A service network point search and recommendation method, device, and storage medium

Abstract

The present application relates to a method, apparatus, and storage medium for searching and recommending service outlets. The method includes the steps of: obtaining multi-source service data; constructing a service outlet knowledge graph based on the multi-source service data; searching for candidate service options according to the service outlet knowledge graph; obtaining the status information of the candidate service options; comprehensively scoring the candidate service options according to the status information; and recommending and dispatching service options according to the comprehensive scoring result. The present application provides real-time recommendations for candidate service outlets in the dispatching of agricultural machinery failures, improves the intelligence level of service outlet dispatching, and effectively reduces the repair time of agricultural machinery failures during the busy farming season.

Description

Technical Field

[0001] This application relates to the field of agricultural activities, and particularly to a method, device, and storage medium for searching and recommending service outlets. Background Art

[0002] With the continuous improvement of the mechanization level of various links in agricultural activities, a large number of different types of agricultural machinery are used in agricultural activities during different busy farming seasons. During the operation process, if the agricultural machinery breaks down and cannot work properly, it may seriously affect the normal development of agricultural activities.

[0003] Currently, the maintenance of agricultural machinery failures is mainly completed through the cooperation between the agricultural machinery after-sales service scheduling center and service outlets. After receiving the fault feedback from customers, the service scheduling center transfers the fault to the service outlets within the agricultural machinery operation area according to the location of the fault and the type of the fault. Finally, the service outlets dispatch service engineers to the fault location for fault repair. In the process of fault transfer, how to select a suitable service outlet becomes an important link affecting the fault repair time.

[0004] Currently, the selection methods of service outlets in the agricultural machinery industry are mostly based on the distribution of the fault location and the location of the service outlets, including: assigning to the service outlets responsible for the fault occurrence area or assigning to the service outlets closest to the fault location. Using the above methods can reduce the complexity of fault assignment by the scheduling center in areas with fewer operating agricultural machinery and during non-busy farming seasons. However, during the busy farming season, when the number of operating agricultural machinery increases significantly, it will affect the overall fault repair time and efficiency in the region.

[0005] Moreover, the above selection methods of service websites do not consider factors such as the agricultural machinery failure and the repair ability of service outlets as well as the working status of existing service personnel. This may lead to the situation that service personnel cannot reach the service site quickly or are not familiar with the fault after arriving at the fault site and cannot repair the fault quickly. Eventually, it will lead to a longer fault repair time and affect the development of agricultural machinery operations. At the same time, the lack of a selection and recommendation method for service outlets based on historical experience and intelligence will also lead to a longer overall fault repair time in each region during the busy farming season. Summary of the Invention

[0006] In order to solve the above technical problems or at least partially solve the above technical problems, this application provides a method, device, and storage medium for searching and recommending service outlets.

[0007] In a first aspect, this application provides a method for searching and recommending service outlets, and the method includes the steps of:

[0008] Obtain multi-source business data;

[0009] Construct a service outlet knowledge graph according to the multi-source business data;

[0010] Search for candidate service options according to the service network knowledge graph;

[0011] Obtain the status information of the candidate service options;

[0012] Conduct a comprehensive evaluation of the candidate service options based on the status information;

[0013] Recommend a dispatching service option according to the comprehensive evaluation result.

[0014] Preferably, the obtaining of multi-source business data includes the steps of:

[0015] Obtain agricultural machinery installation file data;

[0016] Obtain agricultural machinery fault repair dispatching record data;

[0017] Obtain service network data;

[0018] Obtain service personnel data.

[0019] Preferably, the constructing of the service network knowledge graph according to the multi-source business data includes the steps of:

[0020] Obtain the agricultural machinery installation file data in the multi-source business data;

[0021] Construct the structural relationship between agricultural machinery models, agricultural machinery series, agricultural machinery systems, agricultural machinery assemblies and agricultural machinery parts according to the agricultural machinery fault repair dispatching record data.

[0022] Preferably, the constructing of the service network knowledge graph according to the multi-source business data includes the steps of:

[0023] Obtain the agricultural machinery fault repair dispatching record data in the multi-source business data;

[0024] Construct the structural relationship between agricultural machinery parts, service personnel, service networks, and repair time and repair frequency according to the agricultural machinery fault repair dispatching record data.

[0025] Preferably, the constructing of the service network knowledge graph according to the multi-source business data includes the steps of:

[0026] Obtain the service network data and service personnel data in the multi-source business data;

[0027] Construct the association relationship between service personnel and service networks, and between service networks and service regions according to the service network data and the service personnel data.

