第n次购买的所述目标商品的使用时长确定所述目标商品的下一次下单时间。
用v n表示第n次购买所述已购买商品的时间t n到第n+1次购买所述已购买商品的时间t n+1之间消耗了n ns n的速度，则v n可以由公式(2-2)得到。
Figure PCTCN2018072272-appb-000002
其中，在公式(2-2)中，n n为第n次购买所述已购买商品的购买数量，s n为第n次购买所述已购买商品的规格。
由公式(2-2)可以得到计算t n+1的公式(2-3)：
Figure PCTCN2018072272-appb-000003
以平均速度V’作为v n，即v n＝V'，则有公式(2-4)：
Figure PCTCN2018072272-appb-000004
第二种计算方法：根据所述t 1到t n-1之间消耗所述已购买商品的平均速度V’和t 1到t n之间消耗所述已购买商品的平均加速度，确定所述已购买商品的下次购买时间，包括以下步骤：
步骤S2052a，根据所述用户购买所述已购买商品的历史记录，确认所述用户第一次购买所述已购买商品到第n次购买所述已购买商品的购买信息；
这里，第n次购买所述已购买商品的购买信息为最近一次购买所述已购买商品的购买信息，第i次购买所述已购买商品的购买信息为购买时间t i，购买数量n i和所述已购买商品的规格s i，i为1到n之间的自然数；
步骤S2052b，根据所述用户第一次购买所述已购买商品到第n次购买所述已购买商品的购买信息确定t 1到t n-1之间消耗所述已购买商品的平均速度V’和t 1到t n之间消耗所述已购买商品的平均加速度；
这里，按照公式(2-5)确定t 1到t n-1之间消耗所述已购买商品的平均速度V’。
Figure PCTCN2018072272-appb-000005
按照公式(2-6)确定t 1到t 2之间所述目标商品的平均消耗速度v 1；
Figure PCTCN2018072272-appb-000006
按照公式(2-7)确定t 1到t n之间所述目标商品的平均消耗速度v n-1；
Figure PCTCN2018072272-appb-000007
按照公式(2-8)确定t 1到t n之间消耗所述目标商品的平均加速度。
Figure PCTCN2018072272-appb-000008
步骤S2052c，根据所述t 1到t n-1之间消耗所述已购买商品的平均速度V’和t 1到t n之间消耗所述已购买商品的平均加速度，确定所述已购买商品的下次购买时间。
这里，由公式(2-2)，可以得到公式(2-9)
Figure PCTCN2018072272-appb-000009
令Δt＝t n+1-t n，则由v n＝v n-1+aΔt和公式(2-9)可以得到公式(2-10)
Figure PCTCN2018072272-appb-000010
将公式(2-10)进行整理变换，得到公式(2-11)
aΔt 2+v n-1Δt-n ns n＝0  (2-11)；
将t 1到t n-1之间消耗所述已购买商品的平均速度V’作为v n-1带入公式(2-11)，对公式(2-11)进行一元二次方程求解可得出Δt，再根据公式(2-12)，确定所述已购买商品下一次下单时间t n+1。若无解，可以采用第一种计算方法确定所述已购买商品下一次下单时间t n+1。
t n+1＝t n+Δt  (2-12)；
第三种计算方法：根据所述t 1到t n之间消耗所述已购买商品的平均加速度和t n-1到t n之间所述商品的消耗速度v n-1，确定所述已购买商品的下次购买时间，包括以下步骤：
步骤S2053a，根据所述用户购买所述已购买商品的历史记录，确认所述用户第一次购买所述已购买商品到第n次购买所述已购买商品的购买信息；
这里，第n次购买所述已购买商品的购买信息为最近一次购买所述已购买商品的购买信息，第i次购买所述已购买商品的购买信息为购买时间t i，购买数量n i和所述已购买商品的规格s i，i为1到n之间的自然数；
步骤S2053b，根据所述用户第一次购买所述已购买商品到第n次购买所述已购买商品的购买信息确定t 1到t n之间消耗所述已购买商品的平均加速度和t n-1到t n之间所述商品的消耗速度v n-1；
这里，根据公式(2-7)确定t n-1到t n之间所述商品的消耗速度v n-1，根据公式(2-6)、(2-7)和(2-8)确定t 1到t n之间消耗所述已购买商品的平均加速度。
步骤S2054c，根据所述t 1到t n之间消耗所述已购买商品的平均加速度和t n-1到t n之间所述商品的消耗速度v n-1，确定所述已购买商品的下次购买时间。
这里，公式(2-7)代入公式(2-11)，对公式(2-11)进行一元二次方程求解可得出Δt，再根据公式(2-12)，确定所述已购买商品下一次下单时间t n+1。若无解，可以采用第一种计算方法确定所述已购买商品下一次下单时间t n+1。
步骤S206，所述订单处理设备判断是否到达所述已购买商品的下一次下单时间。
步骤S207，如果所述已购买商品的下一次下单时间到达时，则所述订单处理设备确定所述用户设定的购买方式；
步骤S208，所述订单处理设备根据所述用户设定的购买方式进行购买。
需要说明的是，本实施例中与其它实施例中相同步骤或概念的解释可以参考其它实施例中的描述，此处不再赘述。
