CN115438995B

CN115438995B - Business processing method and equipment for clothing customization enterprise based on knowledge graph

Info

Publication number: CN115438995B
Application number: CN202211154954.9A
Authority: CN
Inventors: 张蕴蓝; 闫梅丽; 米庆洋; 刘琦; 艾铮; 陈健宁
Original assignee: Qingdao Kutesmart Co ltd
Current assignee: Qingdao Kutesmart Co ltd
Priority date: 2022-09-21
Filing date: 2022-09-21
Publication date: 2023-10-10
Anticipated expiration: 2042-09-21
Also published as: CN115438995A

Abstract

The embodiment of the specification discloses a business processing method and equipment of a clothing customization enterprise based on a knowledge graph, wherein the method comprises the following steps: responding to processing request information of a service to be processed in a corresponding terminal of a clothing customization enterprise, and extracting keywords in the processing request information according to association relations and vocabulary attributes of each vocabulary in the processing request information; dividing the keywords into different sets to determine function labels to be processed corresponding to the sets; inquiring whether a function label corresponding to the function label to be processed exists in a preset knowledge graph or not; if yes, acquiring a person to be selected based on the function label, and determining department information corresponding to the service to be processed according to the person to be selected; dividing the execution forms of the sub-businesses to be processed according to the working contents of the departments and the personnel authorities in the departments, and storing the execution forms in a preset processing module so as to determine the processing forms and the processing sequence of each sub-business to be processed in the businesses to be processed based on the preset processing module.

Description

Business processing method and equipment for clothing customization enterprise based on knowledge graph

Technical Field

The present disclosure relates to the field of data processing technologies, and in particular, to a business processing method and apparatus for a garment customization enterprise based on a knowledge graph.

Background

Business processes for clothing customizing enterprises are performed in production business activities, such as: financial approval of cloth feeding, training of a volume master, approval of a volume master and a resource grid, dispatching of clothing orders, allocation of workshop process flows and the like. Business processing in clothing customization enterprises is to utilize employee function resources in the enterprises as efficiently as possible, achieve the goals of saving, fast, many and good, and achieve the maximum business output efficiency. Therefore, how to effectively process business is an important process in the production and development process of clothing customizing enterprises.

At present, the common adoption in clothing customization enterprises is: and establishing a mapping relation between the service and the staff based on the division and the staff dividing mode. When the business needs to be processed, a processing staff of the business is determined by searching a corresponding department and a corresponding position, and then the staff executes corresponding business processing according to a subjective allocation flow or a business execution flow based on fixed. The traditional mode of distributing the business to be processed based on posts cannot fully mobilize enterprise staff, so that staff functions cannot be maximized, the business processing flow and sequence cannot be flexibly allocated based on the solidification of departments and positions on personnel structures in the enterprise, and further the problems of lower efficiency and difficult cost regulation in the business processing process are caused.

Disclosure of Invention

One or more embodiments of the present disclosure provide a business processing method and apparatus for a garment customization enterprise based on a knowledge graph, which are used to solve the following technical problems: how to provide an efficient business process method.

One or more embodiments of the present disclosure adopt the following technical solutions:

one or more embodiments of the present disclosure provide a business processing method for a garment customization enterprise based on a knowledge graph, where the method includes:

responding to processing request information of a service to be processed in a corresponding terminal of a clothing customization enterprise, and extracting keywords in the processing request information according to association relations among words in the processing request information and attributes of the words;

dividing each keyword into different sets according to task categories corresponding to each keyword to generate corresponding function sets, and determining one or more function labels to be processed corresponding to the function sets according to each keyword in the function sets;

inquiring whether a function label corresponding to the function label to be processed exists in a preset knowledge graph stored in a clothing customization enterprise database;

If the corresponding function label is inquired, acquiring information of personnel to be selected corresponding to the service to be processed in the preset knowledge graph based on the corresponding function label, and determining department information corresponding to the service to be processed according to the information of the personnel to be selected;

dividing the execution form of each sub-service to be processed corresponding to the service to be processed into a multi-department cooperative service or a single-department execution service according to the working content of each related department in the department information corresponding to the service to be processed and the personnel processing authority in each department, and storing the execution form in a preset processing module so as to determine the processing form and the processing sequence of each sub-service to be processed in the service to be processed based on the preset processing module.