[0028] Preferably, the searching for candidate service options according to the service network knowledge graph includes the steps of:

[0029] Obtain the knowledge graph of the service network points;

[0030] Obtain search keywords;

[0031] Input the search keywords into the knowledge graph of the service network points;

[0032] Obtain the output feedback of the knowledge graph of the service network points.

[0033] Preferably, the obtaining of the search keywords includes the steps of:

[0034] Obtain candidate regions;

[0035] Obtain the region where the fault occurs;

[0036] Obtain the agricultural machinery model;

[0037] Obtain the agricultural machinery fault parts.

[0038] In a second aspect, the present application provides a service network point search and recommendation device, including:

[0039] A data acquisition module, configured to acquire multi-source service data;

[0040] A graph construction module, configured to construct a knowledge graph of service network points according to the multi-source service data;

[0041] An option search module, configured to search for candidate service options according to the knowledge graph of service network points;

[0042] An information acquisition module, configured to acquire the status information of the candidate service options;

[0043] A comprehensive scoring module, configured to comprehensively score the candidate service options according to the status information;

[0044] An option recommendation module, configured to recommend scheduling service options according to the comprehensive scoring result.

[0045] In a third aspect, there is provided an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0046] The memory is used to store a computer program;

[0047] When the processor is used to execute the program stored in the memory, it implements the steps of the service network point search and recommendation described in any embodiment of the first aspect.

[0048] In a fourth aspect, there is provided a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the service network point search and recommendation described in any embodiment of the first aspect.

[0049] The above technical solutions provided by the embodiments of the present application have the following advantages compared with the prior art:

[0050] A service network search and recommendation method, device, and storage medium provided by the present application integrate agricultural machinery after-sales service data, extract fault repair entities, attributes, and relationships, and establish a relationship graph of agricultural machinery fault repair and service networks. By searching for the direct and indirect relationships between service networks and agricultural machinery faults in the fault knowledge graph spectrum, the repair capabilities of service networks and service personnel for agricultural machinery faults are fully explored. At the same time, based on the real-time scheduling status and location data of service personnel, an analytic hierarchy process is used to establish a service network selection model to evaluate the weight values of the capabilities of service networks, and candidate service networks are recommended in real time for agricultural machinery fault scheduling, improving the intelligence level of service network scheduling and effectively reducing the repair time of agricultural machinery faults during the busy farming season. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present invention and used together with the specification to explain the principles of the present invention.

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0053] Figure 1 is a flowchart showing a service network search and recommendation method provided by an embodiment of the present invention;

[0054] Figure 2 is a structural diagram showing a service network search and recommendation device provided by an embodiment of the present invention;

[0055] Figure 3 is a structural diagram showing an electronic device provided by the present invention;

[0056] Figure 4 is a structural diagram showing a non-transitory computer-readable storage medium provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the following will clearly and completely describe the technical solutions in the embodiments of this application with reference to the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are some, but not all, of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the scope of protection of this application.

[0058] Figure 1 It is a schematic flowchart of a service network point search and recommendation method provided by an embodiment of this application.

[0059] This application provides a service network point search and recommendation method, and the method includes the steps:

[0060] S1: Obtain multi-source service data;

[0061] In the embodiments of this application, the obtaining of multi-source service data includes the steps:

[0062] Obtain agricultural machinery installation file data;

[0063] Obtain agricultural machinery fault repair scheduling record data;

[0064] Obtain service network point data;

[0065] Obtain service personnel data.

[0066] Specifically, the data sources that need to be integrated include agricultural machinery installation file data, agricultural machinery fault repair scheduling record data, service network point data, and service personnel data.

[0067] S2: Construct a service network point knowledge graph according to the multi-source service data;

[0068] In the embodiments of this application, the constructing of a service network point knowledge graph according to the multi-source service data includes the steps:

[0069] Obtain the agricultural machinery installation file data in the multi-source service data;

[0070] Construct the structural relationship between agricultural machinery models, agricultural machinery series, agricultural machinery systems, agricultural machinery assemblies, and agricultural machinery parts according to the agricultural machinery fault repair scheduling record data.

[0071] Specifically, the agricultural machinery installation file is used to construct the structural relationship between agricultural machinery models, agricultural machinery series, agricultural machinery systems / platforms, agricultural machinery assemblies, and agricultural machinery parts.