在本发明实施例提供的订单处理方法中，首先确定目标商品的标识信息和购买所述目标商品的用户的标识信息；然后根据所述目标商品的标识信息和所述购买所述目标商品的用户的标识信息，确定用户购买所述目标商品的购买记录，进而根据所述用户购买所述目标商品的购买记录确定所述目标商品的下一次下单时间；当达到所述目标商品的下一次下单时间时，根据用户设置的购买方式，将所述目标商品自动下单或向所述用户发送购物提醒。这样，能够根据用户的购买记录，预测出用户下一次的购买时间，并提醒用户进行购买或者自动下单，提升了用户体验。
基于前述的实施例，本发明实施例再提供一种订单处理方法，应用于一种订单处理设备。在本发明实施例中，用户购买的目标商品的标识信息已经存在订单处理列表中，且已经计算出所述目标商品的下一次购买时间。本发明实施例提供的订单处理方法包括以下步骤：
第一步，订单处理设备判断所述用户最近一次购买所述目标商品的时间是否早于订单处理列表中所述目标商品的下一次购买时间；如果所述用户最 近一次购买所述目标商品的时间早于订单处理列表中所述目标商品的下一次购买时间，则进入第二步，如果所述用户最近一次购买所述目标商品的时间不早于订单处理列表中所述目标商品的下一次购买时间，流程结束。
这里，因为当有各种节日的时候，商品可能会打折，用户可能还没到所述目标商品的下一次购买时间就购买了，这时需要更新订单处理列表中所述目标商品的下一次购买时间。
第二步，如果所述用户最近一次购买所述商品的时间早于订单处理列表中所述目标商品的下一次购买时间，根据所述用户购买所述目标商品的历史记录，确定在所述用户最近一次购买所述商品的购买时间之前所述目标商品的剩余量；
这里，按照公式(3-1)确定在所述用户最近一次购买所述商品的时间之前所述目标商品的剩余量。
m＝v n-1(t' n-t n)  (3-1)；
在公式(3-1)中，m为在所述用户最近一次购买所述商品的购买时间之前所述目标商品的剩余量，v n- 1为t n-1到t’ n之间所述商品的消耗速度，t n-1为所述用户第n-1次购买所述目标商品的时间，t’ n为订单处理列表中所述目标的下一次购买时间，t n为所述用户最近一次购买所述目标商品的时间。
第三步，根据所述目标商品的剩余量和所述用户购买所述目标商品的历史记录，更新所述目标商品的下一次购买时间。
这里，按照公式(3-2)计算出所述目标商品的下一次购买时间，并更新所述订单处理列表中所述目标商品的下一次购买时间。
Figure PCTCN2018072272-appb-000011
将根据公式(2-1)计算得到的平均速度V’作为v n，代入公式(3-2)即可计算出t n+1。
在本发明的其他实施例中，也可以根据前述实施例提供的第二种计算方法或第三种计算方法计算当用户在订单处理列表中目标商品的下一次购买时间之前购买了目标商品时所述目标商品的下一次购买时间。
在本发明实施例提供的订单处理方法中，针对用户在目标商品的下一次购买时间之间进行了购买时，对订单处理列表中的所述目标商品的下一次购买时间进行重新计算并更新，这样，可以更准确地预测出用户下一次的购买时间。
本发明实施例提供一种订单处理设备，图3为本发明实施例订单处理设备的组成结构示意图，如图3所示，所述订单处理设备包括：数据模块301、设置模块302、智能决策购买模块303、提醒模块304和下单购买模块305，其中：
所述数据模块301，设置为提供数据支撑。
这里，所述数据模块中存储的数据至少包含：
1)商品信息
所述商品信息包括商品编码、商品识别码和商品其他信息。所述商品信息通常以如下的表格方式存储。
商品编码 商品识别码 商品规格 其他信息
商品编码：为商品在***内的编码，唯一识别一个商品。如，品牌一1千克(kilogram，kg)装洗衣液，编码为100001，品牌二2kg装洗衣液，编码为100002。
商品识别码：为商品在***内的类别识别码，唯一表示一个商品类型的编码，是商品可被同类其他品牌可替代的标志。如，品牌一1kg装洗衣液，商品识别码为XYY01，品牌二2kg装洗衣液，商品识别码也为XYY01，在智能购买时，可作为同一类商品相互替代。可使用官方HS编码，也可***自定义。
商品规格：商品的包装规格，如500克(gram，g)，1kg，52片，500毫升(milliliter，ml)，1升(Liter，L)。
其值舍去单位，如500ml，500g，24片的商品规格为500，500，24。我们假设同类商品(同一商品识别码，如洗衣液)基本采用相同的规格单位，如洗衣液，不会存在一个牌子用克做单位，另一个牌子用毫升做单位。这个假设是基本成立的。即使存在，在记录商品信息时，也可以对其规格进行换 算(如容量也可以根据密度算出其重量)，在同一个***内为同类商品指定一个相同单位的规格。
商品的其他信息包含价格、库存等信息，不做限制。
2)历史订单信息
所述历史订单信息包含用户识别码，所购买的商品信息，商品数量，和订单时间等信息。所述历史订单信息通常以如下的表格方式存储。
订单号 商品编码 用户识别码 数量 订单时间
订单号：每个订单的编号。
商品编码与商品信息中的商品编码表征的意义相同。
用户识别码：唯一标识一个用户，可以为USER_ID。
数量：是指在这个订单内该商品的购买个数。
