CN110956514A - Method and device for generating order information - Google Patents
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- 238000004590 computer program Methods 0.000 claims description 9
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- G06Q30/06—Buying, selling or leasing transactions
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Abstract
The invention discloses a method and a device for generating order information, and relates to the technical field of computers. One embodiment of the method comprises: according to historical purchase data, eliminating commodities of which the candidate commodities are concentrated in a preset purchase period; receiving a promotion message, and putting the commodities corresponding to the promotion information in the candidate commodity set into an order candidate set according to the promotion information in the promotion message; and performing optimization solution on the commodities in the order candidate set so as to generate order information. This embodiment can solve the problem of not being able to automatically generate an order for a user that meets the user's expectations.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a device for generating order information.
Background
With the rapid development of e-commerce services, users are more and more accustomed to online shopping. Currently, when a user finds that the e-commerce system has a promotion, the user artificially selects commodities to make a bill and then places the bill.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:
1) the user artificially collects the order, and a large amount of time is spent for selecting the commodities, so that a part of users do not want to collect the order due to the time cost and lose a part of user groups;
2) the user spends time making a bill, but the selected goods do not meet the expected benefits of the user, and a part of the user group is lost.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for generating order information, which can solve the problem that an order meeting the expectations of a user cannot be automatically generated for the user.
To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a method of generating order information, including:
according to historical purchase data, eliminating commodities of which the candidate commodities are concentrated in a preset purchase period;
receiving a promotion message, and putting the commodities corresponding to the promotion information in the candidate commodity set into an order candidate set according to the promotion information in the promotion message;
and performing optimization solution on the commodities in the order candidate set so as to generate order information.
Optionally, before excluding the commodities whose candidate commodities are concentrated in the preset purchase period according to the historical purchase order, the method further includes:
determining candidate commodities according to historical purchase data, and putting the candidate commodities into a candidate commodity set; and/or the presence of a gas in the gas,
and putting the commodities appearing in the same session into a candidate commodity set according to the historical browsing data.
Optionally, before excluding the commodities whose candidate commodities are concentrated in the preset purchase period according to the historical purchase order, the method further includes:
determining the payment price of the order, the quantity corresponding to each commodity in the order and the page price according to historical purchase data, and calculating the maximum payment price and the minimum payment price of each commodity so as to determine the expected price interval of each commodity; and/or the presence of a gas in the gas,
and determining an expected price interval of each commodity according to the maximum payment price and the minimum payment price set by the user.
Optionally, the placing the commodities, corresponding to the promotion information, in the candidate commodity set into the candidate order set according to the promotion information in the promotion message includes:
according to the promotion information in the promotion information, calculating the minimum payment price of the commodities corresponding to the promotion information in the candidate commodity set under the current promotion;
and if the minimum payment price of the commodity under the current promotion is within the expected price interval of the commodity, putting the commodity into an order candidate set.
Optionally, performing an optimization solution on the commodities in the order candidate set to generate order information, including:
generating at least one suggested order based on the commodities in the order candidate set;
and performing optimization solution on the at least one suggested order, and taking the suggested order corresponding to the optimal solution as order information.
Optionally, performing an optimization solution on the at least one suggested order, and taking a suggested order corresponding to the optimal solution as order information, includes:
determining limiting conditions corresponding to the promotion information according to the promotion information;
and taking the limiting conditions corresponding to the promotion information and the expected price intervals of the commodities as constraint conditions, and aiming at each proposed order, solving the maximum value of the following formula:
summing all the items in the proposed order according to [ (maximum payment price-payment price of the items in the proposed order) x number of items in the proposed order ];
and taking the suggested order corresponding to the maximum value of the formula as order information.
In addition, according to another aspect of the embodiments of the present invention, there is provided an apparatus for generating order information, including:
the elimination module is used for eliminating the commodities of which the candidate commodities are concentrated in the preset purchase period according to the historical purchase data;
the processing module is used for receiving the promotion information and putting the commodities corresponding to the promotion information in the candidate commodity set into the order candidate set according to the promotion information in the promotion information;
and the solving module is used for carrying out optimization solving on the commodities in the order candidate set so as to generate order information.