[0072] In the embodiments of this application, the constructing of a service network point knowledge graph according to the multi-source service data includes the steps:

[0073] Obtain the agricultural machinery fault repair scheduling record data in the multi-source service data;

[0074] Construct the structural relationship among agricultural machinery parts, service personnel, service outlets, repair time, and repair frequency according to the agricultural machinery fault repair scheduling record data.

[0075] Specifically, the agricultural machinery fault repair scheduling record is used to construct the relationship among agricultural machinery parts, service personnel, service outlets, repair time, and frequency.

[0076] In the embodiment of the present application, the construction of the service outlet knowledge graph according to the multi-source service data includes the steps:

[0077] Obtain the service outlet data and service personnel data in the multi-source service data;

[0078] Construct the association relationships among service personnel and service outlets, and between service outlets and service regions according to the service outlet data and the service personnel data.

[0079] Specifically, the service outlet and service personnel data are used to construct the association relationships among service personnel and service outlets, and between service outlets and service regions. Import the constructed knowledge graph relationship data into the open-source knowledge graph database NebulaGraph for storage and management.

[0080] S3: Search for candidate service options according to the service outlet knowledge graph;

[0081] In the embodiment of the present application, the search for candidate service options according to the service outlet knowledge graph includes the steps:

[0082] Obtain the service outlet knowledge graph;

[0083] Obtain the search keyword;

[0084] Input the search keyword into the service outlet knowledge graph;

[0085] Obtain the output feedback of the service outlet knowledge graph.

[0086] Specifically, in the service outlet fault repair relationship graph, search for candidate service outlets and service personnel. Based on the constructed knowledge graph relationship data, use the keyword as the input parameter to construct a service outlet search rule in the NebulaGraph database, and search for service outlets and service personnel that can directly repair the fault and similar faults. The search rule is as follows.

[0087] 1) Search for service outlets that have repaired the faulty machine model and faulty parts.

[0088] 2) Search for service outlets that have not directly repaired the malfunctioning machine models and malfunctioning parts, but have repaired the assemblies, systems / platforms, and agricultural machinery series to which the malfunctioning parts belong.

[0089] 3) Divide the number of repairs into different levels according to the repair proficiency level. The description of the repair proficiency level is as follows:

[0090] Proficiency level Classification standard 0 The number of repairs is 0 times 1 The number of repairs is less than or equal to 10 times 2 The number of repairs is greater than 10 times and less than or equal to 20 times 3 The number of repairs is greater than 20 times

[0091] In the embodiment of the present application, the obtaining of the search keywords includes the steps of:

[0092] Obtain candidate regions;

[0093] Obtain the region where the failure occurred;

[0094] Obtain the agricultural machinery model;

[0095] Obtain the agricultural machinery malfunctioning parts.

[0096] Specifically, the search keywords include candidate regions, the region where the failure occurred, the agricultural machinery model, and the malfunctioning parts. Search for regions geospatially adjacent to the agricultural machinery failure location as the candidate service outlet selection area. Based on the GPS positioning data of the current failure location, use the geospatial relationship API in the open map platform to search for area information within a specified distance. The search distance is defaulted to 100 kilometers, which can basically meet the distribution of service outlets during the busy farming season.

[0097] S4: Obtain the status information of the candidate service options;

[0098] Specifically, according to the above rules, search for data in the knowledge graph database and the relational database respectively, and associate the data with the service outlet as the associated primary key. The example of the result data (A) is as follows:

[0099]

[0100] Query the dispatching status and current positioning location of the service personnel in the candidate service outlets. Estimate the remaining working time of the service personnel based on the average historical failure repair duration of the service personnel; based on the GPS positioning location of the service personnel, use the path planning API of the open map platform to calculate the shortest time for the service personnel to reach the agricultural machinery failure point.

