Work order processing methods, devices, electronic equipment and computer program products

Abstract

This application relates to the field of IT applications and provides a work order workflow method, apparatus, electronic device, and computer program product. The method includes: acquiring historical work orders containing processing departments and recorded text; segmenting the recorded text into words to obtain a target vocabulary set; calculating the information content of each word in the target vocabulary set; determining keywords in the target vocabulary set based on the information content; determining keyword groups corresponding to each historical work order based on the keywords, and the mapping relationship between each keyword group and each processing department; receiving work orders to be workflowd; determining the target department corresponding to each work order to be workflowd based on the mapping relationships; and workflowing the work order to be workflowd to the target department. The work order workflow method provided by this application reduces the cost and improves the efficiency of work order workflow.

Description

Technical Field

[0001] This application relates to the field of IT applications, specifically to a work order processing method, device, electronic equipment, and computer program product. Background Technology

[0002] Currently, during after-sales service, customer service personnel frequently receive user feedback and forward it to the relevant departments in the form of work orders. In the existing process, the transfer of work orders to the corresponding departments is usually done manually. This requires customer service personnel to record the user's problem to form a work order, and then transfer the work order to the corresponding department based on experience. While voice recognition can now automatically generate work orders, the work orders still require manual transfer, which undoubtedly increases the cost and reduces the efficiency of work order transfer. Summary of the Invention

[0003] This application provides a work order processing method, apparatus, electronic device, and computer program product to solve the technical problems of high cost and low efficiency in existing work order processing.

[0004] In a first aspect, embodiments of this application provide a work order workflow method, including:

[0005] Obtain historical work orders containing processing departments and record text, and perform word segmentation on the record text to obtain a target vocabulary set;

[0006] Calculate the information content of each word in the target vocabulary set, and determine the keywords in the target vocabulary set based on the information content;

[0007] Based on the keywords, determine the keyword groups corresponding to each of the historical work orders, and the mapping relationship between each keyword group and each of the processing departments;

[0008] Receive work orders to be transferred, determine the target department corresponding to the work orders to be transferred according to the mapping relationships, and transfer the work orders to be transferred to the target department.

[0009] In one embodiment, the step of segmenting the recorded text to obtain a target vocabulary set includes:

[0010] The recorded text is segmented according to the maximum number of characters corresponding to the preset maximum matching method to obtain segmented text;

[0011] If the preset vocabulary contains the segmented text, the segmented text will be used as the segmented vocabulary.

[0012] If the preset dictionary does not contain the segmented text, the number of characters in the segmented text is reduced, and the segmented text with the reduced number of characters is used as the new segmented text.

[0013] Once the recorded text is segmented, a target vocabulary set containing the segmented words is obtained.

[0014] In one embodiment, the step of calculating the information content of each word in the target vocabulary set includes:

[0015] Calculate the proportion of each word in the target vocabulary set;

[0016] Based on a preset algorithm and the proportion of each word in the target vocabulary set, the information content of each word in the target vocabulary set is calculated, wherein the preset algorithm is Y = -log2P, P is the proportion of each word in the target vocabulary set, and Y is the information content of each word in the target vocabulary set.

[0017] In one embodiment, the step of determining the keywords in the target vocabulary set based on the amount of information includes:

[0018] Determine the first and second words in the target vocabulary set, wherein the information content of the first word is greater than or equal to a preset threshold, and the information content of the second word is less than the preset threshold;

[0019] Identify target words that are included in both the second vocabulary and the preset special business vocabulary, and use the first vocabulary and the target vocabulary as keywords.

[0020] In one embodiment, the step of determining the keyword groups corresponding to each of the historical work orders based on the keywords, and the mapping relationship between each keyword group and each of the processing departments, includes:

[0021] An initial word group is determined based on a preset iterative algorithm and the keywords, and an initial mapping between the initial word group and each of the processing departments is determined.

[0022] The initial mapping is verified according to a preset simulation matching algorithm. Based on the verification results, the keyword groups corresponding to each historical work order and the mapping relationship between each keyword group and each processing department are determined.

[0023] In one embodiment, the step of determining the target department corresponding to the work order to be transferred based on the mapping relationships includes:

[0024] The first phrase corresponding to the work order to be processed is determined based on the mapping relationships described above.

[0025] Calculate the frequency of occurrence of the first phrase in each of the aforementioned mapping relationships;

[0026] Determine the target mapping corresponding to the highest frequency of occurrence, and take the department corresponding to the target mapping as the target department.

