CN111914163A - Medicine combination recommendation method and device, electronic equipment and storage medium - Google Patents
Medicine combination recommendation method and device, electronic equipment and storage medium Download PDFInfo
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- CN111914163A CN111914163A CN202010569860.2A CN202010569860A CN111914163A CN 111914163 A CN111914163 A CN 111914163A CN 202010569860 A CN202010569860 A CN 202010569860A CN 111914163 A CN111914163 A CN 111914163A
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Abstract
The invention provides a medicine combination recommendation method, a medicine combination recommendation device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring historical sales data of chain drug stores, and preprocessing the historical sales data; generating a frequent item set of the medicine based on an association rule algorithm, and sequencing the frequent item set according to support; traversing the frequent item sets to inquire item sets containing predetermined medicines, and combining and removing the repetition to obtain a related medicine array; selecting a medicine with the highest support degree in the associated medicine array and a preset medicine combination, and substituting the combined medicine into the expansion function to obtain a similar medicine combination; and searching the member ID corresponding to the similar medicine combination in the historical sales data, and combining and removing the duplicate to obtain target member information. By the scheme, the problem that the conventional medicine combination recommendation method is large in calculation amount is solved, the calculation amount of associated medicine recommendation can be reduced, the calculation efficiency is improved, the utilization of privacy data can be reduced, and the privacy of a customer is effectively protected.
Description
Technical Field
The invention relates to the technical field of data mining, in particular to a medicine combination recommendation method and device, electronic equipment and a storage medium.
Background
Generally, various medicines operated in chain pharmacy have great difference, and the sales condition of the medicines is easily influenced by factors such as seasons, epidemic diseases, customs and the like, so that the pharmacy needs to adjust the sales strategy of the medicines according to certain rules. Based on massive drug sales historical data, the method can find the purchasing habits of customers, understand the purchasing behaviors of users, find out the optimal drug combination for the customers according to the associated information among the drugs, guide the sales management behaviors, and carry out combination promotion and placement design on the drugs so as to smoothly realize promotion and reduce the inventory.
At present, a cooperative filtering recommendation method based on articles is adopted in a combined medicine recommendation method, similarity among articles needs to be calculated in an article cooperative filtering ItemCF, and for medicine sales data with huge data volume, the calculated amount of combined medicines obtained by the method is large.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for recommending a drug combination, an electronic device, and a storage medium, so as to solve the problem of a large calculation amount in the conventional drug combination recommendation method.
In a first aspect of an embodiment of the present invention, a method for recommending a drug combination is provided, including:
acquiring historical sales data of chain drug stores, and preprocessing the historical sales data;
generating a frequent item set of the medicine based on an association rule algorithm, and sequencing the frequent item set according to support;
traversing the frequent item set to inquire an item set containing a predetermined medicine, and combining and removing the duplicate to obtain an associated medicine array of the predetermined medicine;
selecting a drug with the highest support degree in the associated drug array and the preset drug combination, and substituting the combined drug into an expansion function to obtain a similar drug combination, wherein the expansion function is a similar drug expansion function defined according to the drug effect of the drug;
and searching the member ID corresponding to the similar medicine combination in the historical sales data, and combining and removing the duplicate to obtain target member information.
In a second aspect of embodiments of the present invention, there is provided an apparatus for drug combination recommendation, comprising:
the acquisition module is used for acquiring historical sales data of chain drug stores and preprocessing the historical sales data;
the association module is used for generating a frequent item set of the medicines based on an association rule algorithm and ordering the frequent item set according to support;
the traversing module is used for traversing the frequent item set to inquire an item set containing a predetermined medicine, and combining and removing the duplicate to obtain an associated medicine array of the predetermined medicine;
the expansion module is used for selecting the medicine with the highest support degree in the associated medicine array and the preset medicine combination, substituting the combined medicine into an expansion function to obtain a similar medicine combination, wherein the expansion function is a similar medicine expansion function defined according to the medicine effect of the medicine;
and the searching module is used for searching the member ID corresponding to the similar medicine combination in the historical sales data, and combining and removing the duplicate to obtain target member information.
In a third aspect of the embodiments of the present invention, there is provided an electronic device, including a memory, a processor, and a computer program stored in the memory and executable by the processor, where the processor executes the computer program to implement the steps of the method according to the first aspect of the embodiments of the present invention.
In a fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided, which stores a computer program, which when executed by a processor implements the steps of the method provided by the first aspect of the embodiments of the present invention.