Optionally, in one or more embodiments of the present disclosure, before querying a preset knowledge graph of a clothing customization enterprise for the presence of a function label corresponding to the function label to be processed, the method further includes:

acquiring the working content of each person in the clothing customization enterprise based on the historical business processing data of the clothing customization enterprise;

Splitting the working content based on the type of the working content, determining the particle function corresponding to each person, and establishing a first connection relation between the person and the particle function;

determining at least one function label of the particle function according to the working content contained in the particle function, and establishing a second connection relationship between the particle function and the function label;

obtaining an organization architecture of the clothing customization enterprise so as to obtain a third connection relation between each person and each department in the clothing customization enterprise according to the organization architecture of the clothing customization enterprise;

and respectively establishing mapping connection among the personnel, the particle function and the function label, and each department in the clothing customization enterprise based on the first connection relation, the second connection relation and the third connection relation, so as to construct a knowledge graph of the clothing customization enterprise.

Optionally, in one or more embodiments of the present disclosure, before responding to processing request information of a service to be processed in a corresponding terminal of a garment customization enterprise to extract keywords in the processing request information according to association relationships between words in the processing request information and attributes of the words, the method further includes:

Acquiring an uploading form of the processing request information, and if the processing request information is determined to be in a voice uploading form based on the uploading form, converting the processing request information into text information through a corresponding conversion tool;

inputting the word information and preset business processing vocabulary data of the clothing customization enterprise into a preset grammar check model, so as to check grammar of the word information and obtain a check result of the word information;

if the text information is determined to pass the grammar verification based on the verification result, the text information is used as the text information of the processing request information;

if the text information is determined to not pass the grammar verification based on the verification result, determining the service type corresponding to the processing request based on the text information;

dividing the text information into a plurality of fields, and determining adjacent words in each field to divide the fields into a first field with semantic errors and a second field without semantic errors based on the adjacent words and the service type;

acquiring a candidate field corresponding to the second field according to the service type, and acquiring pinyin corresponding to the second field and pinyin of the candidate field;

Constructing a similarity matrix between the second field and the candidate field according to the similarity between the characters of each pinyin corresponding to the second field and the characters of each pinyin of the candidate field and the similarity between the tone of each pinyin corresponding to the second field and the tone of each pinyin of the candidate field;

determining a field with highest similarity in the candidate fields based on the similarity matrix, and taking the field with highest similarity as a replacement field of the second field;

and correcting the error of the second field based on the replacement field to obtain text information of the processing request, so that keywords extracted based on the text information are used as keywords in the processing request information.

Optionally, in one or more embodiments of the present disclosure, extracting keywords in the processing request information according to an association relationship between words in the processing request information and attributes of the words specifically includes:

sentence segmentation is carried out on sentences in the processing request information through preset sentence segmentation identifications, and the numbers of all sentences in the processing request information are obtained;

determining vocabulary contained in the processing request information according to a word segmentation dictionary preset by the clothing customization enterprise;

Acquiring attributes corresponding to each vocabulary, filtering the vocabulary irrelevant to the processing request based on the corresponding attributes, and acquiring initial vocabulary of the processing request information;

performing joint iteration of association relation on the initial vocabulary according to the association rule and the number of the sentence corresponding to the initial vocabulary to obtain a frequent vocabulary set of the processing request information, and generating corresponding sliding window parameters according to the frequent vocabulary set so as to mark the vocabulary in the same window based on the sliding window parameters;

calculating the association entropy value contained in each vocabulary according to the definition rule of the association entropy and the mark, obtaining the existence probability of the vocabulary in each frequent vocabulary set, and determining the association entropy weight value of the vocabulary according to the existence probability;

calculating average associated entropy weight values of the words in the frequent word sets according to the associated entropy weight values of the words, and determining weight values of the words based on the average associated entropy weight values;

obtaining a link matrix of each frequent vocabulary set to iteratively calculate weight values of the vocabularies, and if the weight values are converged to a preset credible threshold interval, sequencing the weight values of each vocabulary to obtain a preset number of vocabularies as keywords of the processing request information.

Optionally, in one or more embodiments of the present disclosure, after querying a preset knowledge graph stored in a clothing customization enterprise database for the presence of a function label corresponding to the function label to be processed, the method further includes:

if the function label is not queried, extracting statement information related to service processing in the processing request information;

acquiring a history query service of a terminal corresponding to the processing request information, so as to determine a target scene of the service to be processed based on the statement information and the history query service;

determining at least one scene intention to be selected corresponding to the target scene based on an association relation between a preset service processing scene and scene intention;

screening the at least one scene intention to be selected according to the processing request information and the last processing service of the terminal where the processing request is located, and determining the scene intention of the service to be processed;

and determining department information corresponding to the to-be-processed service according to the basic information of the to-be-processed sub-service corresponding to the scene intention and the range information of the processing personnel in the clothing customization enterprise corresponding to the to-be-processed sub-service.