[0027] In one embodiment, after the step of calculating the frequency of occurrence of the first phrase in each of the mapping relationships, the method includes:

[0028] When there are multiple occurrence frequencies, a target frequency whose dispersion among the occurrence frequencies meets a preset condition is determined;

[0029] The pending work order is transferred to the department corresponding to the target frequency, and the processing result is received from the department corresponding to the target frequency.

[0030] The historical work order is updated based on the processing result.

[0031] Secondly, embodiments of this application provide a work order processing device, comprising:

[0032] The word segmentation module is used to obtain historical work orders containing processing departments and record text, and to segment the record text to obtain a target vocabulary set.

[0033] The information content calculation module is used to calculate the information content of each word in the target vocabulary set and determine the keywords in the target vocabulary set based on the information content.

[0034] The mapping relationship determination module is used to determine the keyword groups corresponding to each of the historical work orders based on the keywords, and the mapping relationship between each keyword group and each of the processing departments;

[0035] The work order transfer module is used to receive work orders to be transferred, determine the target department corresponding to the work order to be transferred according to the mapping relationship, and transfer the work order to be transferred to the target department.

[0036] Thirdly, embodiments of this application provide an electronic device, including a processor and a memory storing a computer program, wherein the processor executes the computer program to implement the steps of the work order flow method described in the first aspect.

[0037] Fourthly, embodiments of this application provide a computer program product, including a computer program, which, when executed by a processor, implements the steps of the work order flow method described in the first aspect.

[0038] The work order processing method, apparatus, electronic device, and computer program product provided in this application, through word segmentation and vocabulary information calculation of historical work orders, determine the keyword groups of each historical work order and the mapping relationship between the keyword groups and each processing department. When a work order to be processed is received, the keyword groups of the work order to be processed are obtained, and the target department for processing the work order to be processed is determined according to the mapping relationship. This realizes the automatic establishment of the mapping relationship between the work order to be processed and the processing department, reduces the cost of work order processing, and improves the efficiency of work order processing. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is one of the flowcharts illustrating the work order workflow method provided in the embodiments of this application;

[0041] Figure 2 This is the second flowchart of the work order transfer method provided in the embodiments of this application;

[0042] Figure 3 This is a schematic diagram of the work order processing device provided in the embodiments of this application;

[0043] Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0045] Reference Figure 1 , Figure 1 This is one of the flowcharts illustrating the work order workflow method in this application. The work order workflow method provided in this application may include:

[0046] Step S100: Obtain historical work orders containing processing departments and recorded text, and perform word segmentation on the recorded text to obtain a target vocabulary set;

[0047] Specifically, historical work orders containing textual content such as user reports, complaints, and suggestions are obtained, and each historical work order corresponds to a specific department that handles it. The textual content of user reports, complaints, and suggestions constitutes the recorded text in this embodiment. Recorded text can be generated by recognizing the user's speech or by the user manually filling in a format that includes business type, location, and description. After obtaining the historical work orders, the recorded text is segmented to obtain a target vocabulary set containing the relevant words. Extracting the vocabulary from the recorded text allows for further determination of the relationship between the work order and the handling department.

[0048] Step S200: Calculate the information content of each word in the target vocabulary set, and determine the keywords in the target vocabulary set based on the information content;

[0049] Specifically, information theory posits that words with lower occurrence probabilities contain greater information and have a stronger relationship with the target classification. Therefore, the importance of different words in a work order can be determined by calculating their information content. When calculating the occurrence probability of a word, if the number of historical work orders is used as the divisor, duplicate words in a single work order should be removed, retaining only one duplicate word. If the total number of words obtained after word segmentation is used as the divisor, duplicate words in a single work order do not need to be removed. The lower the occurrence probability of a word, the greater its corresponding information content. Words with information content greater than a certain value in the target word set are selected as keywords.

[0050] Step S300: Determine the keyword groups corresponding to each of the historical work orders based on the keywords, and the mapping relationship between each keyword group and each of the processing departments;

[0051] Specifically, after determining the keywords in the target vocabulary set based on the amount of information, the keyword groups corresponding to each historical work order are further determined. That is, the combination of words that belong to the keywords in the record text of each historical work order. The number of keywords corresponding to each historical work order can be different. After determining the keyword groups corresponding to each historical work order, a mapping relationship between the keyword groups of each historical work order and the processing department of each historical work order is established. The mapping relationship reflects the association between the processing department and the keywords, so as to determine the processing department of the work order that needs to be processed by obtaining the keywords.

