CN114239984A - Service item optimization method, service item optimization device, electronic device, service item optimization medium, and program product - Google Patents

Service item optimization method, service item optimization device, electronic device, service item optimization medium, and program product Download PDF

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CN114239984A
CN114239984A CN202111584643.1A CN202111584643A CN114239984A CN 114239984 A CN114239984 A CN 114239984A CN 202111584643 A CN202111584643 A CN 202111584643A CN 114239984 A CN114239984 A CN 114239984A
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transaction
target
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陈曦
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China Construction Bank Corp
CCB Finetech Co Ltd
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CCB Finetech Co Ltd
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Abstract

The present disclosure provides an optimization model-based service item optimization method, apparatus, electronic device, medium, and computer program product. The method and the device can be used in the technical field of big data. The service item optimization method based on the optimization model comprises the following steps: acquiring m items of information; giving n to each item information according to a scoring ruleeThe affair handling guidelines are respectively marked to obtain neA point transaction guide; n is to beeComparing the score affair handling guidelines with standard threshold values respectively, and taking the score affair handling guidelines meeting the standard threshold values as standard affair handling guidelines; acquiring a target item; scoring the target item guide according to scoring rules to obtain a target score guide(ii) a Matching the target item name with the item names of the m item information; when the item names are matched, comparing the target score guide with the standard item transaction guide under the item information corresponding to the matched item names to obtain a comparison result; and recommending an optimization scheme of the target items according to the comparison result.

Description

Service item optimization method, service item optimization device, electronic device, service item optimization medium, and program product
Technical Field
The present disclosure relates to the field of big data technologies, and more particularly, to a service item optimization method, apparatus, electronic device, medium, and computer program product based on an optimization model.
Background
Currently, according to the requirements of national policies, administrative departments in various regions need to continuously promote the optimization of government affairs services in the jurisdiction scope (specifically including running times, time, materials and flow reduction for handling affairs), but because the number of government affair service affairs in various regions of the country is huge, and the content and information structure of the handling guidelines of the government affair service affairs in each region and county of province and city are greatly different, a technical method is lacked at present, different names of single items to be optimized can be rapidly agreed in the country (namely the same handling affair but different laws), and whether optimization space exists in the items or not and a specific optimization suggestion are judged.
Disclosure of Invention
In view of the foregoing, the present disclosure provides a method, an apparatus, an electronic device, a computer-readable storage medium, and a computer program product for optimizing service items based on an optimization model, which are fast, efficient, and resource-saving.
One aspect of the present disclosure provides an optimization model-based service item optimization method, including: obtaining m transaction information as a first parameter of the optimization model, wherein each transaction information includes neAn item name and an item guide corresponding to each item name, m is an integer of 1 or more, neIs an integer of 1 or more, and e is an integer of 1 or more and m or less; setting a scoring rule as a second parameter of the optimization model; giving n to each item information according to the scoring ruleeRespectively scoring the item handling guide to obtain neA point transaction guide; setting a standard threshold value as a third parameter of the optimization model; n is to beeThe score transaction guides are respectively compared with the standard threshold value, and the score transaction guides meeting the standard threshold value are used as standard transaction guides; acquiring a target item as an input of the optimization model, wherein the target item comprises a target item name and a target item guide; according to the scoring ruleScoring the target item guide to obtain a target score guide; matching the target item name with the item names of the m item information; when the item name is matched, comparing the target score guide with the standard item transaction guide under the item information corresponding to the matched item name to obtain a comparison result; and recommending an optimization scheme of the target item according to the comparison result as the output of the optimization model.
According to the service item optimization method based on the optimization model, by acquiring the m item information and matching the target item with the item names of the m item information, items similar to the target item can be quickly, accurately and efficiently matched from a plurality of item information data; the target item guide is compared with the standard item transaction guide of the similar items of the target item, and item optimization suggestions are provided according to the comparison result, so that manpower and material resources can be saved, and the working efficiency is improved.
In some embodiments, each of the transaction guides includes giIndividual item transaction element, giIs an integer of 1 or more, i is 1 or more and n or lesseAn integer of (d); the n given to each item information according to the scoring ruleeRespectively scoring the item handling guide to obtain neEach point office guide includes: (g) providing each item transaction guide with the scoring rulesiThe item transaction elements are respectively scored until neAll the item transaction guidelines are scored to obtain neAnd (4) point transaction guides.
In some embodiments, the giThe individual event transaction elements include at least one of transaction time limit, type of office, number of runs, net office level, and number of material copies.