Optionally, in one or more embodiments of the present disclosure, before determining at least one candidate scene intention corresponding to the target scene based on an association relationship between a preset service processing scene and a scene intention, the method further includes:

creating at least one business processing scene related to the clothing customizing enterprise according to the historical business data of the clothing customizing enterprise; wherein, the business processing scene at least comprises any one or more of the following: qualification approval scene of a measuring body engineer, service evaluation scene of the measuring body engineer, scene of applying clothing to process an order, scene of measuring body dispatch, and scene of checking cloth quality;

acquiring processing flow information of each service in the clothing customization enterprise according to the historical service data, and configuring corresponding sub-services to be processed for the service processing scene based on the processing flow information;

the method comprises the steps of obtaining basic processing tasks of all sub-services to be processed and personnel range information related to processing personnel, integrating the basic processing tasks with the personnel range information, obtaining scene intentions of all the sub-services to be processed in the service processing scene, and establishing association relations between the service processing scene and the scene intentions.

Optionally, in one or more embodiments of the present disclosure, according to the working content of each department in the department information corresponding to the to-be-processed service and the personnel processing authority in each department, the execution form of each to-be-processed sub-service in the to-be-processed service is divided into a multi-department collaboration service or a single-department execution service, which specifically includes:

determining that the service to be processed belongs to an accessory customization service or a whole clothes customization service according to the processing request information, and acquiring a sub-service to be processed corresponding to the accessory customization service or the whole clothes customization service; wherein the accessory customization service at least comprises any one or more of the following: button customization related service, waistband customization related service and disc button customization related service;

according to the clothing customization work content corresponding to each department, matching each sub-business to be processed in the fitting customization business or the whole clothing customization business with clothing customization work corresponding to each department respectively to determine department information corresponding to each sub-business to be processed in the business to be processed respectively;

if the sub-business to be processed in the business to be processed is determined to be a single department according to the department information corresponding to the sub-business to be processed, acquiring personnel processing authority in the department, and determining that the execution form of the sub-business to be processed is a single department serial business or a single department parallel business based on the personnel processing authority;

And if the departments corresponding to the sub-tasks to be processed are determined according to the department information corresponding to the sub-tasks to be processed, acquiring personnel processing authorities of all the departments, and determining the execution form of the sub-tasks to be processed as multi-department parallel collaborative services or multi-department serial collaborative services based on the personnel processing authorities.

Optionally, in one or more embodiments of the present disclosure, after dividing the execution form of each sub-service to be processed in the service to be processed into a multi-department collaboration service or a single-department execution service according to the working content of each department in the department information corresponding to the service to be processed and the personnel processing authority in each department, the method further includes:

if the sub-business to be processed is determined to be a multi-department parallel collaborative business or a single-department parallel business according to the clothing customization work content corresponding to the departments and the personnel processing authority in each department, a parallel customization thread is created for the sub-business to be processed; storing the sub-business to be processed into a preset processing module so as to sequentially determine the processing form of the sub-business to be processed in the business to be processed based on the preset processing module;

If the sub-service to be processed in the service to be processed is determined to be a multi-department serial collaborative service or a single-department serial service according to the working contents of the departments and the personnel processing authorities in the departments, acquiring the association relation of each working task in the sub-service to be processed according to the association relation of the departments;

according to the association relation of each work task in the sub-service to be processed, the front sub-service and the rear sub-service of each sub-service to be processed are determined, and the sub-service to be processed, the front sub-service and the rear sub-service are stored in a preset processing module so as to determine the processing form and the processing sequence of each sub-service to be processed in the sub-service to be processed based on the preset processing module.

Optionally, in one or more embodiments of the present disclosure, after determining the processing form and the processing order of each sub-service to be processed in the service to be processed based on the preset processing module, the method further includes:

determining a business processing flow of the task to be processed in the clothing customizing enterprise based on the processing form and the processing sequence of each sub-business to be processed in the task to be processed, so as to obtain at least one clothing production link corresponding to the business processing flow in the clothing customizing enterprise;

Determining a plurality of pieces of personnel information to be processed corresponding to the at least one clothing production link and a plurality of business processing stages corresponding to the at least one production link in the personnel to be selected according to the clothing detail design demand information and the clothing tailoring process information in the processing request information;

acquiring grades of a plurality of staff to be processed corresponding to the at least one clothing production link, inputting the grades of the plurality of staff to be processed and technical cost data of the business processing stages into a preset cost prediction model, and acquiring the cost of the staff to be selected in different business processing stages so as to determine a first weight value of the staff to be selected according to the cost; wherein the cost is in an inverse relationship with the first weight value;

acquiring a time interval between the idle time and the current time of the personnel to be processed corresponding to the at least one clothing production link, and determining a second weight value of the personnel to be processed based on the time interval; wherein the time interval is inversely related to the second weight value;

and taking the weighted values of the first weighted value and the second weighted value as the weighted values of the personnel to be processed, so as to determine personnel information with highest matching degree in the personnel to be processed in the at least one clothing production link based on the weighted values, and assist in judging the execution link information and the execution personnel information of the service to be processed.