订单时间：为购买商品的日期及时间。
3)用户智能购买清单
所述用户智能购买清单包括用户识别码，商品识别码，商品编码，消耗速度，可能库存量，下次购买时间。所述用户智能购买清单通常以如下的表格方式存储。
用户识别码 商品识别码 商品编码 下次购买时间 购买方式
商品识别码、商品编码、用户识别码分别与历史订单信息中的商品识别码、商品编码、用户识别码表征的意义相同。
下次购买时间：预估用户需要在该时间补足商品，用于为用户智能提醒或购买。
购买方式：可以为“自动加入购物车并提醒用户”或“自动下单购买”，本发明实施例不限定或可做扩展。
用户智能购买清单可以是一个表，也可以是多个表。
用户智能购买清单记录用户购买某一种商品(如洗衣液)的智能购买数据。如：
1234 XYY01 100001、100002 2016-12-12 02
可以表示为编号为1234的用户需要智能购买洗衣液，其曾购买过品牌一1kg装洗衣液(编码为100001)和品牌二2kg装洗衣液(编码为100002)，下一次为其智能购买的时间为2016年12月12号，购买方式为自动下单购买(02)。
所述设置模块302，设置为设置智能购买清单中的购买方式或者将用户选择的商品加入智能购买清单或者将用户选择的商品从智能购买清单中删除。
1)允许用户将某商品加入智能购买
对于用户经常购买的商品，***可提供将该商品加入智能购买的入口，用户操作后，将该商品数据加入数据模块中的“用户智能购买清单。
2)允许用户将某商品取消智能购买
对于已加入智能购买的常购商品，***提供将该商品移除智能购买的入口，用户操作后，将该商品数据移除数据模块中的“用户智能购买清单”。
3)允许用户选择单个商品或者所有可智能购买商品的购买方式：可选的，可以为提醒购买(自动加入购物车，短信、信息或邮件等方式提醒通知)，自动下单购买(直接下单)。
A)当用户“将商品加入智能购买”时，可指定智能购买时的购买方式是提醒还是自动下单购买。
B)***也可以提供为所有智能购买商品设置购买方式的入口，设置后，所有智能购买采用统一方式。
所述智能决策购买模块303，设置为判断商品是否达到智能购买时机，时机到，则根据用户在设置模块设置的智能购买方式或***中“用户智能购买清单”中“购买方式”，为用户将商品自动加入购物车并进行短信、信息或邮件等方式的通知，或自动下单购买。
可以以消息触发的方式，也可以以轮询的方式执行到期智能购买。
以轮询的方式为例，可以以开启定时任务的方式(如每天00:00点)， 为“用户智能购买清单”中的每个用户决策其智能购买商品是否符合时机，本发明不做限制。
符合时机的条件可以是“下次购买时间”是今天，也可以是提前N天为用户提醒或购买，本发明实施例中不做限制。
所述提醒模块304，设置为为用户将到期智能购买的商品自动加入购物车，并进行短信、信息或邮件等方式的通知。通知也可以附加推荐。
所述下单购买模块305，设置为为购买某商品生成订单，并完成订单后续流程。电商***中常规模块。
本发明实施例再提供一种订单处理方法，应用于订单处理设备，图4-1为本发明实施例订单处理方法的实现流程示意图，如图4-1所示，所述方法包括：
步骤S401，将商品加入智能购买清单。
这里，将商品加入智能购买清单为将商品的商品识别码添加到智能购买清单，在本发明实施例中，步骤S401可以通过以下两种方式实现：
第一种实现方式，根据用户基于订单处理设备提前为给常购商品提供的入口上的操作(可仅向常购商品提供该入口)，将某商品加入智能购买清单。
第二种实现方式，当商品购买结束后，根据商品的购买信息将商品加入智能购买清单。
这里，图4-2为将商品加入智能购买清单的第二种实现方式的实现流程示意图，如图4-2所示包括以下步骤：
步骤S421，判断所述商品是否购买结束。
这里，如果所述商品购买结束则进入步骤S422，如果所述商品没有购买结束则结束本流程。
步骤S422，判断所述商品的商品识别码是否存在所述智能购买清单中。
这里，如果所述商品的商品识别码存在所述智能购买清单中则进入步骤S402，如果所述商品的商品识别码不存在所述智能购买清单中，则进入步骤S423。
步骤S423，判断所述商品的购买次数是否大于预设的阈值。
这里，当所述商品的商品识别码不存在所述智能购买清单中，则根据所述商品的商品识别码和购买所述商品的用户的用户识别码，查找所述用户购买所述商品的历史记录，判断所述商品的购买次数是否大于预设的阈值N，如果所述商品的购买次数大于预设的阈值N，则进入步骤S424，如果所述商品的购买次数不大于预设的阈值，则结束流程。
也就是说，若所述商品是普通购买(商品识别码不在智能购买清单)，则根据预设的规则，将商品自动加入智能购买清单；若所述商品是智能购买(商品识别码在智能购买清单)，则直接调整智能购买数据。商品自动加入购买的规则为“历史购买次数大于N次”，N***自定义。
步骤S424，将所述商品加入智能购买清单。
步骤S402，调整智能购买数据。
这里，图4-3为本发明实施例调整智能购买数据的实现流程示意图，如图4-3所示，所述步骤S402调整智能购买数据包括：
步骤S402a，判断添加的商品的商品识别码是否存在于智能购买清单中。
这里，本发明实施例中的智能购买清单与本发明其他实施例中的订单处理列表存储的内容及作用相同。