In the embodiment of the invention, after sales data of a pharmacy are acquired, a frequent item set of medicines is generated based on an association rule algorithm, an association array containing specific medicines is searched through the frequent item set, an association medicine and specific medicine combination with the highest support degree is selected, after expansion through an expansion function, a corresponding user ID is searched according to similar medicine combinations, and then medicine recommendation is carried out on target customers. Based on the calculation of the frequent item set of the mass sales data, the calculation amount can be effectively reduced, the calculation cost and the operation load of a computer are reduced, the problem that the conventional medicine combination recommendation method is large in calculation amount is solved, and the accuracy and reliability of the recommendation result can be guaranteed. Meanwhile, compared with similar ItemCF recommendation, the medicine recommendation is carried out based on the purchasing behavior of the user, so that illegal acquisition and utilization of user privacy data can be avoided, and the user privacy is effectively protected.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a drug combination recommendation method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a device for recommending a drug combination according to an embodiment of the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons skilled in the art without any inventive work shall fall within the protection scope of the present invention, and the principle and features of the present invention shall be described below with reference to the accompanying drawings.
The terms "comprises" and "comprising," when used in this specification and claims, and in the accompanying drawings and figures, are intended to cover non-exclusive inclusions, such that a process, method or system, or apparatus that comprises a list of steps or elements is not limited to the listed steps or elements.
Referring to fig. 1, a flow chart of a drug combination recommendation method according to an embodiment of the present invention is schematically illustrated, including:
s101, acquiring historical sales data of chain drug stores, and preprocessing the historical sales data;
generally, historical sales data of a chain of drug stores can be uploaded through a user terminal of the drug store, each consumption of a member can be recorded and uploaded, and the server performs storage analysis.
Specifically, historical sales records of a period of time are collected, sales information corresponding to the historical sales data is extracted, the sales information at least comprises the serial number, the quantity, the member card number, the unit price, the sales amount, the store code, the sales time and the commodity code, data with null member card numbers are filtered, and data merging is carried out according to the serial number.
S102, generating a frequent item set of the medicine based on an association rule algorithm, and sequencing the frequent item set according to support;
the association rule algorithm can be used for extracting interdependency and association relation between a certain item and other items, and regarding a set of a plurality of items, when the support degree is more than a preset threshold value, the set is used as a frequent item set. Based on the association rule algorithm, only sales data of the client can be analyzed, drug recommendation is achieved, and acquisition of privacy data such as interest preference of the user can be avoided.
In the process of generating the frequent item set through the association rule algorithm, the support degree of the frequent item set is calculated, and sequencing is performed according to the support degree, so that the inquiry of the associated medicines corresponding to the specific medicines can be facilitated.
S103, traversing the frequent item sets to inquire item sets containing predetermined medicines, and combining and removing duplicates to obtain associated medicine arrays of the predetermined medicines;
for a specific medicine X, the item set containing the medicine X is searched in a traversing mode, and the item set containing the medicine X is subjected to de-duplication to obtain an associated medicine array of the medicine X.
Furthermore, the associated medicine arrays are sorted, so that the medicines with the highest support degree can be conveniently selected for combination and expansion.
S104, selecting a medicine with the highest support degree in the associated medicine array and the preset medicine combination, and substituting the combined medicine into an expansion function to obtain a similar medicine combination, wherein the expansion function is a similar medicine expansion function defined according to the medicine effect of the medicine;
the method comprises the steps of searching for a target member in a larger range, obtaining a more comprehensive recommendable object, substituting the associated medicine combination into an expansion function, wherein the expansion function is used for inquiring similar medicines according to fields of the medicines, namely similar medicine effects, and effectively expanding the similar or associated medicine combination.
And S105, searching the member ID corresponding to the similar medicine combination in the historical sales data, and combining and removing the duplicate to obtain target member information.
According to the similar medicine combination, corresponding member information is searched in the acquired historical sales data, the member information is merged and de-duplicated, the target member information can be finally obtained, based on the target member information, associated medicine recommendation can be performed in chain pharmacy, and the medicine sales volume is increased.
By the method provided by the embodiment, the computing efficiency of the computer or the server can be improved, the load is reduced, the computing amount is reduced, meanwhile, the privacy data of the user can be avoided being obtained, and the privacy safety of the user is guaranteed.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Fig. 2 is a schematic structural diagram of an apparatus for recommending a pharmaceutical composition according to an embodiment of the present invention, where the apparatus includes:
the acquisition module 210 is configured to acquire historical sales data of a chain pharmacy and preprocess the historical sales data;
specifically, the sales information corresponding to the historical sales data is extracted, wherein the sales information at least comprises a serial number, a quantity, a membership card number, a unit price, a sales amount, a store code, a sales time and a commodity code; and filtering the data with the member card number being null, and merging the data according to the serial number.
The association module 220 is configured to generate a frequent item set of the medicine based on an association rule algorithm, and sort the frequent item set according to a support degree;
a traversal module 230, configured to traverse the frequent item set to query an item set including a predetermined drug, and obtain an associated drug array of the predetermined drug after combining and deduplication;
optionally, the traversing module 230 further includes:
and the sorting unit is used for sorting the associated medicine data of the preset medicines obtained after merging and de-duplication according to the support degree.