Optionally, the system further comprises a screening module, configured to:
determining candidate commodities according to historical purchase data, and putting the candidate commodities into a candidate commodity set; and/or the presence of a gas in the gas,
and putting the commodities appearing in the same session into a candidate commodity set according to the historical browsing data.
Optionally, the system further comprises a preset module, configured to:
determining the payment price of the order, the quantity corresponding to each commodity in the order and the page price according to historical purchase data, and calculating the maximum payment price and the minimum payment price of each commodity so as to determine the expected price interval of each commodity; and/or the presence of a gas in the gas,
and determining an expected price interval of each commodity according to the maximum payment price and the minimum payment price set by the user.
Optionally, the placing the commodities, corresponding to the promotion information, in the candidate commodity set into the candidate order set according to the promotion information in the promotion message includes:
according to the promotion information in the promotion information, calculating the minimum payment price of the commodities corresponding to the promotion information in the candidate commodity set under the current promotion;
and if the minimum payment price of the commodity under the current promotion is within the expected price interval of the commodity, putting the commodity into an order candidate set.
Optionally, the solving module is configured to:
generating at least one suggested order based on the commodities in the order candidate set;
and performing optimization solution on the at least one suggested order, and taking the suggested order corresponding to the optimal solution as order information.
Optionally, performing an optimization solution on the at least one suggested order, and taking a suggested order corresponding to the optimal solution as order information, includes:
determining limiting conditions corresponding to the promotion information according to the promotion information;
and taking the limiting conditions corresponding to the promotion information and the expected price intervals of the commodities as constraint conditions, and aiming at each proposed order, solving the maximum value of the following formula:
summing all the items in the proposed order according to [ (maximum payment price-payment price of the items in the proposed order) x number of items in the proposed order ];
and taking the suggested order corresponding to the maximum value of the formula as order information.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any of the embodiments described above.
According to another aspect of the embodiments of the present invention, there is also provided a computer readable medium, on which a computer program is stored, which when executed by a processor implements the method of any of the above embodiments.
One embodiment of the above invention has the following advantages or benefits: because the technical means that the commodities corresponding to the sales promotion information in the candidate commodity set are put into the order candidate set according to the sales promotion information and the commodities in the order candidate set are optimally solved to generate the order information is adopted, the technical problem that the order meeting the expectation of the user cannot be automatically generated for the user is solved; according to the method, the price sensitive zone and the candidate commodity set of the commodities purchased by the user are summarized by utilizing the historical shopping data and the historical browsing data of the user, then the promotion information is taken as the classification dimension, and the suggested order recommended to the user is calculated by utilizing an optimization means, so that a quick path for collecting the order is provided for the user, the user does not need to manually collect the order, the time cost of the user is saved, and the commodities which meet the expected price of the user can be quickly and accurately positioned.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
fig. 1 is a schematic view of a main flow of a method of generating order information according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating a main flow of a method of generating order information according to a referential embodiment of the present invention;
FIG. 3 is a schematic diagram of the main modules of an apparatus for generating order information according to an embodiment of the present invention;
FIG. 4 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 5 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 is a schematic diagram of a main flow of a method of generating order information according to an embodiment of the present invention. As shown in fig. 1, as an embodiment of the present invention, the method for generating order information includes:
and 101, eliminating the commodities with the candidate commodities concentrated in the preset purchase period according to the historical purchase data.
It should be noted that, in the embodiment of the present invention, the commodity may be a Fast selling commodity, which is an abbreviation of Fast Moving Consumer Goods (FMCG), and refers to a Consumer product with a short service life and a Fast consuming speed. The quick sales items may be restricted by item classification.
In another embodiment of the present invention, before step 101, the method further comprises: and determining candidate commodities according to historical purchase data, and putting the candidate commodities into a candidate commodity set. In this embodiment, candidate items in each order data are determined through the historical purchase data (i.e. completed order data) of the user, and the candidate items are placed in the candidate item set after being deduplicated.