如果所述商品的商品识别码存在于智能购买清单中则进入步骤S402c，如果所述商品的商品识别码不存在于智能购买清单中则进入步骤S402b。
如果步骤S401是通过第一种实现方式实现的，则直接添加商品识别码和商品编码至智能购买清单，并计算和设置智能购买清单数据。
步骤S402b，将所述商品的商品识别码添加至智能购买清单。
这里，比如购买品牌一洗衣液后，若智能清单中不存在该商品识别码，即没购买过该类商品(如，没买过洗衣液)，则将商品识别码和商品加入智能购买清单中，计算并重置智能购买数据。
步骤S402c，判断所述商品的商品编码是否存在于智能购买清单中。
这里，如果所述商品的商品编码存在于智能购买清单中，则进入步骤 S402e，如果所述商品的商品编码不存在于智能购买清单中，则进入步骤S402d。
也就是说，比如购买品牌一洗衣液后，若智能清单中存在该商品识别码，即购买过该类商品(如，买过洗衣液)，如果智能购买清单中不存在该商品的商品编码(品牌一洗衣液)，则将该商品的商品编码加入智能购买清单中(之前购买的可能是品牌二洗衣液)。如果智能购买清单中如果已存在该商品的商品编码，则进入步骤S402e计算并重置智能购买数据。
步骤S402d，将所述商品的商品编码添加至智能购买清单。
步骤S402e，计算并重置智能购买数据，特别是下次购买时间。本发明实施例推荐一种方法，但不限定。
本发明实施例中的下次购买时间与其他实施例中的下一次下单时间相同。
图4-4为本发明实施例计算商品的下次购买时间的时间轴示意图，为了便于理解，首先对图4-4中的标识进行说明。
t表示购买时间，也就是某一次购买的时间。
n表示购买数量，也就是某一次所购商品的数量。
s表示所购商品的规格。
以上数据均有数据模块作为支撑获得。
如图4-4所示，t 1，n 1，s 1分别为某种商品第一次购买的时间，数量和商品规格；t n，n n，s n分别为某种商品第n次购买的时间，数量和商品规格。
T为时间区间，T1为第二次购买和第一次购买的时间区间，Tn-1为第n次购买和第n-1次购买的时间区间。
这里，引入速度和加速度的概念。
速度v，为用户对商品的消耗速度。
加速度a，是描述速度变化快慢的物理量，a＝Δv/Δt，本发明实施例采用平均加速度。
v为对商品的消耗速度，具体为
Figure PCTCN2018072272-appb-000012
也即在时间t内，消耗了n个s 规格的商品，v n为第n次到第n+1次购买之间消耗了n ns n的速度，由公式(4-1)计算得到；v n-1为第n-1次到第n次购买之间消耗了n n-1s n-1的速度，由公式(4-2)计算得到。
Figure PCTCN2018072272-appb-000013
Figure PCTCN2018072272-appb-000014
按照公式(4-3)确定t 1至t n之间购买该类商品的平均速度：
Figure PCTCN2018072272-appb-000015
按照公式(4-4)确定平均加速度：
Figure PCTCN2018072272-appb-000016
将公式(4-1)和公式(4-2)代入到公式(4-4)得到公式(4-5)，也即：
Figure PCTCN2018072272-appb-000017
现在需要计算的是，第n+1次购买时间t n+1，可以采用如下方法：
1)根据平均速度来计算t n+1。
以平均速度V’作为v n，即令v n＝V'，那么将公式(4-1)进行变换，得到公式(4-6)：
Figure PCTCN2018072272-appb-000018
令v n＝V'，再将公式(4-3)代入到公式(4-6)得到公式(4-7)：
Figure PCTCN2018072272-appb-000019
这里，在公式(4-7)中，所有的参数都是已知数，通过公式(4-7)即可确定商品的第n+1次购买时间。
2)根据平均速度和平均加速度，计算t n+1。
令Δt＝t n+1-t n，公式(4-6)可以变换为公式(4-8)：
Figure PCTCN2018072272-appb-000020
将公式(4-9)代入公式(4-8)，得到公式(4-10)：
v n＝v n-1+aΔt(4-9)；
Figure PCTCN2018072272-appb-000021
将公式(4-10)进行变换得到公式(4-11)：
aΔt 2+v n-1Δt-n ns n＝0  (4-11)；
按照公式(4-12)确定t 1到t n-1之间消耗所述已购买商品的平均速度V’。
Figure PCTCN2018072272-appb-000022
将t 1到t n-1之间消耗所述已购买商品的平均速度V’作为v n-1带入公式(4-11)，对公式(4-11)进行一元二次方程求解可得出Δt，再根据公式(4-13)，确定所述已购买商品下一次购买时间t n+1。若无解，可以采用第一种计算方法确定所述已购买商品下一次购买时间t n+1。
t n+1＝t n+Δt  (4-13)。
3)根据瞬时速度和平均加速度，计算t n+1
将公式(4-2)代入到公式(4-11)对公式(4-11)进行一元二次方程求解可得出Δt，再根据公式(4-13)，确定所述已购买商品下一次购买时间t n+1。若无解，可以采用第一种计算方法确定所述已购买商品下一次购买时间t n+1。