In some embodiments, the target transaction guide includes r target transaction elements, r is an integer greater than or equal to 1, and scoring the target transaction guide according to the scoring rule to obtain the target score guide includes: and respectively scoring the r target transaction elements according to the scoring rules to obtain a target score guide.
In some embodiments, when the item name is matched, the r target transaction elements of the target item guide and the g of the standard item transaction guide matchediThe item transaction elements are the same, and the comparing the target score guide with the standard item transaction guide under the item information corresponding to the matched item name to obtain the comparison result comprises: and comparing the score of each target transaction element with the corresponding score of the transaction element to obtain r comparison results.
In some embodiments, the recommending, as the output of the optimization model, the optimization scheme of the target item according to the comparison result includes: and recommending the optimization scheme of the corresponding target transaction element as the output of the optimization model according to each comparison result.
Another aspect of the present disclosure provides an optimization model-based service item optimization apparatus, including: a first obtaining module, configured to perform obtaining m event information as a first parameter of the optimization model, where each event information includes neAn item name and an item guide corresponding to each item name, m is an integer of 1 or more, neIs an integer of 1 or more, and e is an integer of 1 or more and m or less; the first setting module is used for executing setting of a scoring rule as a second parameter of the optimization model; a first scoring module for executing n for each of the transaction information according to the scoring ruleseRespectively scoring the item handling guide to obtain neA point transaction guide; a second setting module, configured to perform setting of a standard threshold as a third parameter of the optimization model; a first comparison module to perform comparing neThe score transaction guides are respectively compared with the standard threshold value, and the score transaction guides meeting the standard threshold value are used as standard transaction guides; a second acquisition module that acquiresThe module is used for acquiring a target item as the input of the optimization model, wherein the target item comprises a target item name and a target item guide; the second scoring module is used for scoring the target item guide according to the scoring rule to obtain a target score guide; a matching module for performing matching of the target item name with item names of the m item information; the second comparison module is used for comparing the target score guide with the standard event handling guide under the event information corresponding to the matched event name when the event name is matched to obtain a comparison result; and the recommending module is used for executing an optimizing scheme for recommending the target items according to the comparison result and outputting the optimizing scheme as the optimizing model.
According to the service event optimization device based on the optimization model, by acquiring the m pieces of event information and matching the target event with the event names of the m pieces of event information, events similar to the target event can be quickly, accurately and efficiently matched from a plurality of pieces of event information data; the target item guide is compared with the standard item transaction guide of the similar items of the target item, and item optimization suggestions are provided according to the comparison result, so that manpower and material resources can be saved, and the working efficiency is improved.
Another aspect of the present disclosure provides an electronic device comprising one or more processors and one or more memories, wherein the memories are configured to store executable instructions that, when executed by the processors, implement the method as described above.
According to the electronic equipment disclosed by the embodiment of the disclosure, the items similar to the target item can be quickly, accurately and efficiently matched from a plurality of item information data by acquiring the m item information and matching the target item with the item names of the m item information; the target item guide is compared with the standard item transaction guide of the similar items of the target item, and item optimization suggestions are provided according to the comparison result, so that manpower and material resources can be saved, and the working efficiency is improved.
Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions for implementing the method as described above when executed.
According to the computer-readable storage medium of the embodiment of the disclosure, by acquiring m pieces of event information and matching the target event with the event names of the m pieces of event information, events similar to the target event can be quickly, accurately and efficiently matched from a plurality of pieces of event information data; the target item guide is compared with the standard item transaction guide of the similar items of the target item, and item optimization suggestions are provided according to the comparison result, so that manpower and material resources can be saved, and the working efficiency is improved.
Another aspect of the disclosure provides a computer program product comprising a computer program comprising computer executable instructions for implementing the method as described above when executed.
According to the computer program product of the embodiment of the disclosure, by acquiring m items of event information and matching the target items with the item names of the m items of event information, items similar to the target items can be quickly, accurately and efficiently matched from a plurality of items of event information data; the target item guide is compared with the standard item transaction guide of the similar items of the target item, and item optimization suggestions are provided according to the comparison result, so that manpower and material resources can be saved, and the working efficiency is improved.