One or more embodiments of the present specification provide a business processing device for a garment customization enterprise based on a knowledge-graph, the device comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the device to perform:

The above-mentioned at least one technical scheme that this description embodiment adopted can reach following beneficial effect:

in the specification, after the query request is converted into the text information, the keywords in the text information are extracted to perform subsequent query, so that the query efficiency is improved, the query mode is unified, the text correction of the query request is facilitated, and the accuracy of service processing is improved. The keywords are divided into function sets according to task categories to which the keywords belong, so that function labels of the function sets are determined, corresponding staff are determined according to the knowledge graph query function labels, and the problems that staff functions cannot be fully utilized and staff functions are excavated due to the fact that staff functions are solidified based on departments and posts in a traditional mode are solved. Meanwhile, based on analysis of scene intention on the query request, the possibility of error distribution of the service to be processed caused by unclear subjective description of service inquirers is reduced, and the service processing efficiency is improved.

Drawings

In order to more clearly illustrate the embodiments of the present description or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some of the embodiments described in the present description, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:

fig. 1 is a schematic flow chart of a business processing method of a clothing customizing enterprise based on a knowledge graph according to an embodiment of the present disclosure;

fig. 2 is a schematic architecture diagram of an enterprise business processing process based on a knowledge graph in an application scenario provided in an embodiment of the present disclosure;

fig. 3 is a schematic internal structure diagram of an enterprise business processing device based on a knowledge graph according to an embodiment of the present disclosure.

Detailed Description

The embodiment of the specification provides a business processing method and equipment for a clothing customization enterprise based on a knowledge graph.

In order to make the technical solutions in the present specification better understood by those skilled in the art, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present disclosure.

As shown in fig. 1, the embodiment of the present disclosure provides a method flow diagram of a business processing method of a clothing customizing enterprise based on a knowledge graph, and as can be seen from fig. 1, the method includes the following steps:

s101: responding to processing request information of a service to be processed in a corresponding terminal of a clothing customization enterprise, and extracting keywords in the processing request information according to the association relation among words in the processing request information and the attribute of each word.

Enterprises encounter, for example, in the production and management process: the business to be processed in aspects of finance, manpower, administration, research and development, sales, customer service, purchasing, production, storage, logistics and the like is required to be distributed to corresponding personnel for processing, so that the query speed of the query personnel of the business to be processed for querying the corresponding processing personnel is improved. In the embodiment of the specification, the server responds to the query request of the service to be processed initiated by the query person, and after the query request is obtained, the server processes the association relation among the vocabularies in the request information and the attribute of each vocabulary, and extracts the keywords in the processing request information so as to perform subsequent processing based on the keywords, thereby improving the query efficiency.

Further, since the query request may be based on a voice query or a text query, in order to facilitate unified processing analysis of the server, before extracting keywords in the processing request information according to the association relationship between words in the processing request information and the attribute of each word, the method further includes the following steps: first, the uploading form of the processing request information is acquired, and if the uploading form of the processing request information is determined to be a voice uploading form, the processing request information is converted into text information through a corresponding conversion tool. For example: in the voice query form, the voice needs to be converted into text information through an NLP mode, and the tool for text conversion is not limited here. The conversion process or the query person can have the problems of semantic errors and the like when uploading the processing request information, so that the accuracy of service processing is improved. Firstly, inputting text information corresponding to the converted processing request information and preset business processing vocabulary data of a garment customization enterprise into a preset grammar checking model, so as to check grammar of the text information and obtain a checking result of the text information. The preset business processing vocabulary data stores language information corresponding to each business processed in the clothing customizing enterprise, and as shown in fig. 2, the analysis of the text information can be realized based on the AI capability layer and the training of a preset grammar checking model can be realized in the application scene of the specification model.