[0052] Step S400: Receive the work order to be transferred, determine the target department corresponding to the work order to be transferred according to the mapping relationship, and transfer the work order to be transferred to the target department.

[0053] Specifically, after determining the mapping relationship between the keyword groups corresponding to each historical work order and the processing departments corresponding to each historical work order, the work orders to be processed (i.e., the work orders to be transferred in this embodiment) are received. The recorded text in the work orders to be transferred is segmented to obtain some words. Then, through the target word set, the information content of these words is calculated so as to determine the keywords in these words as the keyword groups corresponding to the work orders to be transferred. It is known that the mapping relationship corresponding to each historical work order consists of keyword groups and processing departments. The keyword groups corresponding to the work orders to be transferred are compared with the keyword groups in each mapping relationship to determine the target mapping relationship in each mapping relationship. Among them, the keyword groups in the target mapping relationship have the highest matching degree with the keyword groups corresponding to the work orders to be transferred. The processing department in the target mapping relationship is taken as the target department corresponding to the work orders to be transferred, and the work orders to be transferred are transferred to the target department, thereby realizing the automatic transfer of work orders, reducing the cost of work order transfer, and improving the efficiency of work order transfer.

[0054] This embodiment performs word segmentation and vocabulary information calculation on historical work orders to determine the keyword groups for each historical work order, as well as the mapping relationship between the keyword groups and each processing department. When a work order to be transferred is received, the keyword groups of the work order to be transferred are obtained, and the target department for processing the work order to be transferred is determined according to the mapping relationship. This realizes the automatic establishment of the mapping relationship between the work order to be transferred and the processing department, reduces the cost of work order transfer, and improves the efficiency of work order transfer.

[0055] In one embodiment, the work order workflow method provided in this application may further include:

[0056] Step S101: Segment the recorded text according to the maximum number of characters corresponding to the preset maximum matching method to obtain segmented text;

[0057] Step S102: If the preset dictionary contains the segmented text, the segmented text is used as the segmented vocabulary.

[0058] Step S103: If the preset dictionary does not contain the segmented text, reduce the number of characters in the segmented text and use the segmented text with the reduced number of characters as the new segmented text;

[0059] Step S104: After the recorded text is segmented, a target vocabulary set containing the segmented words is obtained.

[0060] Specifically, the recorded text could be "Underground parking garage in Shanghai New City, Yangpu District, my phone has no signal". In this embodiment, the preset maximum matching algorithm can be the forward maximum matching algorithm, which has a maximum character count of 5. The recorded text is segmented according to the maximum character count of the preset maximum matching algorithm to obtain the segmented text "Yangpu District Shanghai". Then, it is determined whether the preset vocabulary contains the segmented text "Yangpu District Shanghai". If the preset vocabulary does not contain the segmented text "Yangpu District Shanghai", the number of characters in the segmented text "Yangpu District Shanghai" is reduced to obtain the new segmented text "Yangpu District Shang". Then, it is repeatedly determined whether the preset vocabulary contains the new segmented text "Yangpu District Shang" until the new segmented text "Yangpu District" is obtained. If the preset vocabulary contains the new segmented text "Yangpu District", the new segmented text "Yangpu District" is used as the segmented word. Then, the remaining recorded text "Underground parking garage in Shanghai New City, my phone has no signal" is segmented according to the maximum character count until all recorded text is segmented, resulting in a target vocabulary set containing the segmented words "Yangpu District, Shanghai New City, underground parking garage, phone, always, no signal". Before segmenting the recorded text, this embodiment can perform preliminary processing on the recorded text to improve the accuracy of word segmentation. For example, the recorded text "no signal" can be changed to "no signal" to prevent "no signal" from being segmented into the two words "no, signal".

[0061] This embodiment segments the recorded text using a preset maximum matching method, thereby obtaining a more accurate target vocabulary set for words related to the acquisition and processing departments, and thus improving the accuracy of work order flow.

[0062] In one embodiment, the work order workflow method provided in this application may further include:

[0063] Step S201: Calculate the proportion of each word in the target vocabulary set;

[0064] Step S202: Calculate the information content of each word in the target vocabulary set according to the preset algorithm and the proportion of each word in the target vocabulary set, wherein the preset algorithm is Y = -log2P, P is the proportion of each word in the target vocabulary set, and Y is the information content of each word in the target vocabulary set.