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The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments of the present disclosure with reference to the accompanying drawings, in which:
fig. 1 schematically illustrates an exemplary system architecture to which the methods, apparatus, and methods may be applied, in accordance with an embodiment of the present disclosure;
FIG. 2 schematically illustrates a flow chart of a method for optimizing a service transaction based on an optimization model according to an embodiment of the present disclosure;
FIG. 3 schematically illustrates n given to each item information according to a scoring rule according to an embodiment of the disclosureeThe manual of each itemScoring to obtain neA flow chart of a point transaction guide;
FIG. 4 schematically illustrates a flow diagram for scoring a target item guide according to scoring rules, resulting in a target score guide, according to an embodiment of the present disclosure;
FIG. 5 schematically illustrates a flowchart for comparing a target score guide with a standard transaction guide under item information corresponding to a matched item name, resulting in a comparison result, according to an embodiment of the disclosure;
FIG. 6 schematically illustrates a flow chart of an optimization scheme for recommending a target item based on a comparison, according to an embodiment of the present disclosure;
FIG. 7 schematically illustrates a block diagram of an optimization model-based service transaction optimization apparatus, in accordance with an embodiment of the present disclosure;
FIG. 8 schematically shows a block diagram of an electronic device according to an embodiment of the disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.
In the technical scheme of the disclosure, the acquisition, storage, application and the like of the personal information of the related user all accord with the regulations of related laws and regulations, necessary security measures are taken, and the customs of the public order is not violated. In the technical scheme of the disclosure, the data acquisition, collection, storage, use, processing, transmission, provision, disclosure, application and other processing are all in accordance with the regulations of relevant laws and regulations, necessary security measures are taken, and the public order and good custom are not violated.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
Where a convention analogous to "A, B or at least one of C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B or C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). The terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features.
Currently, according to the requirements of national policies, administrative departments in various regions need to continuously promote the optimization of government affairs services in the jurisdiction scope (specifically including running times, time, materials and flow reduction for handling affairs), but because the number of government affair service affairs in various regions of the country is huge, and the content and information structure of the handling guidelines of the government affair service affairs in each region and county of province and city are greatly different, a technical method is lacked at present, different names of single items to be optimized can be rapidly agreed in the country (namely the same handling affair but different laws), and whether optimization space exists in the items or not and a specific optimization suggestion are judged.
If the user wants to judge whether a certain government affair item has an optimized space, at present, only a manual method can be adopted to perform fuzzy matching search from item lists of government affair service networks in all nationalities, then the user can manually judge whether the government affair item is the same item, and then the user can manually see the item and handle the guide to judge whether the government affair item belongs to more optimized items, so that a large amount of manpower and material resources are consumed, and the efficiency is very low.
The embodiment of the disclosure provides a service item optimization method and device based on an optimization model, an electronic device and a computer readable memoryStorage medium and computer program product. The service item optimization method based on the optimization model comprises the following steps: acquiring m transaction information, wherein each transaction information comprises neEach item name and item guide corresponding to each item name, m is an integer of 1 or more, neIs an integer of 1 or more, and e is an integer of 1 or more and m or less; giving n to each item information according to a scoring ruleeThe affair handling guidelines are respectively marked to obtain neA point transaction guide; n is to beeComparing the score transaction guidelines with a standard threshold respectively, and taking the score transaction guideline with the minimum score difference with the standard threshold as a standard transaction guideline; acquiring a target item, wherein the target item comprises a target item name and a target item guide; scoring the target item guide according to a scoring rule to obtain a target score guide; the name of the target item and n of each item informationeMatching item names; when the item names are matched, comparing the target score guide with a standard item transaction guide corresponding to the matched item names to obtain a comparison result; and recommending an optimization scheme of the target items according to the comparison result.
It should be noted that the optimization model-based service item optimization method, apparatus, electronic device, computer-readable storage medium, and computer program product of the present disclosure may be used in the field of big data technology, and may also be used in any field other than the field of big data technology, such as the financial field, and the field of the present disclosure is not limited herein.
FIG. 1 schematically illustrates an exemplary system architecture 100 to which an optimization model-based service item optimization method, apparatus, electronic device, computer-readable storage medium, and computer program product may be applied, according to embodiments of the present disclosure. It should be noted that fig. 1 is only an example of a system architecture to which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, and does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios.
As shown in fig. 1, the system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 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 101, 102, 103 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 105 may be a server providing various services, such as a background management server (for example only) providing support for websites browsed by users using the terminal devices 101, 102, 103. The background management server may analyze and perform other processing on the received data such as the user request, and feed back a processing result (e.g., a webpage, information, or data obtained or generated according to the user request) to the terminal device.
It should be noted that the optimization model-based service item optimization method provided by the embodiment of the present disclosure may be generally executed by the server 105. Accordingly, the service item optimization device based on the optimization model provided by the embodiment of the present disclosure can be generally disposed in the server 105. The optimization model-based service item optimization method provided by the embodiment of the present disclosure may also be performed by a server or a server cluster that is different from the server 105 and is capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Accordingly, the service item optimization device based on the optimization model provided by the embodiment of the present disclosure may also be disposed in a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
The optimization model-based service item optimization method according to the embodiment of the present disclosure will be described in detail below with reference to fig. 2 to 6 based on the scenario described in fig. 1.