In another embodiment of the present invention, before step 101, the method further comprises: and putting the commodities appearing in the same session into a candidate commodity set according to the historical browsing data. In this embodiment, the candidate commodity set may be maintained in combination with a browsing record of the user, that is, a skip situation of browsing the fast-selling commodities by the user. This is primarily to take advantage of the complementarity between goods, such as the purchase of a toothbrush, and the easy thought of purchasing toothpaste, and thus one session of the user as a processing node. If the user browses items A, B and C in the same session, a key-value pair is maintained if A is a quick sell item. Where key is the SKU (short for product uniform number) of item a, and value is a list including fast-selling items, such as item B and item C, that appear in the same session as item a. If a plurality of fast selling commodities appear in the same session, correspondingly establishing a plurality of groups of key-value key value pairs, wherein key is the SKU of the fast selling commodity, and value is the fast selling commodity list corresponding to the fast selling commodity.
In yet another embodiment of the present invention, before step 101, the method further comprises: determining the payment price of the order, the quantity corresponding to each commodity in the order and the page price according to historical purchase data, and calculating the maximum payment price and the minimum payment price of each commodity so as to determine the expected price interval of each commodity; and/or determining the expected price interval of each commodity according to the maximum payment price and the minimum payment price set by the user.
If an order m includes N commodities, the quantity corresponding to each commodity is NumimI is equal to {1,2, …, N }, and the Price of the page corresponding to each commodity is PriceimI e {1,2, …, N }, and the order has a payment price PmThen the payment price for item i is:
then, for this purpose, the payment price for purchasing item i is a set Pi＝{Pi1,Pi2,…,PiMAnd M is the times of purchasing the commodity by the user. Then in the set PiAnd acquiring the maximum payment price and the minimum payment price as the expected price interval of the commodity.
Further, the expected price interval can be used as a reference interval given to the user by the system. If the user does not set the price interval, the maximum payment price and the minimum payment price calculated according to the method are used as the expected price interval of the commodity; and if the maximum payment price and the minimum payment price are set by the user, taking the maximum payment price and the minimum payment price set by the user as the expected price interval of the commodity. That is, the priority set by the user is greater than the priority of the system configuration.
In another embodiment of the present invention, before step 101, the method further comprises: purchase cycles are set in advance for respective commodities. Optionally, the same purchase cycle may be set for each commodity, or different purchase cycles may be set for different commodities, that is, how long the consumer purchases the fast-moving commodity is set, the consumer may be triggered to purchase the commodity again. The purchase cycle can also be set for a certain commodity, if the certain commodity is provided with an independent purchase cycle, the judgment is carried out according to the purchase cycle, and if the independent purchase cycle is not set, the judgment is carried out according to the purchase cycle of the fast-selling commodity.
Therefore, in step 101, according to the fast-moving goods purchased by the user, the difference between the current time and the purchase time is calculated, so as to exclude the fast-moving goods with candidate goods concentrated in the preset purchase period and avoid repeated purchase in the purchase period.
And 102, receiving the promotion information, and putting the commodities corresponding to the promotion information in the candidate commodity set into the order candidate set according to the promotion information in the promotion information.
The method can subscribe the sales promotion information of the commodities through the background, and after the sales promotion information is received, the commodities which are associated with the sales promotion information in the candidate commodity set can be put into the order candidate set according to the sales promotion information in the sales promotion information.
Similarly, the promotion information may also be maintained based on a key-value key value pair, where key is the SKU of the item and value is the promotion id (i.e., promotion information). For example, the promotional information is: the number of the parts is reduced from the full A part to the B part, from the full A part to the full B part, or from the full A part to the full B part, and the like. When the promotion information is newly added promotion, the value data corresponding to the key is newly added with the promotion information; when the promotion message is deleted for promotion or is expired, the value data corresponding to the key will remove the corresponding promotion id (i.e., promotion information). It should be noted that each piece of the promotion information has a promotion id, and the corresponding promotion information can be known through the promotion id.