[0065] Specifically, the information content of each word in the target vocabulary set is inversely proportional to the proportion of each word in the target vocabulary set. Specifically, the first step is to calculate the proportion of each word in the target vocabulary set by dividing the frequency of each word's occurrence by the total vocabulary size of the target vocabulary set. For example, if word 'a' in the target vocabulary set accounts for 33%, the preset algorithm in this embodiment, i.e., the formula for calculating the information content of each word, can be: Y = -log2P, where P is the proportion of each word in the target vocabulary set, and Y is the information content of each word in the target vocabulary set. Substituting P equal to 33% into the formula, we get Y = 1.585. If P is 0.01, then substituting P equal to 0.01 into the formula, we get Y = 6.6439. It can be seen that when P decreases, Y increases, further illustrating that the information content is inversely proportional to the proportion.

[0066] This embodiment calculates the information content of each word in the target vocabulary set to more accurately obtain keywords that are relevant to the processing department, thereby improving the accuracy of work order flow.

[0067] In one embodiment, the work order workflow method provided in this application may further include:

[0068] Step S203: Determine the first word and the second word in the target word set, wherein the information content of the first word is greater than or equal to a preset threshold, and the information content of the second word is less than the preset threshold;

[0069] Step S204: Determine the target words that are included in both the second vocabulary and the preset special business vocabulary, and use the first vocabulary and the target words as keywords.

[0070] Specifically, to better match the keywords in the target vocabulary set with actual business operations, in addition to determining the keywords in the target vocabulary set through information content, a special business vocabulary library can also be preset. First, determine the first and second words in the target vocabulary set, where the information content of the first word is greater than or equal to a preset threshold, and the information content of the second word is less than the preset threshold. That is, the second word is a word in the target vocabulary set other than the first word. Then, determine the target words that are included in both the second word and the preset special business vocabulary library. Then, use the first word and the target words as keywords. The second word with less information content may also contain professional terms related to specific business operations, such as "SMS", "ringtone", "fiber optic cable", etc., which can directly reflect the business type or fault phenomenon. These words may be regarded as non-keywords because they appear frequently. However, the preset special business vocabulary library in this embodiment contains professional terms related to specific business operations.

[0071] This embodiment improves the applicability of the work order transfer method of this application by introducing a preset special business terminology library and information volume as the judgment rules for keywords.

[0072] In one embodiment, the work order workflow method provided in this application may further include:

[0073] Step S301: Determine an initial word group based on a preset iterative algorithm and the keywords, and determine the initial mapping between the initial word group and each of the processing departments;

[0074] Step S302: Verify the initial mapping according to the preset simulation matching algorithm, and determine the keyword group corresponding to each historical work order and the mapping relationship between each keyword group and each processing department according to the verification result.

[0075] Specifically, after obtaining the keywords, since it's initially unclear how many keywords need to be selected for the mapping to obtain a reasonable dispatch rule and guide the actual work order flow, this embodiment uses a preset iterative algorithm to first determine a small range of keywords, such as two. Then, it verifies the case where the same keyword combination corresponds to multiple different target objects. The verification method can be a preset simulation matching algorithm, which simulates work orders using the dispatch rule and the preset simulation matching algorithm. The simulated work orders are then automatically routed to obtain the accuracy and effectiveness of work order flow. If the accuracy and effectiveness are low, the range of keywords is further expanded until a higher accuracy and effectiveness of work order flow is obtained, thus determining the number of keywords, for example, three. After determining the number of keywords, the keyword groups corresponding to each historical work order and the mapping relationship between each keyword group and each processing department can be determined.

[0076] This embodiment uses a preset iterative algorithm and a preset simulation matching algorithm to determine the keyword groups corresponding to each historical work order and the mapping relationship between each keyword group and each processing department, thereby realizing the automatic establishment of the mapping relationship between the work orders to be processed and the processing departments, reducing the cost of work order processing and improving the efficiency of work order processing.