[0101] S5: Conduct a comprehensive evaluation of the candidate service options according to the status information;

[0102] Specifically, a comprehensive score is given to the candidate service outlets. The analytic hierarchy process is used to determine the weight values of each evaluation dimension. The specific process of the evaluation and analysis is as follows: Construct an analytic hierarchy judgment matrix. The matrix contains 7 dimensions, namely: the number of parts failure repairs, the number of parts assembly repairs, the number of agricultural machinery platform repairs, the number of agricultural machinery series repairs, the estimated total repair duration, the estimated arrival duration, and the estimated repair duration. The importance levels among different dimensions are: the number of parts failure repairs > the number of parts assembly repairs > the number of agricultural machinery platform repairs > the number of agricultural machinery series repairs; the estimated total repair duration > the number of parts failure repairs, the estimated total repair duration > the estimated arrival duration, the estimated total repair duration > the estimated repair duration, and the estimated arrival duration = the estimated repair duration. The importance levels are divided as follows:

[0103] Degree of importance Meaning 1 Compared with the two factors, they have the same importance 3 Compared with the two factors, the former is slightly more important than the latter 5 Compared with the two factors, the former is significantly more important than the latter 7 Compared with the two factors, the former is extremely more important than the latter 9 Compared with the two factors, the former is strongly more important than the latter 2，4，6，8 The intermediate value of the above adjacent judgments The reciprocal of 1-9 The importance of comparing the two elements after exchanging their order

[0104]

[0105] The analytic hierarchy judgment matrix (M) satisfies the following properties:

[0106] a i，j > 0

[0107] a i，i = 1

[0108]

[0109] where i < 7, i >= 0, j < 7, j >= 0;

[0110] The weights of each dimension in the criterion layer are calculated using the sum method. The calculation steps are as follows:

[0111] step1: Standardize each column of the matrix to construct a standardized matrix. The standardization method is: element value / sum of the element values in the column where the element is located.

[0112] step2: Sum the standardized elements by row.

[0113] step3: Standardize the sum results to obtain the criterion item weight value matrix (W). The criterion factor weight value diagram is as follows:

[0114]

[0115] Then, the consistency of the weight matrix is verified. The steps are as follows:

[0116] step1: Solve the maximum eigenvalue (λ max ) and the consistency index (CI).

[0117] where n is the number of criterion layer factors, equal to 7.

[0118] λ max = 7.44, CI = 0.07

[0119] Step 2: Calculate the consistency ratio (CR), and the calculation method is as follows.

[0120] Among them, RI is obtained by looking up the table. The number of factors in the criterion layer (matrix order) is 7, and the corresponding RI value is 1.32. The RI value table is as follows:

[0121]

[0122] CR = 0.05, which is less than 0.1, indicating that the weight systems in the judgment matrix (M) are normal and effective.

[0123] Calculate the comprehensive score (R) of each service outlet according to the search results and the weight matrix, R = A × W. The scoring result example is as follows:

[0124] Service network Comprehensive score Service network 1 1.18 Service network 2 2.01 Service network 3 1.86 Service network 4 1.50 Service network 5 1.60 Service network 6 1.81

[0125] S6: Recommend a scheduling service option according to the comprehensive scoring result.

[0126] Specifically, sort the service outlet scores in descending order for the service scheduling center to make scheduling decisions.

[0127] Such as Figure 2 , this application provides a service outlet search and recommendation device, including:

[0128] A data acquisition module 10, configured to acquire multi-source service data;

[0129] A knowledge graph construction module 20, configured to construct a service outlet knowledge graph according to the multi-source service data;

[0130] An option search module 30, configured to search for candidate service options according to the service outlet knowledge graph;

[0131] An information acquisition module 40, configured to acquire the status information of the candidate service options;

[0132] A comprehensive scoring module 50, configured to comprehensively score the candidate service options according to the status information;

[0133] An option recommendation module 60, configured to recommend a scheduling service option according to the comprehensive scoring result.

[0134] The service outlet search and recommendation device provided by this application can execute the service outlet search and recommendation method provided in the above steps.

[0135] It should be understood that the above specific embodiments of the present invention are only used for exemplary illustration or explanation of the principles of the present invention, and do not constitute a limitation on the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc. made without departing from the spirit and scope of the present invention shall be included within the protection scope of the present invention. In addition, the appended claims of the present invention are intended to cover all variations and modifications that fall within the scope and boundaries of the appended claims, or equivalent forms of such scope and boundaries.

[0136] Reference is now made to Figure 3 , which shows a schematic structural diagram of an electronic device 100 suitable for implementing the embodiments of the present disclosure. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The electronic device shown is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present disclosure.

[0137] As Figure 3 shown, the electronic device 100 may include a processing device (such as a central processing unit, a graphics processing unit, etc.) 101, which may perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 102 or a program loaded from a storage device 108 into a random access memory (RAM) 103. In the RAM 103, various programs and data required for the operation of the electronic device 100 are also stored. The processing device 101, the ROM 102, and the RAM 103 are connected to each other through a bus 104. An input / output (I / O) interface 105 is also connected to the bus 104.