为了解决用户某次随机购买(即在智能购买时间到达之前的一次购买，如商品打折，用户主动执行了购买)对智能购买的带来的影响，可采用如下方法。图4-5中，第n次购买为一个在其智能购买时间t n'到来之前的随机购买。
在智能购买t n'到来之前，用户自行执行了一次随机购买t n。其判断条件可以为购买时间t n早于***计算的下一次购买时间t n'M天且商品为打折促销中，M可***自定义，如半个月或其他。
此种情况下，可认为t n时刻用户拥有该商品的余量m可以由公式(4-14)得到：
m＝v n-1Δt＝v n-1(t' n-t n)  (4-14)；
则，t n+1的计算方法，以平均速度V’作为v n(v n＝V')为例，计算如下：
Figure PCTCN2018072272-appb-000023
则
Figure PCTCN2018072272-appb-000024
同理，采用相同的思路计算出以平均加速度和瞬时速度的t n+1。
同时，也可得出n越大，v越平稳，则智能购买时间计算的准确度越大的结论。
步骤S403，到期执行智能购买。
这里，步骤S403即为本发明其他实施例中智能决策购买模块所执行的功能，判断商品是否达到智能购买时机，如果所述商品的购买时机达到，则根据用户在设置模块设置的智能购买方式或***中“用户智能购买清单”中“购买方式”，为用户将商品自动加入购物车并进行短信、信息或邮件等方 式的通知，或自动下单购买。同时也可以做推荐。
在本发明其他实施例中，可以以消息触发的方式也可以以轮询的方式执行到期智能购买。
以轮询的方式为例，可以以开启定时任务的方式(如每天00:00点)，为“用户智能购买清单”中的每个用户决策其智能购买商品是否符合时机，符合时机的条件可以是“下次购买时间”是今天，也可以是提前N天为用户提醒或购买，本发明不做限制。
另外，同一商品识别码(同一类商品，如洗衣液)的智能购买中，可能存在多次购买品牌A和多次购买品牌B的情况，做智能购买时，***可自动购买A也可自动购买B，也可根据一定的规则(购买次数多的，或者最近购买的)选择购买哪个商品。
在本发明实施例中，通过对用户经常购买的商品，通过对用户购买商品的时间、数量、规格(容量、重量等)进行分析，动态地计算并预测其商品用完时间(即下次购买时间)，到期自动提醒或自动购买，达到及时为用户补足供给的目的。
基于前述的实施例，本发明实施例提供一种订单处理方法，应用于一种订单处理设备，其中，所述方法包括以下步骤：
第一步，同一种商品购买5次后，订单处理设备提供将商品加入智能购买的入口。用户点击该入口，并设置所述商品的智能购买方式为“购买提醒”
第二步，所述订单处理设备直接添加商品识别码和商品编码至智能购买清单，并计算和设置其下一次智能购买的时间。
这里，所述订单处理设备按照本发明其他实施例中提供的方法计算所述商品的下一次智能购买时间。
第三步，所述订单处理设备智能决策购买，当所述订单处理设备确认到达该商品的智能购买时间时，则根据用户的设置，将该商品加入购物车，并进行信息或邮件等方式的提醒，同时，也可以进行同类商品推荐。
采用本发明实施例中提供的智能购买方法，可以为用户自动补充供给，为用户省心省力。同时，也避免因忘记购买而无东西可用的情况。
基于前述的实施例，本发明实施例再提供一种订单处理方法，应用于一种订单处理设备，所述方法包括以下步骤：
第一步，同一种商品购买5次后，订单处理设备自动将商品加入智能购买清单。
这里，所述订单处理设备自动将商品加入智能购买清单包括所述订单处理设备至少将所述商品的商品识别码和商品编码加入智能购买清单。
第二步，所述订单处理设备添加商品识别码和商品编码至智能购买清单后，计算和设置其下一次智能购买时间。
这里，所述订单处理设备按照本发明其他实施例中提供的方法计算所述商品的下一次智能购买时间。
第三步，所述订单处理设备智能决策购买，当所述订单处理设备确定到达到该商品的智能购买时间时，则根据用户在订单处理设备的***中的统一设置(比如，用户设置为自动购买)，为商品生成订单，自动为用户购买，支付方式可以为货到付款或者用户在***中设置的自动扣款等。
本发明实施例再提供一种订单处理方法，应用于一种购物设备。所述方法包括以下步骤：
第一步，订单处理设备执行一次智能购买，智能购买商品结束。
第二步，所述订单处理设备计算和设置所述商品的下一次智能购买的时间。
这里，所述订单处理设备按照本发明其他实施例中提供的方法计算所述商品的下一次智能购买时间。
第三步，所述智能订单处理设备进行智能决策购买，当确认到达该商品的智能购买时间时，则根据用户在***中的统一设置(比如，用户设备为提醒购买)，将商品加入购物车，并进行信息或邮件等方式的提醒，同时，也可以进行同类商品推荐。
本发明实施例提供一种订单处理设备，图5为本发明实施例订单处理设备的组成结构示意图，如图5所示，所述订单处理设备500包括：第一确定模块501、第二确定模块502和下单模块503，其中：
所述第一确定模块501，设置为确定目标商品的标识信息和购买所述目标商品的用户的标识信息；
所述第二确定模块502，设置为根据所述目标商品的标识信息和所述购买所述目标商品的用户的标识信息，确定所述目标商品的下一次购买时间；
这里，所述第二确定模块502包括：