As still another embodiment of the present invention, placing the items corresponding to the promotion information in the candidate item set into an order candidate set according to the promotion information in the promotion message includes: according to the promotion information in the promotion information, calculating the minimum payment price of the commodities corresponding to the promotion information in the candidate commodity set under the current promotion; and if the minimum payment price of the commodity under the current promotion is within the expected price interval of the commodity, putting the commodity into an order candidate set. In the embodiment, firstly, the minimum payment price of the commodity corresponding to the promotion information under the current promotion is calculated according to the promotion information, then whether the minimum payment price of the commodity under the current promotion is within the expected price interval of the commodity is judged, if yes, the commodity is put into the order candidate set, and if not, the commodity is kept in the candidate commodity set.
It should be noted that each piece of promotion information corresponds to one order candidate set, that is, the items associated with the same promotion id and meeting the conditions of purchase cycle, price interval, etc. are put into the same order candidate set. Moreover, the same item may be involved in multiple promotional programs, and thus the same item may be placed into multiple order candidate sets associated therewith based on the promotional information.
And 103, carrying out optimization solution on the commodities in the order candidate set so as to generate order information.
Firstly, generating at least one suggested order based on the commodities in the order candidate set obtained in the step 102; and then carrying out optimization solution on the at least one suggested order, and taking the suggested order corresponding to the optimal solution as order information. In this step, at least one suggested order may be generated separately for each order candidate set.
Optionally, performing an optimization solution on the at least one suggested order, and taking a suggested order corresponding to the optimal solution as order information, includes: determining limiting conditions corresponding to the promotion information according to the promotion information; and taking the limiting conditions corresponding to the promotion information and the expected price intervals of the commodities as constraint conditions, and aiming at each proposed order, solving the maximum value of the following formula: summing all the items in the proposed order according to [ (maximum payment price-payment price of the items in the proposed order) x number of items in the proposed order ]; and taking the suggested order corresponding to the maximum value of the formula as order information.
It should be noted that different promotional information may have different constraints, such as the following table:
for a proposed order, if the items in the candidate set of proposed orders are {1,2, …, N }, the price paid for item i in the proposed order is piThe maximum payment price of the commodity i set by the user or the system is siNumber of items n in the proposed orderiAnd optimally solving the maximum value of the following formula:
constraint conditions are as follows: 1) the commodity belongs to a candidate commodity set; 2) the payment price corresponding to the commodity is in the range of the expected price interval; 3) and limiting conditions corresponding to the promotion id.
And (4) carrying out optimization solution on at least one suggested order corresponding to the same promotion information by combining constraint conditions, and selecting the optimized solution, wherein the suggested order is the generated order information.
Therefore, the embodiment of the invention provides the user with the order suggestion of the fast selling goods based on the historical purchase record and/or the historical browsing data of the user. The user selects the service through subscription, configures a period of fast selling goods to complete subscription, automatically places an order if a goods set which accords with the subscription of the user is found, and then informs the user, and the user starts to walk an order production flow if the user selects to be determined; if a cancel or no selection is selected (within the order validity period, e.g., 24 hours), the produced order is suggested to be automatically cancelled.
According to the various embodiments, the technical scheme that the order information is generated by putting the commodities corresponding to the promotion information in the candidate commodity set into the order candidate set according to the promotion information and performing optimization solution on the commodities in the order candidate set is adopted, and the problem that the order meeting the expectation of the user cannot be automatically generated for the user is solved. According to the method, the price sensitive zone and the candidate commodity set of the commodities purchased by the user are summarized by utilizing the historical shopping data and the historical browsing data of the user, then the promotion information is taken as the classification dimension, and the suggested order recommended to the user is calculated by utilizing an optimization means, so that a quick path for collecting the order is provided for the user, the user does not need to manually collect the order, the time cost of the user is saved, and the commodities which meet the expected price of the user can be quickly and accurately positioned.