FIG. 2 schematically illustrates a flow chart of a method for optimizing a service transaction based on an optimization model according to an embodiment of the present disclosure.
As shown in fig. 2, the optimization model-based service item optimization method of this embodiment includes operations S210 to S280.
In operation S210, m pieces of event information, each of which includes n, are acquired as first parameters of an optimization modeleEach item name and item guide corresponding to each item name, m is an integer of 1 or more, neIs an integer of 1 or more, and e is an integer of 1 or more and m or less. It should be noted that the transaction information may be transaction events of events, such as identity card transaction, technician school approval setup, law firm setup, change, cancellation permission approval, taxi operation permission approval, and the like; the event guide may be an instructional recommendation for the event, such as a transaction time limit, event type, number of runs, net level, and number of material units, and the like.
As some specific examples, the expiration time period may be, but is not limited to, 1 day, 2 days, 3 days, 4 days, etc.; the office type can be instant office and promissory, but is not limited to the instant office and the promissory, namely the event that can be transacted immediately and the promissory waiting for transaction; the number of runs may be 1, 2, 3, 4, etc., but is not limited thereto.
The level of networking may be, but is not limited to, level I, level II, level III, level IV, and the like. The I level can understand that the transaction item realizes information publishing, namely the transaction item can provide detailed and specific transaction guidance, online consultation and complaint channels, but cannot provide online transaction and needs to be submitted on site. Level II can be understood as the transaction having implemented an application material online pre-review. The applicant can submit and correct the related application information and materials through the network, the auditing mechanism carries out pre-auditing on the submitted materials on the platform, after the pre-auditing is passed, the applicant still needs to carry the original materials to be filed, submitted and transacted, after the approval decision is made, the applicant can obtain the result on the site, and can also select a logistics delivery mode to deliver the approval result. The whole handling process should be carried out on site for no more than 2 times.
Level III may be understood as the transaction having implemented an on-line verification of the application material. The applicant can submit and correct the related application information and materials through the network, the materials meet the handling conditions and directly enter the handling program, the applicant can inquire the handling state and the consultation problems on the network, and after the approval decision is made, the applicant needs to check the original materials on site and obtain the approval result after payment. The whole transaction process should be carried out on the site of the hall for no more than 1 time. Level IV may be understood as that the transaction has been completed through the web. The applicant can submit and correct the related application information and materials through the network, the approval mechanism carries out online verification on the submitted materials, the materials directly enter a handling program after the materials are accepted, the applicant can inquire handling states and consultation problems on line, and after approval determination is made, the applicant can deliver approval results through logistics after online payment. The whole process does not need to be handled on site.
Here, 4 items of information, i.e., m is 4, may be obtained by way of example of handling an id card, setting up an approval of a mechanic school, setting up a law firm, changing, canceling an approval, and approving an operation approval of a taxi, wherein the name of each item of information is different due to differences in culture, language, and the like of each administrative area throughout the country, in other words, for different administrative areas, one item of information may include a plurality of item names, and further each item of information may include neThe item name and the item transaction guide corresponding to each item name are understood as that, for the information of transaction of the ID card, some areas are called as applying ID card, and some areas are called as issuing ID card, so that the information of transaction of the ID cardThe next 3 item names, i.e. neAnd 3, a corresponding local item transaction guide is provided for transaction items of each region, namely for each item name of the item information.
In operation S220, a scoring rule is set as a second parameter of the optimization model.
In operation S230, n of each item information is given according to a scoring ruleeThe affair handling guidelines are respectively marked to obtain neAnd (4) point transaction guides. It will be understood that each transaction message includes neEach item name has a corresponding item transaction guide, so each item can include neEach item transaction guide is scored to obtain a corresponding score transaction guide.
As a possible implementation, each event guide includes giIndividual item transaction element, giIs an integer of 1 or more, i is 1 or more and n or lesseIs an integer of (1). For example, the transaction information of the identity card includes 3 transaction names, corresponding to 3 transaction guides, each transaction guide has one or more transaction elements, and the number of the transaction elements in each transaction guide may be the same or different. In other words, the number of transaction elements for transaction guides of 3 transaction guides corresponding to the ID card may be g1、g2And g3According to the actual situation g1May be any integer of 1 or more, g2May be any integer of 1 or more, g3Any integer greater than or equal to 1 may be used.