第一确定单元，设置为根据所述目标商品的标识信息和所述购买所述目标商品的用户的标识信息，确定所述用户购买所述目标商品的历史记录；
第二确定单元，设置为根据所述用户购买所述目标商品的历史记录，确定所述目标商品的下一次购买时间。
这里，所述第二确定单元包括：
第一确定子单元，设置为根据所述用户购买所述目标商品的历史记录，确定所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息；其中，第n次购买所述目标商品的购买信息为最近一次购买所述目标商品的购买信息，第i次购买所述目标商品的购买信息为购买时间t i，购买数量n i和所述目标商品的规格s i，i为1到n之间的自然数；
第二确定子单元，设置为根据所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息确定t 1到t n之间所述目标商品的平均消耗速度V’；
第三确定子单元，设置为根据所述目标商品的平均消耗速度确定所述目标商品的下一次购买时间。
第四确定子单元，设置为根据所述用户购买所述目标商品的历史记录，确定所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息；其中，第n次购买所述目标商品的购买信息为最近一次购买所述目标商品的购买信息，第i次购买所述目标商品的购买信息为购买时间t i，购买数量n i和所述目标商品的规格s i，i为1到n之间的自然数；
第五确定子单元，设置为根据所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息确定t 1到t n-1之间消耗所述目标商品的平均速度V’和t 1到t n之间消耗所述目标商品的平均加速度；
第六确定子单元，设置为根据所述t 1到t n-1之间消耗所述目标商品的平均速度V’和t 1到t n之间消耗所述目标商品的平均加速度，确定所述目标商品的下次购买时间。
第七确定子单元，设置为根据所述用户购买所述目标商品的历史记录，确认所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息；其中，第n次购买所述目标商品的购买信息为最近一次购买所述目标商品的购买信息，第i次购买所述目标商品的购买信息为购买时间t i，购买数量n i和所述目标商品的规格s i，i为1到n之间的自然数；
第八确定子单元，设置为根据所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息确定t 1到t n之间消耗所述目标商品的平均加速度和t n-1到t n之间所述商品的消耗速度v n-1；
第九确定子单元，设置为根据所述t 1到t n之间消耗所述目标商品的平均加速度和t n-1到t n之间所述商品的消耗速度v n-1，确定所述目标商品的下次购买时间。
所述下单模块503，设置为当所述目标商品的下一次购买时间到达时，将所述目标商品自动下单或向所述用户发送购物提醒。
这里，所述订单处理设备还包括：
第一判断模块，设置为判断已购买的商品的标识信息是否在订单处理列表中；
第二判断模块，设置为如果所述已购买的商品的标识信息不在订单处理列表中，判断所述已购买的商品的购买次数是否达到预设的阈值；
添加模块，设置为如果所述已购买的商品的购买次数达到预设的阈值，则将所述已购买的商品的标识信息添加至订单处理列表。
第三判断模块，设置为判断所述用户最近一次购买所述商品的购买时间是否早于订单处理列表中所述目标商品的下一次购买时间；
第三确定模块，设置为如果所述用户最近一次购买所述商品的购买时间早于订单处理列表中所述目标商品的下一次购买时间，根据所述用户购买所述目标商品的历史记录，确定在所述用户最近一次购买所述商品的购买时间 之前所述目标商品的剩余量；
更新模块，设置为根据所述目标商品的剩余量和所述用户购买所述目标商品的历史记录，更新所述目标商品的下一次购买时间。
这里需要指出的是：以上订单处理设备实施例的描述，与上述方法实施例的描述是类似的，具有同方法实施例相似的有益效果，因此不做赘述。对于本发明订单处理设备实施例中未披露的技术细节，请参照本发明方法实施例的描述而理解，为节约篇幅，因此不再赘述。
本发明实施例还提供了一种计算机可读存储介质，存储有计算机可执行指令，所述计算机可执行指令被处理器执行时实现上述实施例所述的方法。
本领域普通技术人员可以理解，上文中所公开方法中的全部或某些步骤、***、装置中的功能模块/单元可以被实施为软件、固件、硬件及其适当的组合。在硬件实施方式中，在以上描述中提及的功能模块/单元之间的划分不一定对应于物理单元的划分；例如，一个物理组件可以具有多个功能，或者一个功能或步骤可以由若干物理组件合作执行。某些组件或所有组件可以被实施为由处理器，如数字信号处理器或微处理器执行的软件，或者被实施为硬件，或者被实施为集成电路，如专用集成电路。这样的软件可以分布在计算机可读介质上，计算机可读介质可以包括计算机存储介质(或非暂时性介质)和通信介质(或暂时性介质)。如本领域普通技术人员公知的，术语计算机存储介质包括用于存储信息(诸如计算机可读指令、数据结构、程序模块或其他数据)的任何方法或技术中实施的易失性和非易失性、可移除和不可移除介质。计算机存储介质包括但不限于RAM、ROM、EEPROM、闪存或其他存储器技术、CD-ROM、数字多功能盘(DVD)或其他光盘存储、磁盒、磁带、磁盘存储或其他磁存储装置、或者可以用于存储期望的信息并且可以被计算机访问的任何其他的介质。此外，本领域技术人员公知的是，通信介质通常包含计算机可读指令、数据结构、程序模块或者诸如载波或其他传输机制之类的调制数据信号中的其他数据，并且可包括任何信息递送介质。