Fig. 2 is a schematic diagram of a main flow of a method for generating order information according to a referential embodiment of the present invention, and the method for generating order information may include:
step 201, determining candidate commodities according to historical purchase data, and putting the candidate commodities into a candidate commodity set;
step 202, placing the commodities appearing in the same conversation into a candidate commodity set according to historical browsing data;
step 203, determining the payment price of the order, the quantity corresponding to each commodity in the order and the page price according to the historical purchase data, and calculating the maximum payment price and the minimum payment price of each commodity so as to determine the expected price interval of each commodity; and/or determining an expected price interval of each commodity according to the maximum payment price and the minimum payment price set by the user;
step 204, eliminating commodities with candidate commodities concentrated in a preset purchase period according to historical purchase data;
step 205, receiving a promotion message, and calculating the minimum payment price of the commodities corresponding to the promotion information in the candidate commodity set under the current promotion according to the promotion information in the promotion message;
step 206, judging whether the minimum payment price of the commodity under the current promotion is within the expected price interval of the commodity; if yes, go to step 207; if not, ending;
step 208, generating at least one suggested order based on the commodities in the order candidate set;
and step 209, performing optimization solution on the at least one suggested order, and using the suggested order corresponding to the optimal solution as order information.
It should be noted that, step 201 and step 202 may be executed simultaneously, or step 201 and then step 202 may be executed first, or step 202 and then step 201 may be executed first, which is not limited in this embodiment of the present invention.
It should be noted that, under the condition that the present invention can be realized, the order of the above steps can be adjusted according to needs, and the adjusted technical solutions are all within the protection scope of the present invention.
In addition, in a reference embodiment of the present invention, the detailed implementation of the method for generating order information is described in detail in the above-mentioned method for generating order information, and therefore, the repeated content is not described again.
Fig. 3 is a schematic diagram of main blocks of an apparatus for generating order information according to an embodiment of the present invention. As shown in fig. 3, the apparatus 300 for generating order information includes an excluding module 301, a processing module 302 and a solving module 303. The eliminating module 301 eliminates the commodities with the candidate commodities concentrated in the preset purchasing period according to the historical purchasing data; the processing module 302 receives the promotion message, and puts the commodities corresponding to the promotion information in the candidate commodity set into the order candidate set according to the promotion information in the promotion message; the solving module 303 performs an optimization solution on the commodities in the order candidate set, thereby generating order information.
Optionally, the system further comprises a screening module, wherein the screening module determines candidate commodities according to historical purchase data and puts the candidate commodities into a candidate commodity set; and/or putting the commodities appearing in the same conversation into the candidate commodity set according to the historical browsing data.
Optionally, the system further comprises a preset module, wherein the preset module determines the payment price of the order, the quantity corresponding to each commodity in the order and the page price according to historical purchase data, and calculates the maximum payment price and the minimum payment price of each commodity, so as to determine the expected price interval of each commodity; and/or determining the expected price interval of each commodity according to the maximum payment price and the minimum payment price set by the user.
Optionally, the placing the commodities, corresponding to the promotion information, in the candidate commodity set into the candidate order set according to the promotion information in the promotion message includes:
according to the promotion information in the promotion information, calculating the minimum payment price of the commodities corresponding to the promotion information in the candidate commodity set under the current promotion;
and if the minimum payment price of the commodity under the current promotion is within the expected price interval of the commodity, putting the commodity into an order candidate set.
Optionally, the solving module 303 generates at least one suggested order based on the commodities in the order candidate set; and performing optimization solution on the at least one suggested order, and taking the suggested order corresponding to the optimal solution as order information.
Optionally, performing an optimization solution on the at least one suggested order, and taking a suggested order corresponding to the optimal solution as order information, includes:
determining limiting conditions corresponding to the promotion information according to the promotion information;
and taking the limiting conditions corresponding to the promotion information and the expected price intervals of the commodities as constraint conditions, and aiming at each proposed order, solving the maximum value of the following formula:
summing all the items in the proposed order according to [ (maximum payment price-payment price of the items in the proposed order) x number of items in the proposed order ];
and taking the suggested order corresponding to the maximum value of the formula as order information.
According to the various embodiments, the technical scheme that the order information is generated by putting the commodities corresponding to the promotion information in the candidate commodity set into the order candidate set according to the promotion information and performing optimization solution on the commodities in the order candidate set is adopted, and the problem that the order meeting the expectation of the user cannot be automatically generated for the user is solved. According to the method, the price sensitive zone and the candidate commodity set of the commodities purchased by the user are summarized by utilizing the historical shopping data and the historical browsing data of the user, then the promotion information is taken as the classification dimension, and the suggested order recommended to the user is calculated by utilizing an optimization means, so that a quick path for collecting the order is provided for the user, the user does not need to manually collect the order, the time cost of the user is saved, and the commodities which meet the expected price of the user can be quickly and accurately positioned.