If it can be determined that the text information passes the grammar check based on the check result obtained in the above check process, the text information is used as the text information after the conversion of the processing request information. If the text information can not pass the grammar check according to the check result obtained in the process, the service type corresponding to the processing request information is determined according to the text information. Then dividing the text information into a plurality of fields, and determining adjacent words in each field, so that the fields are divided into a first field with semantic errors and a second field without semantic errors based on the adjacent words and the service field. For example: if the text information is "the beam qualification approval of the clothing colorist", the business type corresponding to the query request is approximately determined to be the "approval" field according to the text information. Then dividing the text information into a plurality of fields of 'clothing', 'body', 'qualification', 'approval' of a 'clothing', 'body' and 'body' according to the text information, determining the fields of 'clothing', 'qualification', 'approval' of the 'clothing', 'body' as a first field without semantic errors according to adjacent words and the belonging approval field, and determining the field as a second field with semantic errors because the 'body' is not matched with the adjacent words and the service field. And then acquiring the candidate field corresponding to the second field according to the service field, and acquiring the pinyin corresponding to the second field and the pinyin of the candidate field. And constructing a similarity matrix between the second field and the candidate field according to the similarity between the characters of each pinyin corresponding to the second field and the characters of each pinyin of the candidate field and the similarity between the tone of each pinyin corresponding to the second field and the tone of each pinyin of the candidate field. And determining a field with highest similarity with the second field in the candidate fields according to the similarity matrix, and taking the field with highest similarity as a replacement field of the second field. And correcting the error of the second field according to the determined replacement field, so as to obtain the text information after the query request is converted. By correcting the text information, errors caused by subjective query of a inquirer and semantic errors caused by conversion of the conversion tool into the text information are reduced, and the accuracy of business processing and subsequent distribution is improved.

Further, in order to avoid the problem that the vocabulary with the large number of occurrences is determined as the keyword based only on the number of occurrences of the vocabulary in the conventional manner, the resulting problem that the vocabulary with the small number of occurrences but significant meaning is ignored is solved. In one or more embodiments of the present disclosure, extracting keywords in text information according to association relationships between words in processing request information and attributes of words, specifically includes the following steps:

firstly, sentence segmentation is carried out on sentences in the processing request information through preset sentence segmentation marks, and numbers corresponding to all sentences in the processing request information are obtained. Such as: the text information corresponding to the processed query request in a certain scene is: the method comprises the steps that firstly, available clothing designer information of each department needs to be collected, then corresponding butt joint persons are determined according to clothing customization demands, relevant persons are organized to process clothing customization orders, the dispatching orders are produced, then the text information is divided into the clothing customization scheme of the first party company and the clothing customization orders which need to be processed according to preset sentence division marks, namely, the available clothing designer information of each department needs to be collected firstly, then corresponding butt joint persons are determined according to the clothing customization demands, relevant persons are organized to process the clothing customization orders/dispatching orders to produce, firstly, available clothing designer information of each department/sentence corresponding number 2 need to be collected, and the serial numbers corresponding to each sentence are obtained sequentially.

After the sentences are divided, determining the vocabulary contained in the processing request information according to a word segmentation dictionary preset by the clothing customizing enterprise. And then acquiring the attribute corresponding to each vocabulary, filtering the vocabulary irrelevant to the processing request based on the corresponding attribute, and acquiring the initial vocabulary for processing the request information. Taking "available clothing designer information of each department needs to be collected first" as an example, it can be seen that words such as "first", "need" are words irrelevant to a query request, and filtering is needed, so that an initial word of text information is obtained. And then carrying out joint iteration of association relation on the initial vocabulary according to association rules and the number of the sentence corresponding to the initial vocabulary to obtain a frequent vocabulary set of the processing request information, and generating corresponding sliding window parameters according to the frequent vocabulary set, so that the vocabulary in the same window is marked according to the parameters of the sliding window. And then calculating the associated entropy value contained in each vocabulary according to the definition rule and the mark of the associated entropy, obtaining the existence probability of the vocabulary in each frequent vocabulary set, and determining the associated entropy weight value of the vocabulary according to the existence probability. And then calculating the average associated entropy weight value of the words in each frequent word set according to the associated entropy weight value of each word, thereby determining the weight value of each word according to the obtained average associated entropy weight value. And acquiring a link matrix of each frequent vocabulary set, so as to iteratively calculate the weight values of the vocabularies, and if the weight values of the vocabularies are determined to be converged within a preset credible threshold interval, sequencing the weight values of the vocabularies to obtain a preset number of vocabularies as keywords for processing the request information.

S102: dividing the keywords into different sets according to task categories corresponding to the keywords to generate corresponding function sets, and determining one or more function labels to be processed corresponding to the function sets according to the keywords in the function sets.