本发明是参照根据本发明实施例的方法、设备(***)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
以上所述，仅为本发明的可选实施例而已，并非用于限定本发明的保护范围。
工业实用性
本发明实施例能够根据用户的购买记录，预测出用户下一次的购买时间，并提醒用户进行购买或者自动下单，提升了用户体验。

Claims (11)

  1. 一种订单处理方法，所述方法包括：
    确定目标商品的标识信息和购买所述目标商品的用户的标识信息(S101)；
    根据所述目标商品的标识信息和所述购买所述目标商品的用户的标识信息，确定所述目标商品的下一次下单时间(S102)；
    当所述目标商品的下一次下单时间到达时，将所述目标商品自动下单或向所述用户发送购物提醒(S103)。
  2. 根据权利要求1中所述的方法，其中，所述根据所述目标商品的标识信息和所述购买所述目标商品的用户的标识信息，确定所述目标商品的下一次下单时间，包括：
    根据所述目标商品的标识信息和所述购买所述目标商品的用户的标识信息，确定所述用户购买所述目标商品的历史记录；
    根据所述用户购买所述目标商品的历史记录，确定所述目标商品的下一次下单时间。
  3. 根据权利要求1中所述的方法，所述方法还包括：
    在所述确定目标商品的标识信息和购买所述目标商品的用户的标识信息之前，判断已购买的商品的标识信息是否在订单处理列表中；
    如果所述已购买的商品的标识信息不在所述订单处理列表中，判断所述已购买的商品的购买次数是否达到预设的阈值；
    如果所述已购买的商品的购买次数达到预设的阈值，则将所述已购买的商品的标识信息添加至所述订单处理列表。
  4. 根据权利要求2中所述的方法，其中，所述根据所述用户购买所述目标商品的历史记录，确定所述目标商品的下一次下单时间，包括：
    根据所述用户购买所述目标商品的历史记录，确认所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息；其中，第n次购买所述目标商品的购买信息为最近一次购买所述目标商品的购买信息；
    根据所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息确定第一次购买所述目标商品到第n次购买所述目标商品之间所述目标商品的平均消耗速度；
    根据所述目标商品的平均消耗速度以及第n次购买所述目标商品的购买信息确定所述目标商品的下一次下单时间。
  5. 根据权利要求4中所述的方法，其中，所述根据所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息确定第一次购买所述目标商品到第n次购买所述目标商品之间所述目标商品的平均消耗速度，包括：
    根据所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息确定第一次购买所述目标商品到第n次购买所述目标商品之间所述目标商品的购买总量；
    根据第一次购买所述目标商品到第n次购买所述目标商品之间所述目标商品的购买总量和第一次购买所述目标商品到第n次购买所述目标商品之间的时间差确第一次购买所述目标商品到第n次购买所述目标商品之间所述目标商品的平均消耗速度。
  6. 根据权利要求4中所述的方法，其中，所述根据所述目标商品的平均消耗速度以及第n次购买所述目标商品的购买信息确定所述目标商品的下一次下单时间，包括：
    根据所述目标商品的平均速度以及第n次购买所述目标商品的购买信息确定第n次购买的所述目标商品的使用时长；
    根据第n次购买所述目标商品的购买时间和第n次购买的所述目标商品的使用时长确定所述目标商品的下一次下单时间。
  7. 根据权利要求2中所述的方法，其中，所述根据所述用户购买所述目标商品的历史记录，确定所述目标商品的下一次下单时间，包括：
    根据所述用户购买所述目标商品的历史记录，确认所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息；其中，第n次购买所述目标商品的购买信息为最近一次购买所述目标商品的购买信息；
    根据所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息确定第一次购买所述目标商品到第n-1次购买所述目标商品之间消耗所述目标商品的平均速度和第一次购买所述目标商品到第n次购买所述目标商品之间消耗所述目标商品的平均加速度；
    根据所述第一次购买所述目标商品到第n-1次购买所述目标商品之间消耗所述目标商品的平均速度和第一次购买所述目标商品到第n次购买所述目标商品之间消耗所述目标商品的平均加速度，确定所述目标商品的下次购买时间。