An extension module 240, configured to select a drug with the highest support degree in the associated drug array and the predetermined drug combination, and substitute the combined drug into an extension function to obtain a similar drug combination, where the extension function is a similar drug extension function defined according to drug efficacy of the drug;
and the searching module 250 is configured to search the historical sales data for the member ID corresponding to the similar medicine combination, and obtain the target member information after combining and deduplication.
In an embodiment of the present invention, an electronic device for drug combination recommendation is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing steps S101 to S105 as in embodiments of the present invention when executing the computer program.
There is also provided in an embodiment of the present invention a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the temperature membership tag prediction method provided in the above embodiment, the non-transitory computer readable storage medium including: ROM/RAM, magnetic disk, optical disk, etc.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. A drug combination recommendation method is characterized by comprising the following steps:
acquiring historical sales data of chain drug stores, and preprocessing the historical sales data;
generating a frequent item set of the medicine based on an association rule algorithm, and sequencing the frequent item set according to support;
traversing the frequent item set to inquire an item set containing a predetermined medicine, and combining and removing the duplicate to obtain an associated medicine array of the predetermined medicine;
selecting a drug with the highest support degree in the associated drug array and the preset drug combination, and substituting the combined drug into an expansion function to obtain a similar drug combination, wherein the expansion function is a similar drug expansion function defined according to the drug effect of the drug;
and searching the member ID corresponding to the similar medicine combination in the historical sales data, and combining and removing the duplicate to obtain target member information.
2. The method of claim 1, wherein the obtaining historical sales data of a chain of pharmacy, and the preprocessing of the historical sales data comprises:
extracting sales information corresponding to the historical sales data, wherein the sales information at least comprises a serial number, a quantity, a membership card number, a unit price, a sales amount, a store code, sales time and a commodity code;
and filtering the data with the member card number being null, and merging the data according to the serial number.
3. The method of claim 1, wherein said traversing said frequent item set for an item set comprising a predetermined drug, and wherein said combining and de-duplicating to obtain an associated drug array for said predetermined drug further comprises:
and sorting the associated medicine data of the preset medicines obtained after merging and de-duplication according to the support degree.
4. An apparatus for drug combination recommendation, comprising:
the acquisition module is used for acquiring historical sales data of chain drug stores and preprocessing the historical sales data;
the association module is used for generating a frequent item set of the medicines based on an association rule algorithm and ordering the frequent item set according to support;
the traversing module is used for traversing the frequent item set to inquire an item set containing a predetermined medicine, and combining and removing the duplicate to obtain an associated medicine array of the predetermined medicine;
the expansion module is used for selecting the medicine with the highest support degree in the associated medicine array and the preset medicine combination, substituting the combined medicine into an expansion function to obtain a similar medicine combination, wherein the expansion function is a similar medicine expansion function defined according to the medicine effect of the medicine;
and the searching module is used for searching the member ID corresponding to the similar medicine combination in the historical sales data, and combining and removing the duplicate to obtain target member information.
5. The apparatus of claim 4, wherein the historical sales data of the pharmacy chain is obtained, and the preprocessing of the historical sales data comprises:
extracting sales information corresponding to the historical sales data, wherein the sales information at least comprises a serial number, a quantity, a membership card number, a unit price, a sales amount, a store code, sales time and a commodity code;
and filtering the data with the member card number being null, and merging the data according to the serial number.
6. The apparatus of claim 4, wherein the traversal module further comprises:
and the sorting unit is used for sorting the associated medicine data of the preset medicines obtained after merging and de-duplication according to the support degree.
7. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the drug combination recommendation method of any one of claims 1 to 5 when executing the computer program.
8. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for recommending a pharmaceutical combination according to any of claims 1 to 5.
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| CN202010569860.2A CN111914163A (en) | 2020-06-20 | 2020-06-20 | Medicine combination recommendation method and device, electronic equipment and storage medium |
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| CN112258085A (en) * | 2020-11-12 | 2021-01-22 | 北京筑龙信息技术有限责任公司 | Material management method and device |
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| CN113011918A (en) * | 2021-03-02 | 2021-06-22 | 广东便捷神科技股份有限公司 | Data processing system for cost control |
| CN113849724A (en) * | 2021-06-23 | 2021-12-28 | 福建省农业科学院植物保护研究所 | Special small crop pest control medication recommendation method based on rule association and storage device |
| CN113934943A (en) * | 2021-11-26 | 2022-01-14 | 湖北中烟工业有限责任公司 | Formula module collocation recommendation method and device based on FP-growth correlation analysis rule |
| CN114496170A (en) * | 2022-01-27 | 2022-05-13 | 四川大学 | Tibetan medicine display recommendation method and system, computer device and readable storage medium |
| CN115983921A (en) * | 2022-12-29 | 2023-04-18 | 广州市玄武无线科技股份有限公司 | Offline store commodity association combination method, device, equipment and storage medium |
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