After the keywords of the processing request information are obtained in the step S101, in order to facilitate quick query for service executives, in the embodiment of the present disclosure, the keywords are divided into different function sets according to task categories corresponding to the keywords, and then at least one function label corresponding to each function set is determined according to the keywords in the function sets. For example, the processing request information in step S101 is "the currently received clothing customization scheme and clothing customization order of the first party company needs to be processed/the available clothing designer information of each department needs to be collected first/then the corresponding docker is determined according to the clothing customization requirement,/the organization related personnel processes the clothing customization order/dispatch for production", if the keywords obtained after processing are "collection", "department", "clothing designer information", "clothing customization requirement", "docker", "organization", "processing", "order", "dispatch", "production", the keywords are classified into "collection, department, clothing designer information", "collection, clothing customization requirement, docker", "organization, processing, order", "order, dispatch, production" and other sets according to the task category of each keyword, and then the function labels of each set are obtained as the function labels to be queried according to the keywords in each set.

S103: inquiring whether a function label corresponding to the function label to be processed exists in a preset knowledge graph stored in a clothing customization enterprise database.

In order to avoid the problem that the functions of staff cannot be fully mined due to the fact that business processing is distributed based on fixed posts in the traditional mode, the problem that business processing efficiency and cost are high is solved. In one or more embodiments of the present disclosure, by querying a preset knowledge graph of a clothing customization enterprise, it is determined whether a function label corresponding to a function label to be queried exists for query, and a query mode based on the function label breaks through an employee architecture inherent in service matching based on only employee positions, which brings beneficial effects for improving efficiency of enterprise service processing and saving processing cost. The following description is needed: the knowledge graph is used as a new knowledge organization and retrieval technology in the big data age for describing concepts and correlations in the physical world in a symbolic form. The basic composition unit is an entity-relation-entity triplet, and the entities and the related attribute value-value pairs thereof are mutually connected through the relation to form a net knowledge structure. Through the man-machine interaction technology, a large amount of computer-readable knowledge can be obtained, and the embodiment of the specification improves the query efficiency by utilizing the powerful information retrieval function of the knowledge graph. As shown in fig. 2, the knowledge layer realizes knowledge collection and database mapping, processes data and automatically extracts knowledge, generates structured information and stores the structured information in a knowledge graph for management and maintenance of entity attributes and association relations.

Further, in one or more embodiments of the present disclosure, before querying whether a function label corresponding to the function label to be queried exists in a preset knowledge graph of a clothing customization enterprise, the method further includes the following process: firstly, according to historical business processing data of a clothing customizing enterprise, working contents of all personnel are obtained. And then splitting each working content according to the type of the working content, determining the particle function corresponding to each staff, and establishing a first connection relation between the staff and the particle function. It should be noted that, the granular function is a micro-service item that can be processed by each employee, for example: the basic capabilities and functions of employees such as search capability, leave-on approval capability, financial approval capability, project interfacing capability and the like are considered as granular functions of the employee. And then determining at least one function label of the particle function according to the work content contained in the particle function of the staff, and establishing a second connection relationship between the particle function and the function label. Wherein, it should be noted that the function label is a label for describing the function of the particle.

And then obtaining an organization framework of the clothing customization enterprise, and obtaining a third connection relation between each person and each department in the clothing customization enterprise according to the organization framework of the clothing customization enterprise, so as to respectively establish mapping connection among the person and the particle function, the particle function and the function label and between the person and each department in the clothing customization enterprise according to the first connection relation, the second connection relation and the third connection relation, thereby constructing a knowledge graph of the connection relation among the particle function, the staff and the departments.

Further, in one or more embodiments of the present disclosure, if the function label to be queried determined in the step S102 cannot be queried based on the preset knowledge graph determined in the step. Then extracting statement information related to service processing from the processing request information, acquiring historical query service of the terminal corresponding to the processing request information, and determining a target scene of the service to be processed according to the statement information and the historical query service. And determining at least one scene intention to be selected corresponding to the target scene according to the association relation between the service processing scene and the scene intention determined in the process. And then screening the determined at least one scene intention to be selected according to the processing request information and the last processing service of the terminal where the processing request is located, thereby determining the scene intention of the service to be processed corresponding to the service processing flow. After determining the scene intention, determining at least one function label of the to-be-processed service according to the basic information of the to-be-processed sub-service corresponding to the scene intention and the range information of the processing personnel in the clothing customization enterprise corresponding to the to-be-processed sub-service. And then acquiring personnel to be selected corresponding to the service to be processed in the preset knowledge graph according to the corresponding at least one functional label. According to the embodiment of the specification, when the corresponding label cannot be determined based on the processing request information, the corresponding functional label is determined based on the scene intention by combining analysis, so that the intelligent level of business processing is improved, and the effect of combining analysis with the scene is achieved.