  8. 根据权利要求2中所述的方法，其中，所述根据所述用户购买所述目标商品的历史记录，确定所述目标商品的下一次下单时间，包括：
    根据所述用户购买所述目标商品的历史记录，确认所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息；其中，第n次购买所述目标商品的购买信息为最近一次购买所述目标商品的购买信息；
    根据所述用户第一次购买所述目标商品到第n次购买所述目标商品的购买信息确定第一次购买所述目标商品到第n次购买所述目标商品之间消耗所述目标商品的平均加速度和第n-1次购买所述目标商品到第n次购买所述目标商品之间所述商品的消耗速度；
    根据所述第一次购买所述目标商品到第n次购买所述目标商品之间消耗所述目标商品的平均加速度和第n-1次购买所述目标商品到第n次购买所述目标商品之间所述商品的消耗速度，确定所述目标商品的下次购买时间。
  9. 根据权利要求1中所述的方法，所述方法还包括：
    判断所述用户最近一次购买所述商品的购买时间是否早于订单处理列表中所述目标商品的下一次下单时间；
    如果所述用户最近一次购买所述商品的购买时间早于订单处理列表中所述目标商品的下一次下单时间；
    根据所述用户购买所述目标商品的历史记录，确定在所述用户最近一次购买所述商品的购买时间之前所述目标商品的剩余量；
    根据所述目标商品的剩余量和所述用户购买所述目标商品的历史记录， 更新所述目标商品的下一次下单时间。
  10. 一种订单处理设备(500)，所述设备(500)包括：
    第一确定模块(501)，设置为确定目标商品的标识信息和购买所述目标商品的用户的标识信息；
    第二确定模块(502)，设置为根据所述目标商品的标识信息和所述购买所述目标商品的用户的标识信息，确定所述目标商品的下一次下单时间；
    下单模块(502)，设置为当所述目标商品的下一次下单时间到达时，将所述目标商品自动下单或向所述用户发送购物提醒。
  11. 一种计算机可读存储介质，存储有计算机可执行指令，所述计算机可执行指令被处理器执行时实现权利要求1至9中任一项所述的方法。
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7769153B1 (en) * 2003-06-30 2010-08-03 Embarq Holdings Company, LLP System and method for automated routing and processing of telecommunication service orders
CN103593767A (zh) * 2012-08-17 2014-02-19 纽海信息技术（上海）有限公司 电商***和订单提交方法
CN104463637A (zh) * 2014-12-23 2015-03-25 北京石油化工学院 一种基于电商平台的商品推荐方法、装置及服务器
CN106327284A (zh) * 2015-07-03 2017-01-11 中兴通讯股份有限公司 一种自动下单的方法、装置和购物平台
CN107292724A (zh) * 2017-07-04 2017-10-24 北京惠赢天下网络技术有限公司 一种订单的自动生成方法、装置及服务器

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP3596444B2 (ja) * 2000-08-02 2004-12-02 株式会社寺岡精工 キャッシュレジスタ
CN103150660A (zh) * 2011-12-06 2013-06-12 阿里巴巴集团控股有限公司 在网络购物平台中产生用户提醒消息的方法和装置
CN105511304B (zh) * 2015-11-25 2019-02-12 小米科技有限责任公司 智能提醒用户采购食材的方法及装置

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7769153B1 (en) * 2003-06-30 2010-08-03 Embarq Holdings Company, LLP System and method for automated routing and processing of telecommunication service orders
CN103593767A (zh) * 2012-08-17 2014-02-19 纽海信息技术（上海）有限公司 电商***和订单提交方法
CN104463637A (zh) * 2014-12-23 2015-03-25 北京石油化工学院 一种基于电商平台的商品推荐方法、装置及服务器
CN106327284A (zh) * 2015-07-03 2017-01-11 中兴通讯股份有限公司 一种自动下单的方法、装置和购物平台
CN107292724A (zh) * 2017-07-04 2017-10-24 北京惠赢天下网络技术有限公司 一种订单的自动生成方法、装置及服务器

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