As shown in FIG. 3, operation S230 assigns n to each item of information according to a scoring ruleeThe affair handling guidelines are respectively marked to obtain neThe point transaction guide includes operation S231.
In operation S231, each item transaction guide is given g according to the scoring ruleiThe item transaction elements are respectively scored until neAll the affair handling guidelines are scored to be finished to obtain neAnd (4) point transaction guides.
Further, giThe individual event elements may include at least one of an event deadline, an event type, a number of runs, a net rating, and a number of material copies, but are not limited thereto.
As some specific examples, the scoring rules may be understood as shown in table 1.
TABLE 1
Figure BDA0003427393480000111
G for handling the guide for each item can be implemented by the scoring rules in Table 1iThe transaction elements are respectively scored to obtain corresponding score transaction guidelines when n iseAfter all the affair handling guidelines are scored, n is obtainedeAnd (4) point transaction guides. Thus, n given to each item information according to the scoring rule can be conveniently implemented through operation S221eThe affair handling guidelines are respectively marked to obtain neAnd (4) point transaction guides.
In operation S240, a criterion threshold is set as a third parameter of the optimization model.
In operation S250, n is addedeThe point transaction guides are respectively compared with the standard threshold value, and the point transaction guides meeting the standard threshold value are taken as standard transaction guides. It is understood that the standard threshold may be set, and the example is continued by handling the identity card, assuming that the standard threshold is set to 40 points, and if the standard threshold is set to be satisfied if the standard threshold is greater than 40 points, it is needless to say that the standard threshold is satisfied if the standard threshold is less than 40 points, and how to define the satisfaction of the standard threshold may be determined according to specific situations, and no limitation is made here.
In this example, the score of the office guidance corresponding to the name "application id" after operation S221 is 20 points, the score of the office guidance corresponding to the name "application id" after operation S221 is 30 points, and the score of the office guidance corresponding to the name "id issuance" after operation S221 is 45 points, so that it is apparent that the office guidance corresponding to the name "id issuance" satisfies the standard threshold, and therefore the office guidance corresponding to the name "id issuance" is used as the standard matter office guidance.
In operation S260, a target item is obtained as an input of the optimization model, wherein the target item includes a target item name and a target item guide. The target items can be understood as items that the user wants to optimize, for example, the identity card transaction process in Zhangzhou city wants to optimize the identity card transaction process in this city, the identity card transaction is the target item in Zhangzhou city, the search keyword of the event that the worker transacts the identity card is the target item name, for example, the target item name is 'transacted identity card', and the transaction guidance suggestion corresponding to the name 'transacted identity card' is the target item guide.
In operation S270, the target item guide is scored according to the scoring rules to obtain a target score guide.
As a possible implementation, the target transaction guide may include r target transaction elements, where r is an integer greater than or equal to 1. Further, the r transaction elements may include at least one of a transaction deadline, a office type, a number of runs, a net level, and a number of material copies, but are not limited thereto.
As shown in fig. 4, operation S270 scores the target item guide according to the scoring rule, and obtaining the target score guide includes operation S271.
In operation S271, the r target transaction elements are scored according to the scoring rule, so as to obtain a target score guideline. Wherein, the scoring rule may be the scoring rule in table 1. The r target transaction elements of the target item guide can be respectively scored according to the scoring rules in table 1 to obtain the target score guide, and thus, the target item guide can be conveniently scored according to the scoring rules to obtain the target score guide through operation S271.
In operation S280, the target transaction name is matched with the transaction names of the m pieces of transaction information. Taking the example of the identity card transaction process in Zhangzhou city which wants to be optimized, the target item name of Zhangzhou city, namely the transaction identity card, is matched with the item names of the m item information, and specifically, the identification can be carried out by identifying keywords in the item names and semantics in the item names.
In operation S290, when the item name is matched, the target score guide is compared with the standard item transaction guide under the item information corresponding to the matched item name, and a comparison result is obtained. It can be understood that, when the item name is matched, the standard item transaction guide in the item information corresponding to the item name may be used as the target object to be targeted by the target point score guide, that is, the target point score guide needs to be compared with the standard item transaction guide to obtain the comparison result.
As a practical matter, when the item name is matched, the r target transaction elements of the target item guide are identical to the gi item transaction elements of the matched standard item transaction guide. As shown in fig. 5, operation S290 compares the target score guide with the standard event transaction guide under the event information corresponding to the matched event name, and obtaining the comparison result includes operation S291.