[0077] Reference Figure 2 , Figure 2 This is a second flowchart illustrating the work order workflow method in this application. In one embodiment, the work order workflow method provided in this application may further include:

[0078] Step S401: Determine the first phrase corresponding to the work order to be processed according to the mapping relationships described above;

[0079] Specifically, firstly, the number of keywords corresponding to each mapping relationship is obtained. Then, the keywords in the record text of the work order to be processed are determined using the method described above. If the number of keywords corresponding to the work order to be processed is less than or equal to the number of keywords corresponding to each mapping relationship, the keywords corresponding to the work order to be processed are directly added to the first phrase corresponding to the work order to be processed. If the number of keywords corresponding to the work order to be processed is greater than the number of keywords corresponding to each mapping relationship, the keywords corresponding to the work order to be processed are selected with the same number of keywords as those corresponding to each mapping relationship and added to the first phrase corresponding to the work order to be processed.

[0080] Step S402: Calculate the frequency of occurrence of the first phrase in each of the mapping relationships;

[0081] Specifically, the same keyword combination may correspond to multiple different processing departments. That is, there may be multiple mapping relationships containing the first word. For example, if the first word is "Songjiang Road, No. 38, no signal", in each mapping relationship, the first word corresponds to the first processing department, the second processing department, and the third processing department. Among them, there are 3 first mapping relationships between the first word and the first processing department, 2 second mapping relationships between the first word and the second processing department, and 1 third mapping relationship between the first word and the third processing department. Then, the frequency of the first word corresponding to the first mapping relationship is 50%, the frequency of the first word corresponding to the second mapping relationship is 33%, and the frequency of the first word corresponding to the third mapping relationship is 16.7%.

[0082] Step S403: Determine the target mapping corresponding to the highest frequency of occurrence, and take the department corresponding to the target mapping as the target department.

[0083] Specifically, the target mapping corresponding to the highest frequency of occurrence is determined as the first mapping relationship mentioned above, and the department corresponding to the target mapping is taken as the target department, that is, the first processing department mentioned above.

[0084] This embodiment obtains the keyword group corresponding to the work order to be processed, i.e., the first word group, and then determines the frequency of occurrence of the first word group corresponding to each mapping relationship. The department corresponding to the target mapping with the highest frequency is taken as the target department, thereby realizing the automatic establishment of the mapping relationship between the work order to be processed and the processing department, reducing the cost of work order processing and improving the efficiency of work order processing.

[0085] In one embodiment, the work order workflow method provided in this application may further include:

[0086] Step S404: When there are multiple occurrence frequencies, determine the target frequency among the occurrence frequencies whose dispersion meets the preset conditions;

[0087] Step S405: Transfer the work order to be processed to the department corresponding to the target frequency, and receive the processing result from the department corresponding to the target frequency;

[0088] Step S406: Update the historical work order based on the processing result.

[0089] Specifically, there may be multiple mapping relationships containing the first phrase. This is likely because, during the actual processing of these work orders, objective factors may influence their handling, ultimately resulting in different processing departments handling them. These objective factors include a large number of work orders pending in each department and departmental adjustments. Therefore, it is necessary to filter all mapping relationships containing the first phrase. If there are 10 mapping relationships containing the first phrase, and three different processing departments (processing department b, processing department c, and processing department d), then processing department b corresponds to 5 mapping relationships, with a frequency of 50%; processing department c corresponds to 4 mapping relationships. There are 100 work orders with a frequency of 40%, and the corresponding mapping relationship of processing department d is 10%. When there are multiple frequencies, the target frequencies that meet the preset conditions in terms of dispersion are determined, namely, frequencies of 50% and 40%. Then, the work orders to be processed are transferred to the departments corresponding to the target frequencies, namely processing departments b and c. Then, the processing results fed back by processing departments b and c are received, and the historical work orders are updated according to the processing results fed back by processing departments b and c. If processing department b reports processing, the work orders to be transferred with the first phrase and the mapping relationship with processing department b are saved to the historical work orders.

[0090] The purpose of the above process is to prevent the occurrence of too many objective factors during the processing of historical work orders. For example, the content of the first phrase corresponding to the work order to be transferred is to be processed by processing department c. However, due to many objective factors, the mapping relationship between the first phrase and processing department b occurs the most times. Transferring the work order to be processed to multiple departments corresponding to mapping relationships with similar frequencies helps to reduce the impact of objective factors. Specifically, the work order to be processed can also be transferred to all departments corresponding to mapping relationships to eliminate the impact of objective factors.

[0091] This embodiment helps reduce the impact of objective factors by routing work orders to multiple departments with similar frequency of occurrence, thereby accurately establishing the mapping relationship between work orders and processing departments, reducing the cost of work order routing, and improving the efficiency of work order routing.