It should be noted that, in the implementation of the apparatus for generating order information according to the present invention, the above method for generating order information has been described in detail, and therefore, the repeated description is omitted here.
Fig. 4 illustrates an exemplary system architecture 400 to which the method of generating order information or the method of generating order information of embodiments of the present invention may be applied.
As shown in fig. 4, the system architecture 400 may include terminal devices 401, 402, 403, a network 404, and a server 405. The network 404 serves as a medium for providing communication links between the terminal devices 401, 402, 403 and the server 405. Network 404 may include various types of connections, such as wire, wireless communication links, or fiber optic cables, to name a few.
A user may use terminal devices 401, 402, 403 to interact with a server 405 over a network 404 to receive or send messages or the like. The terminal devices 401, 402, 403 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 401, 402, 403 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 405 may be a server providing various services, such as a background management server (for example only) providing support for shopping websites browsed by users using the terminal devices 401, 402, 403. The background management server may analyze and process the received data such as the product information query request, and feed back a processing result (for example, target push information and product information — only an example) to the terminal device.
It should be noted that the method for generating order information provided by the embodiment of the present invention is generally executed in the server 405, and accordingly, the apparatus for generating order information is generally disposed in the server 405. The method for generating order information provided by the embodiment of the present invention may also be executed in the terminal devices 401, 402, and 403, and accordingly, the apparatus for generating order information is generally disposed on the terminal devices 401, 402, and 403.
It should be understood that the number of terminal devices, networks, and servers in fig. 4 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 5, shown is a block diagram of a computer system 500 suitable for use with a terminal device implementing an embodiment of the present invention. The terminal device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 5, the computer system 500 includes a Central Processing Unit (CPU)501 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the system 500 are also stored. The CPU 501, ROM 502, and RAM 503 are connected to each other via a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
The following components are connected to the I/O interface 505: an input portion 506 including a keyboard, a mouse, and the like; an output portion 507 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The driver 510 is also connected to the I/O interface 505 as necessary. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as necessary, so that a computer program read out therefrom is mounted into the storage section 508 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 509, and/or installed from the removable medium 511. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 501.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes an exclusion module, a processing module, and a resolution module, where the names of the modules do not in some cases constitute a limitation on the modules themselves.
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: according to historical purchase data, eliminating commodities of which the candidate commodities are concentrated in a preset purchase period; receiving a promotion message, and putting the commodities corresponding to the promotion information in the candidate commodity set into an order candidate set according to the promotion information in the promotion message; and performing optimization solution on the commodities in the order candidate set so as to generate order information.
According to the technical scheme of the embodiment of the invention, the technical means that the order information is generated by putting the commodities corresponding to the sales promotion information in the candidate commodity set into the order candidate set and optimally solving the commodities in the order candidate set according to the sales promotion information is adopted, so that the technical problem that the order meeting the expectation of the user cannot be automatically generated for the user is solved; according to the method, the price sensitive zone and the candidate commodity set of the commodities purchased by the user are summarized by utilizing the historical shopping data and the historical browsing data of the user, then the promotion information is taken as the classification dimension, and the suggested order recommended to the user is calculated by utilizing an optimization means, so that a quick path for collecting the order is provided for the user, the user does not need to manually collect the order, the time cost of the user is saved, and the commodities which meet the expected price of the user can be quickly and accurately positioned.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (14)
1. A method of generating order information, comprising:
according to historical purchase data, eliminating commodities of which the candidate commodities are concentrated in a preset purchase period;
receiving a promotion message, and putting the commodities corresponding to the promotion information in the candidate commodity set into an order candidate set according to the promotion information in the promotion message;
and performing optimization solution on the commodities in the order candidate set so as to generate order information.
2. The method of claim 1, further comprising, prior to excluding the items of which the candidate items are concentrated within the preset purchase period according to the historical purchase order:
determining candidate commodities according to historical purchase data, and putting the candidate commodities into a candidate commodity set; and/or the presence of a gas in the gas,
and putting the commodities appearing in the same session into a candidate commodity set according to the historical browsing data.