In operation S291, the score of each target transaction element is compared with the scores of the corresponding transaction elements to obtain r comparison results. Continuing with the description taking the transaction guide corresponding to "id card issuance" as the standard transaction guide, assume that the transaction element "transaction time limit" has a score of 0, the transaction element "transaction type" has a score of 10, the transaction element "running number" has a score of 10, the transaction element "web level" has a score of 10, and the transaction element "material number" has a score of 5. The target office element "office time" is assumed to score 7 points, the target office element "office type" is assumed to score 10 points, the target office element "run number" is assumed to score 2 points, the target office element "web level" is assumed to score 4 points, and the target office element "material share" is assumed to score 5 points. The target transaction element 'transaction time limit' can be compared with the transaction element 'transaction time limit' to obtain a comparison result, the target transaction element 'transaction time limit' is 5 minutes higher than the transaction element 'transaction time limit', the handling type, running times, network handling level and material number are the same, and the details are not repeated.
In operation S300, an optimization scheme of the target item is recommended as an output of the optimization model according to the comparison result.
As one practicable manner, as shown in fig. 6, the operation S300 of recommending an optimization scheme of the target item according to the comparison result as an output of the optimization model includes an operation S301.
In operation S301, an optimization scheme of the corresponding target transaction element is recommended as an output of the optimization model according to each comparison result. As can be seen from operation S291, r comparison results can be obtained by comparing the score of each target transaction element with the score of the corresponding transaction element, and each comparison result shows the difference between the target transaction element and the transaction element, i.e., whether the target transaction element has a higher score than the transaction element or whether the target transaction element has a lower score than the transaction element.
For example, a comparison result that the target transaction element "transaction deadline" is 5 points higher than the transaction element "transaction deadline" may indicate that the target transaction element is more efficient and therefore does not need to be optimized, if the comparison result is that the target transaction element is less efficient than the transaction element, the target transaction element needs to be optimized, and the optimization measure may refer to the transaction element corresponding to the target transaction element so that the optimized target transaction element is the same as the corresponding transaction element, or of course, may exceed the corresponding transaction element and be more efficient than the corresponding transaction element. Thus, it is possible to facilitate implementation of an optimization scheme for recommending a target item according to the comparison result through operation S301.
According to the service item optimization method based on the optimization model, by acquiring the m item information and matching the target item with the item names of the m item information, items similar to the target item can be quickly, accurately and efficiently matched from a plurality of item information data; the target item guide is compared with the standard item transaction guide of the similar items of the target item, and item optimization suggestions are provided according to the comparison result, so that manpower and material resources can be saved, and the working efficiency is improved.
Based on the service item optimization method based on the optimization model, the present disclosure also provides a service item optimization device 100 based on the optimization model. The optimization model-based service event optimization apparatus 100 will be described in detail below with reference to fig. 7.
Fig. 7 schematically shows a block diagram of the service event optimization device 100 based on the optimization model according to the embodiment of the present disclosure.
The optimization model-based service item optimization device 100 comprises a first obtaining module 1, a first scoring module 2, a first comparing module 3, a second obtaining module 4, a second scoring module 5, a matching module 6, a second comparing module 7, a recommending module 8, a first setting module 9 and a second setting module 10.
A first obtaining module 1, where the first obtaining module 1 is configured to perform operation S210: obtaining m item information as a first parameter of an optimization model, wherein each item information comprises neEach item name and item guide corresponding to each item name, m is an integer of 1 or more, neIs an integer of 1 or more, and e is an integer of 1 or more and m or less.
A first setting module 9, configured to perform operation S220: setting a scoring rule as a second parameter of the optimization model;
a first scoring module 2, the first scoring module 2 being configured to perform operation S230: giving n to each item information according to a scoring ruleeThe affair handling guidelines are respectively marked to obtain neAnd (4) point transaction guides.
A second setting module 10, configured to perform operation S240: setting a standard threshold value as a third parameter of the optimization model;
a first comparing module 3, wherein the first comparing module 3 is configured to perform operation S250: n is to beeThe point transaction guides are respectively compared with the standard threshold value, and the point transaction guides meeting the standard threshold value are taken as standard transaction guides.
A second obtaining module 4, where the second obtaining module 4 is configured to perform operation S260: and acquiring the target item, wherein the target item comprises a target item name and a target item guide.
A second scoring module 5, the second scoring module 5 being configured to perform operation S270: and scoring the target item guide according to a scoring rule to obtain a target score guide.
A matching module 6, the matching module 6 being configured to perform operation S280: the target item name is matched with the item names of the m item information.
A second comparing module 7, where the second comparing module 7 is configured to perform operation S290: and when the item names are matched, comparing the target score guide with the standard item transaction guide under the item information corresponding to the matched item names to obtain a comparison result.