[0092] refer to Figure 3 , Figure 3This is a schematic diagram of the work order processing device in the embodiments of this application. The work order processing device provided in the embodiments of this application is described below. The work order processing device described below and the work order processing method described above can be referred to in correspondence.

[0093] The word segmentation module is used to obtain historical work orders containing processing departments and record text, and to segment the record text to obtain a target vocabulary set.

[0094] The information content calculation module is used to calculate the information content of each word in the target vocabulary set and determine the keywords in the target vocabulary set based on the information content.

[0095] The mapping relationship determination module is used to determine the keyword groups corresponding to each of the historical work orders based on the keywords, and the mapping relationship between each keyword group and each of the processing departments;

[0096] The work order transfer module is used to receive work orders to be transferred, determine the target department corresponding to the work order to be transferred according to the mapping relationship, and transfer the work order to be transferred to the target department.

[0097] It is known that the word segmentation module includes:

[0098] The text segmentation unit is used to segment the recorded text according to the maximum number of characters corresponding to the preset maximum matching method to obtain segmented text;

[0099] The segmentation word determination unit is used to identify the segmented text as segmented words when the preset word library contains the segmented text.

[0100] The character count reduction unit is used to reduce the character count of the segmented text when the preset dictionary does not contain the segmented text, and to use the segmented text with the reduced character count as the new segmented text.

[0101] The target vocabulary set acquisition unit is used to obtain a target vocabulary set containing the segmented vocabulary after the recorded text is segmented.

[0102] It is known that the information calculation module includes:

[0103] A proportion calculation unit is used to calculate the proportion of each word in the target vocabulary set;

[0104] The information content calculation unit is used to calculate the information content of each word in the target vocabulary set according to a preset algorithm and the proportion of each word in the target vocabulary set. The preset algorithm is Y = -log2P, where P is the proportion of each word in the target vocabulary set and Y is the information content of each word in the target vocabulary set.

[0105] It is understood that the information calculation module further includes:

[0106] A vocabulary determination unit is used to determine a first vocabulary and a second vocabulary in the target vocabulary set, wherein the information content of the first vocabulary is greater than or equal to a preset threshold, and the information content of the second vocabulary is less than the preset threshold.

[0107] The keyword determination unit is used to determine the target words that are included in both the second word and the preset special business terminology library, and to use the first word and the target words as keywords.

[0108] It is understood that the mapping relationship determination module includes:

[0109] An initial mapping determination unit is used to determine an initial word group based on a preset iterative algorithm and the keywords, and to determine the initial mapping between the initial word group and each of the processing departments;

[0110] The verification unit is used to verify the initial mapping according to a preset simulation matching algorithm, and to determine the keyword group corresponding to each historical work order and the mapping relationship between each keyword group and each processing department based on the verification result.

[0111] It is known that the work order workflow module includes:

[0112] The first phrase determination unit is used to determine the first phrase corresponding to the work order to be processed based on the mapping relationships described above.

[0113] A frequency calculation unit is used to calculate the frequency of occurrence of the first word group in each of the mapping relationships;

[0114] The target department determination unit is used to determine the target mapping corresponding to the highest frequency of occurrence, and to take the department corresponding to the target mapping as the target department.

[0115] It is understood that the work order processing device further includes:

[0116] The target frequency determination module is used to determine the target frequency whose dispersion meets a preset condition when there are multiple occurrence frequencies.

[0117] The processing result receiving module is used to transfer the work order to be processed to the department corresponding to the target frequency and receive the processing result fed back by the department corresponding to the target frequency;

[0118] The historical work order update module is used to update the historical work orders based on the processing results.

[0119] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4As shown, the electronic device may include a processor 410, a communication interface 420, a memory 430, and a communication bus 440. The processor 410, communication interface 420, and memory 430 communicate with each other via the communication bus 440. The processor 410 can call the computer program in the memory 430 to execute the steps of the work order processing method.

[0120] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0121] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the steps of the work order flow method provided in the above embodiments.