3. The method of claim 1, further comprising, prior to excluding the items of which the candidate items are concentrated within the preset purchase period according to the historical purchase order:
determining the payment price of the order, the quantity corresponding to each commodity in the order and the page price according to historical purchase data, and calculating the maximum payment price and the minimum payment price of each commodity so as to determine the expected price interval of each commodity; and/or the presence of a gas in the gas,
and determining an expected price interval of each commodity according to the maximum payment price and the minimum payment price set by the user.
4. The method of claim 3, wherein placing the set of candidate items corresponding to promotional information into a candidate set of orders based on promotional information in the promotional message comprises:
according to the promotion information in the promotion information, calculating the minimum payment price of the commodities corresponding to the promotion information in the candidate commodity set under the current promotion;
and if the minimum payment price of the commodity under the current promotion is within the expected price interval of the commodity, putting the commodity into an order candidate set.
5. The method of claim 3, wherein optimally solving the items in the candidate set of orders to generate order information comprises:
generating at least one suggested order based on the commodities in the order candidate set;
and performing optimization solution on the at least one suggested order, and taking the suggested order corresponding to the optimal solution as order information.
6. The method of claim 5, wherein performing an optimization solution on the at least one proposed order with a proposed order corresponding to the optimal solution as order information comprises:
determining limiting conditions corresponding to the promotion information according to the promotion information;
and taking the limiting conditions corresponding to the promotion information and the expected price intervals of the commodities as constraint conditions, and aiming at each proposed order, solving the maximum value of the following formula:
summing all the items in the proposed order according to [ (maximum payment price-payment price of the items in the proposed order) x number of items in the proposed order ];
and taking the suggested order corresponding to the maximum value of the formula as order information.
7. An apparatus for generating order information, comprising:
the elimination module is used for eliminating the commodities of which the candidate commodities are concentrated in the preset purchase period according to the historical purchase data;
the processing module is used for receiving the promotion information and putting the commodities corresponding to the promotion information in the candidate commodity set into the order candidate set according to the promotion information in the promotion information;
and the solving module is used for carrying out optimization solving on the commodities in the order candidate set so as to generate order information.
8. The apparatus of claim 7, further comprising a screening module to:
determining candidate commodities according to historical purchase data, and putting the candidate commodities into a candidate commodity set; and/or the presence of a gas in the gas,
and putting the commodities appearing in the same session into a candidate commodity set according to the historical browsing data.
9. The apparatus of claim 7, further comprising a preset module configured to:
determining the payment price of the order, the quantity corresponding to each commodity in the order and the page price according to historical purchase data, and calculating the maximum payment price and the minimum payment price of each commodity so as to determine the expected price interval of each commodity; and/or the presence of a gas in the gas,
and determining an expected price interval of each commodity according to the maximum payment price and the minimum payment price set by the user.
10. The apparatus of claim 9, wherein placing the set of candidate items corresponding to promotional information into a candidate set of orders based on promotional information in the promotional message comprises:
according to the promotion information in the promotion information, calculating the minimum payment price of the commodities corresponding to the promotion information in the candidate commodity set under the current promotion;
and if the minimum payment price of the commodity under the current promotion is within the expected price interval of the commodity, putting the commodity into an order candidate set.
11. The apparatus of claim 9, wherein the solving module is configured to:
generating at least one suggested order based on the commodities in the order candidate set;
and performing optimization solution on the at least one suggested order, and taking the suggested order corresponding to the optimal solution as order information.
12. The apparatus of claim 11, wherein performing an optimization solution on the at least one proposed order with a proposed order corresponding to the optimal solution as order information comprises:
determining limiting conditions corresponding to the promotion information according to the promotion information;
and taking the limiting conditions corresponding to the promotion information and the expected price intervals of the commodities as constraint conditions, and aiming at each proposed order, solving the maximum value of the following formula:
summing all the items in the proposed order according to [ (maximum payment price-payment price of the items in the proposed order) x number of items in the proposed order ];
and taking the suggested order corresponding to the maximum value of the formula as order information.
13. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-6.
14. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-6.
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