S104: if the corresponding function label is inquired, acquiring information of personnel to be selected corresponding to the service to be processed in the preset knowledge graph based on the corresponding function label, and determining department information corresponding to the service to be processed according to the information of the personnel to be selected.

If the function label to be queried determined in the step S102 can be queried based on the preset knowledge graph in the step S103. In the embodiment of the present disclosure, according to the function label corresponding to the function label to be queried in the preset knowledge graph, a corresponding particle function is obtained, and then one or more pieces of personnel information to be selected corresponding to the service to be processed are obtained based on the functional particle. The functions of personnel in the clothing customization enterprise are divided and defined based on the particle function mode, so that the full utilization of staff capacity is realized, and the benefit of business processing is improved.

Further, in one or more embodiments of the present disclosure, before determining at least one candidate scene intention corresponding to the target scene based on an association relationship between the preset service processing scene and the scene intention, the method further includes the following steps: at least one business processing scene related to the clothing customizing enterprise is created according to the historical business data of the clothing customizing enterprise. Wherein, it should be noted that the service processing scenario at least includes any one or more of the following: qualification approval of the measuring body, service evaluation of the measuring body, application of clothing to process orders, measuring body dispatch, and cloth quality checking. And then, according to the historical service data, acquiring the processing flow information of each service in the clothing customizing enterprise, so as to configure corresponding sub-services to be processed for the service processing scene according to the processing flow information. After determining the sub-services to be processed, obtaining basic matters of each sub-service to be processed and personnel range information of the processing personnel related to each sub-service to be processed, wherein the personnel range information can be department information, such as: if the subtask to be processed involves financial processing matters, the personnel scope of its processing personnel is limited to the financial sector due to the confidentiality of the financial information. And integrating the basic items with the personnel range information, so as to obtain scene intentions of all sub-services to be processed in the service processing scene, and establishing an association relationship between the service processing scene and the scene intentions.

S105: dividing the execution form of each sub-service to be processed corresponding to the service to be processed into a multi-department cooperative service or a single-department execution service according to the working content of each related department in the department information corresponding to the service to be processed and the personnel processing authority in each department, and storing the execution form in a preset processing module so as to determine the processing form and the processing sequence of each sub-service to be processed in the service to be processed based on the preset processing module.

In order to achieve efficient processing of a to-be-processed service, after determining department information corresponding to information of a person to be selected based on the above process, according to working content of each relevant department in the department information corresponding to the to-be-processed service and personnel processing authority in each department, the embodiment of the present disclosure divides execution forms of each to-be-processed sub-service corresponding to the to-be-processed service into multi-department collaborative service or single-department execution service, and stores the execution forms into a preset processing module, so that processing forms and processing sequences of each to-be-processed sub-service in the to-be-processed service are determined according to the preset processing module in the service processing process, thereby improving processing efficiency of the to-be-processed service.

Specifically, in one or more embodiments of the present disclosure, according to the working content of each department in the department information corresponding to the to-be-processed service and the personnel processing authority in each department, the execution form of each to-be-processed sub-service in the to-be-processed service is divided into a multi-department collaborative service or a single-department execution service, which specifically includes:

and determining that the service to be processed belongs to the fitting custom service or the whole clothes custom service according to the processing request information. Then obtaining a sub-service to be processed corresponding to the accessory customization service or the whole clothes customization service; wherein, it should be noted that the accessory customization service at least includes any one or more of the following: button customization related service, waistband customization related service, and disc button customization related service. And according to the clothing customization work content corresponding to each department, matching each sub-business to be processed in the fitting customization business or the whole clothing customization business with the clothing customization work corresponding to each department respectively so as to determine department information corresponding to each sub-business to be processed in the business to be processed respectively. If the sub-business to be processed in the business to be processed is determined to be executed by a single department, namely, corresponds to the single department according to the department information corresponding to the sub-business to be processed, the personnel processing authority in the department is acquired, so that the execution form of the sub-business to be processed is determined to be the serial business of the single department or the parallel business of the single department based on the personnel processing authority in the department. And if the department information corresponding to the sub-business to be processed is determined, the sub-task business to be processed corresponds to a plurality of departments, and then the personnel processing authority of each department is acquired, so that the execution form of the sub-business to be processed is determined to be the multi-department parallel collaborative business or the multi-department serial collaborative business based on the personnel processing authority.