[0138] Generally, the following devices may be connected to the I / O interface 105: an input device 106 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 107 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 108 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 109. The communication device 109 may allow the electronic device 100 to communicate with other devices wirelessly or wiredly to exchange data. Although the figure shows an electronic device 100 having various devices, it should be understood that it is not required to implement or include all the shown devices. More or fewer devices may be alternatively implemented or included.

[0139] In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present disclosure includes a computer program product that includes a computer program carried on a computer-readable medium, and the computer program includes program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 109, or installed from the storage device 108, or installed from the ROM 102. When the computer program is executed by the processing device 101, the above-mentioned functions defined in the methods of the embodiments of the present disclosure are executed.

[0140] Reference is made below to Figure 4 , which shows a schematic structural diagram of a computer-readable storage medium suitable for implementing the embodiments of the present disclosure. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it can implement the service network search and recommendation method described in any of the above.

[0141] A service network search and recommendation method, device, and storage medium provided by the present application integrate agricultural machinery after-sales service data, extract fault repair entities, attributes, and relationships, and establish a relationship map of agricultural machinery fault repair and service networks. By searching for the direct and indirect relationships between service networks and agricultural machinery faults in the fault knowledge graph spectrum, the repair capabilities of service networks and service personnel for agricultural machinery faults are fully explored. At the same time, based on the real-time scheduling status and location data of service personnel, an analytic hierarchy process is used to establish a service network selection model, evaluate the weight values of the capabilities of service networks, and recommend candidate service networks in real time for agricultural machinery fault scheduling, improving the intelligence level of service network scheduling and effectively reducing the repair time of agricultural machinery faults during the busy farming season.

[0142] It should be noted that in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.

[0143] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features claimed herein.

Claims

1. A service network search and recommendation method, characterized in that, The method includes the steps of: Obtain multi-source business data; Construct a service network knowledge graph based on the multi-source business data; Search for candidate service options according to the service network knowledge graph; Obtain the status information of the candidate service options; Conduct a comprehensive scoring of the candidate service options according to the status information; Recommend a scheduling service option according to the comprehensive scoring result; The step of constructing a service network knowledge graph according to the multi-source business data includes the steps of: Obtain the agricultural machinery installation file data in the multi-source business data; Construct the structural relationship between agricultural machinery models, agricultural machinery series, agricultural machinery systems, agricultural machinery assemblies, and agricultural machinery parts according to the agricultural machinery installation file data; The step of constructing a service network knowledge graph according to the multi-source business data includes the steps of: Obtain the agricultural machinery fault repair scheduling record data in the multi-source business data; Construct the structural relationship between agricultural machinery parts, service personnel, service networks, repair time, and repair times according to the agricultural machinery fault repair scheduling record data; The step of constructing a service network knowledge graph according to the multi-source business data includes the steps of: Obtain the service network data and service personnel data in the multi-source business data; Construct the association relationship between service personnel and service networks, and between service networks and service regions according to the service network data and the service personnel data.

2. The service outlet search and recommendation method according to claim 1, wherein The step of searching for candidate service options according to the service network knowledge graph includes the steps of: Obtain the service network knowledge graph; Obtain search keywords; Input the search keywords into the service network knowledge graph; Obtain the output feedback of the service network knowledge graph.

3. The service outlet search and recommendation method according to claim 2, wherein The step of obtaining search keywords includes the steps of: Obtain candidate regions; Obtain the region where the fault occurs; Obtain the agricultural machinery model; Obtain the agricultural machinery fault parts.

4. A service network search and recommendation device for the method according to any one of claims 1-3, characterized in that, Includes: A data acquisition module for obtaining multi-source business data; A graph construction module for constructing a service network knowledge graph according to the multi-source business data; An option search module for searching for candidate service options according to the service network knowledge graph; An information acquisition module for obtaining the status information of the candidate service options; A comprehensive scoring module for comprehensively scoring the candidate service options according to the status information; An option recommendation module for recommending a scheduling service option according to the comprehensive scoring result.

5. An electronic device, characterized in that, Includes a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus; The memory is used to store computer programs; When the processor is used to execute the programs stored on the memory, it realizes the steps of the service network search and recommendation method described in any one of claims 1-3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it realizes the steps of the service network search and recommendation method described in any one of claims 1-3.

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