[0122] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0123] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0124] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A work order flow method, characterized in that, include: Obtain historical work orders containing processing departments and record text, and perform word segmentation on the record text to obtain a target vocabulary set; Calculate the information content of each word in the target vocabulary set, and determine the keywords in the target vocabulary set based on the information content; Based on the keywords, determine the keyword groups corresponding to each of the historical work orders, and the mapping relationship between each keyword group and each of the processing departments; Receive a work order to be transferred, determine the target department corresponding to the work order to be transferred according to the mapping relationship, and transfer the work order to be transferred to the target department; The step of segmenting the recorded text to obtain the target vocabulary set includes: The recorded text is segmented according to the maximum number of characters corresponding to the preset maximum matching method to obtain segmented text; If the preset vocabulary contains the segmented text, the segmented text will be used as the segmented vocabulary. If the preset dictionary does not contain the segmented text, the number of characters in the segmented text is reduced, and the segmented text with the reduced number of characters is used as the new segmented text. Once the recorded text is segmented, a target vocabulary set containing the segmented words is obtained; The steps of determining the keyword groups corresponding to each of the historical work orders based on the keywords, and the mapping relationship between each keyword group and each of the processing departments, include: An initial word group is determined based on a preset iterative algorithm and the keywords, and an initial mapping between the initial word group and each of the processing departments is determined. The initial mapping is verified according to a preset simulation matching algorithm. Based on the verification results, the keyword groups corresponding to each historical work order and the mapping relationship between each keyword group and each processing department are determined.

2. The work order processing method according to claim 1, characterized in that, The steps for calculating the information content of each word in the target vocabulary set include: Calculate the proportion of each word in the target vocabulary set; Based on a preset algorithm and the proportion of each word in the target vocabulary set, the information content of each word in the target vocabulary set is calculated, wherein the preset algorithm is Y = -log2 P, P is the proportion of each word in the target vocabulary set, and Y is the information content of each word in the target vocabulary set.

3. The work order processing method according to claim 1, characterized in that, The step of determining the keywords in the target vocabulary set based on the amount of information includes: Determine the first and second words in the target vocabulary set, wherein the information content of the first word is greater than or equal to a preset threshold, and the information content of the second word is less than the preset threshold; Identify target words that are included in both the second vocabulary and the preset special business vocabulary, and use the first vocabulary and the target vocabulary as keywords.

4. The work order processing method according to claim 1, characterized in that, The step of determining the target department corresponding to the work order to be transferred based on the mapping relationships includes: The first phrase corresponding to the work order to be processed is determined based on the mapping relationships described above. Calculate the frequency of occurrence of the first phrase in each of the aforementioned mapping relationships; Determine the target mapping corresponding to the highest frequency of occurrence, and take the department corresponding to the target mapping as the target department.

5. The work order processing method according to claim 4, characterized in that, After the step of calculating the frequency of occurrence of the first phrase in each of the mapping relationships, the method includes: When there are multiple occurrence frequencies, a target frequency whose dispersion among the occurrence frequencies meets a preset condition is determined; The pending work order is transferred to the department corresponding to the target frequency, and the processing result is received from the department corresponding to the target frequency. The historical work order is updated based on the processing result.

6. A work order circulation device, characterized in that, include: The word segmentation module is used to obtain historical work orders containing processing departments and record text, and to segment the record text to obtain a target vocabulary set. The information content calculation module is used to calculate the information content of each word in the target vocabulary set and determine the keywords in the target vocabulary set based on the information content. The mapping relationship determination module is used to determine the keyword groups corresponding to each of the historical work orders based on the keywords, and the mapping relationship between each keyword group and each of the processing departments; The work order transfer module is used to receive work orders to be transferred, determine the target department corresponding to the work order to be transferred according to the mapping relationship, and transfer the work order to be transferred to the target department. The word segmentation module includes: The text segmentation unit is used to segment the recorded text according to the maximum number of characters corresponding to the preset maximum matching method to obtain segmented text; The segmentation word determination unit is used to identify the segmented text as segmented words when the preset word library contains the segmented text. The character count reduction unit is used to reduce the character count of the segmented text when the preset dictionary does not contain the segmented text, and use the segmented text with reduced character count as the new segmented text. The target vocabulary set acquisition unit is used to obtain a target vocabulary set containing the segmented vocabulary after the recorded text is segmented; The mapping relationship determination module includes: An initial mapping determination unit is used to determine an initial word group based on a preset iterative algorithm and the keywords, and to determine the initial mapping between the initial word group and each of the processing departments; The verification unit is used to verify the initial mapping according to a preset simulation matching algorithm, and to determine the keyword group corresponding to each historical work order and the mapping relationship between each keyword group and each processing department based on the verification result.

7. An electronic device comprising a processor and a memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the work order flow method according to any one of claims 1 to 5.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the work order flow method according to any one of claims 1 to 5.

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