A recommending module 8, the recommending module 8 being configured to perform operation S300: and recommending an optimization scheme of the target items according to the comparison result.
Since the service item optimization device 100 based on the optimization model is configured based on the service item optimization method based on the optimization model, the beneficial effects of the service item optimization device 100 based on the optimization model are the same as those of the service item optimization method based on the optimization model, and are not described herein again.
In addition, according to the embodiment of the present disclosure, any plurality of the first obtaining module 1, the first scoring module 2, the first comparing module 3, the second obtaining module 4, the second scoring module 5, the matching module 6, the second comparing module 7, the recommending module 8, the first setting module 9, and the second setting module 10 may be combined and implemented in one module, or any one of them may be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module.
According to the embodiment of the present disclosure, at least one of the first obtaining module 1, the first scoring module 2, the first comparing module 3, the second obtaining module 4, the second scoring module 5, the matching module 6, the second comparing module 7, the recommending module 8, the first setting module 9 and the second setting module 10 may be at least partially implemented as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented by hardware or firmware such as any other reasonable manner of integrating or packaging a circuit, or implemented by any one of three implementation manners of software, hardware and firmware, or by a suitable combination of any of them.
Alternatively, at least one of the first obtaining module 1, the first scoring module 2, the first comparing module 3, the second obtaining module 4, the second scoring module 5, the matching module 6, the second comparing module 7, the recommending module 8, the first setting module 9 and the second setting module 10 may be at least partially implemented as a computer program module, which when executed may perform a corresponding function.
FIG. 8 schematically illustrates a block diagram of an electronic device suitable for implementing an optimization model-based service item optimization method according to an embodiment of the present disclosure.
As shown in fig. 8, an electronic apparatus 900 according to an embodiment of the present disclosure includes a processor 901 which can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)902 or a program loaded from a storage portion 908 into a Random Access Memory (RAM) 903. Processor 901 may comprise, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 901 may also include on-board memory for caching purposes. The processor 901 may comprise a single processing unit or a plurality of processing units for performing the different actions of the method flows according to embodiments of the present disclosure.
In the RAM 903, various programs and data necessary for the operation of the electronic apparatus 900 are stored. The processor 901, the ROM 902, and the RAM 903 are connected to each other through a bus 904. The processor 901 performs various operations of the method flows according to the embodiments of the present disclosure by executing programs in the ROM 902 and/or the RAM 903. Note that the programs may also be stored in one or more memories other than the ROM 902 and the RAM 903. The processor 901 may also perform various operations of the method flows according to embodiments of the present disclosure by executing programs stored in the one or more memories.
Electronic device 900 may also include input/output (I/O) interface 905, input/output (I/O) interface 905 also connected to bus 904, according to an embodiment of the present disclosure. The electronic device 900 may also include one or more of the following components connected to the I/O interface 905: an input portion 906 including a keyboard, a mouse, and the like; an output section 907 including components such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 908 including a hard disk and the like; and a communication section 909 including a network interface card such as a LAN card, a modem, or the like. The communication section 909 performs communication processing via a network such as the internet. The driver 910 is also connected to an input/output (I/O) interface 905 as necessary. A removable medium 911 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 910 as necessary, so that a computer program read out therefrom is mounted into the storage section 908 as necessary.
The present disclosure also provides a computer-readable storage medium, which may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.
According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example but is not limited to: 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), 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 disclosure, 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. For example, according to embodiments of the present disclosure, a computer-readable storage medium may include the ROM 902 and/or the RAM 903 described above and/or one or more memories other than the ROM 902 and the RAM 903.
Embodiments of the present disclosure also include a computer program product comprising a computer program containing program code for performing the method illustrated in the flow chart. The program code is for causing a computer system to perform the methods of the embodiments of the disclosure when the computer program product is run on the computer system.
The computer program performs the above-described functions defined in the system/apparatus of the embodiments of the present disclosure when executed by the processor 901. The systems, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.
In one embodiment, the computer program may be hosted on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted, distributed in the form of a signal on a network medium, and downloaded and installed through the communication section 909 and/or installed from the removable medium 911. The computer program containing program code may be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 909, and/or installed from the removable medium 911. The computer program, when executed by the processor 901, performs the above-described functions defined in the system of the embodiment of the present disclosure. The systems, devices, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.
In accordance with embodiments of the present disclosure, program code for executing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, these computer programs may be implemented using high level procedural and/or object oriented programming languages, and/or assembly/machine languages. The programming language includes, but is not limited to, programming languages such as Java, C + +, python, the "C" language, or the like. The program code may execute entirely on the user computing device, partly on the user device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
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 disclosure. 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.
Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments and/or claims of the present disclosure may be made without departing from the spirit or teaching of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.
The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.

Claims (10)

1. A service item optimization method based on an optimization model is characterized by comprising the following steps:
obtaining m transaction information as a first parameter of the optimization model, wherein each transaction information includes neAn item name and an item guide corresponding to each item name, m is an integer of 1 or more, neIs an integer of 1 or more, and e is an integer of 1 or more and m or less;
setting a scoring rule as a second parameter of the optimization model;
giving n to each item information according to the scoring ruleeRespectively scoring the item handling guide to obtain neA point transaction guide;
setting a standard threshold value as a third parameter of the optimization model;
n is to beeThe score transaction guides are respectively compared with the standard threshold value, and the score transaction guides meeting the standard threshold value are used as standard transaction guides;
acquiring a target item as an input of the optimization model, wherein the target item comprises a target item name and a target item guide;
scoring the target item guide according to the scoring rule to obtain a target score guide;
matching the target item name with the item names of the m item information;
when the item name is matched, comparing the target score guide with the standard item transaction guide under the item information corresponding to the matched item name to obtain a comparison result; and
and recommending the optimization scheme of the target item as the output of the optimization model according to the comparison result.
2. The method of claim 1, wherein each of the transaction guides comprises giIndividual item transaction element, giIs an integer of 1 or more, i is 1 or more and n or lesseAn integer of (d);
the n given to each item information according to the scoring ruleeRespectively scoring the item handling guide to obtain neEach point office guide includes:
(g) providing each item transaction guide with the scoring rulesiThe item transaction elements are respectively scored until neAll the item transaction guidelines are scored to obtain neAnd (4) point transaction guides.
3. The method of claim 2, wherein the gi transaction elements include at least one of a transaction deadline, a office type, a number of runs, a net level, and a number of material copies.
4. The method of claim 2, wherein the target transaction guide includes r target transaction elements, r being an integer greater than or equal to 1,
the scoring the target item guide according to the scoring rule to obtain the target score guide comprises:
and respectively scoring the r target transaction elements according to the scoring rules to obtain a target score guide.
5. A method according to claim 4, wherein the r target transaction elements of the target transaction guide are identical to the gi transaction elements of the matched standard transaction guide when the transaction name is matched,
the comparing the target score guide with the standard item transaction guide under the item information corresponding to the matched item name to obtain a comparison result comprises:
and comparing the score of each target transaction element with the corresponding score of the transaction element to obtain r comparison results.
6. The method of claim 5, wherein recommending the optimization scheme for the target item as the output of the optimization model according to the comparison result comprises:
and recommending the optimization scheme of the corresponding target transaction element as the output of the optimization model according to each comparison result.
7. An optimization model-based service item optimization device, comprising:
a first obtaining module, configured to perform obtaining m event information as a first parameter of the optimization model, where each event information includes neAn item name and an item guide corresponding to each item name, m is an integer of 1 or more, neIs an integer of 1 or more, and e is an integer of 1 or more and m or less;
the first setting module is used for executing setting of a scoring rule as a second parameter of the optimization model;
a first scoring module for executing n for each of the transaction information according to the scoring ruleseRespectively scoring the item handling guide to obtain neA point transaction guide;
a second setting module, configured to perform setting of a standard threshold as a third parameter of the optimization model;
a first comparison module to perform comparing neEach of the score office guides is compared to the standard threshold, and the score office guides meet the standard thresholdThe score handling guide is used as a standard item handling guide;
a second obtaining module, configured to perform obtaining a target item as an input of the optimization model, where the target item includes a target item name and a target item guide;
the second scoring module is used for scoring the target item guide according to the scoring rule to obtain a target score guide;
a matching module for performing matching of the target item name with item names of the m item information;
the second comparison module is used for comparing the target score guide with the standard event handling guide under the event information corresponding to the matched event name when the event name is matched to obtain a comparison result; and
and the recommending module is used for executing an optimizing scheme for recommending the target items according to the comparison result and outputting the optimizing scheme as the optimizing model.
8. An electronic device, comprising:
one or more processors;
one or more memories for storing executable instructions that, when executed by the processor, implement the method of any of claims 1-6.
9. A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, implement a method according to any one of claims 1 to 6.
10. A computer program product comprising a computer program comprising one or more executable instructions which, when executed by a processor, implement a method according to any one of claims 1 to 6.
CN202111584643.1A 2021-12-22 2021-12-22 Service item optimization method, service item optimization device, electronic device, service item optimization medium, and program product Pending CN114239984A (en)

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