Further, in order to enable each service to be processed orderly according to the corresponding processing form, in one or more embodiments of the present disclosure, according to the working content of each department in the department information corresponding to the service to be processed and the personnel processing authority in each department, the method further includes the following steps after dividing the execution form of each sub-service to be processed in the service to be processed into the multi-department collaborative service or the single-department execution service:

if the to-be-processed sub-service is determined to be the multi-department parallel collaborative service or the single-department parallel service according to the clothing customization work content corresponding to the departments and the personnel processing authority in each department in the process, a parallel customization thread is created for the to-be-processed sub-service. And then storing the sub-service to be processed into a preset processing module so as to sequentially determine the processing form of the sub-service to be processed in the service to be processed based on the preset processing module. If the sub-service to be processed in the service to be processed is determined to be the serial collaborative service of multiple departments or the serial service of single department according to the working contents of the multiple departments and the personnel processing authority of each department, the association relation of each working task in the sub-service to be processed is obtained according to the association relation of the multiple departments corresponding to the service. And the front sub-service and the rear sub-service of each sub-service to be processed are stored into a preset processing module so as to determine the processing form and the processing sequence of each sub-service to be processed in the service to be processed based on the preset processing module. As shown in fig. 2, the storage layer may store processing and storage of various data, store structured data through MySQL, store unstructured data using ES, store map data using map database, use dis for data caching, and implement message queue management through kafka. The preset processing mode in this embodiment may be stored based on a storage layer to sequentially implement business processes.

Further, in order to assist in determining at least one garment production link, processing efficiency of a garment customization enterprise is improved. In one or more embodiments of the present disclosure, after determining the processing form and the processing order of each sub-service to be processed in the service to be processed based on the preset processing module, the method further includes the following procedures:

firstly, determining a business processing flow of a business to be processed in a clothing customizing enterprise according to the processing form and the processing sequence of each sub-business to be processed in the task to be processed, thereby obtaining at least one clothing production link corresponding to the business processing flow in the clothing customizing enterprise. And then determining a plurality of pieces of personnel information to be processed corresponding to at least one clothing production link and a plurality of business processing stages corresponding to at least one production link in the personnel to be selected according to the clothing detail design demand information and the clothing tailoring process information in the processing request information. The method comprises the steps of obtaining grades of a plurality of staff to be processed corresponding to at least one clothing production link, inputting the grades of the plurality of staff to be processed and technical cost data of business processing stages into a preset cost prediction model to obtain cost of the staff to be selected in different business processing stages, and determining a first weight value of the staff to be selected according to the cost. It will be appreciated that the cost is inversely related to the first weight value, i.e. the higher the cost the lower the first weight value of the person to be selected, the lower the cost the higher the first weight value of the person to be selected.

And secondly, acquiring a time interval between the idle time and the current time of the personnel to be processed corresponding to at least one clothing production link, and determining a second weight value of the personnel to be processed according to the time interval. It will be appreciated that there is an inverse relationship between the time interval and the second weight value, i.e. the shorter the time interval the higher the second weight value and the longer the interval the lower the second weight value. Multiplying the first weight value and the second weight value to obtain a weight value, and taking the weight value as the weight value of the personnel to be selected, so as to determine the executive information under comprehensive consideration of cost and efficiency in the personnel to be selected based on the weight value, and assist in judging the executive link information and executive information of the service to be processed, thereby realizing efficient processing of the service to be processed. It should be further noted that, in the process of using this mode, the application layer and the access layer shown in fig. 2 are used to implement the docking with the intelligent application and the implementation of the function, where the access layer mainly completes the docking with the external platform, and is based on the open API interface. The platform applet and the digital large screen realize the butt joint of the searching and associated recommending capacity, the voice recognition and the voice synthesizing capacity of the intelligent knowledge graph. The application layer supports various intelligent applications of the application system, including knowledge graph search, knowledge graph data viewing, knowledge question answering, voice query and voice filling capability, and provides an API interface for capability output, and related AI capability can be called through the API interface.

As shown in fig. 3, in one or more embodiments of the present disclosure, a schematic internal structure of an enterprise business processing device based on a knowledge graph is provided. As can be seen from fig. 3, the apparatus comprises: a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the device to perform:

Dividing the execution form of each sub-service to be processed corresponding to the service to be processed into a multi-department cooperative service or a single-department execution service according to the working content of each related department in the department information corresponding to the service to be processed and the personnel processing authority in each department, and storing the execution form in a preset processing module so as to determine the processing form and the processing sequence of each sub-service to be processed in the service to be processed based on the preset processing module. In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus, devices, non-volatile computer storage medium embodiments, the description is relatively simple, as it is substantially similar to method embodiments, with reference to the section of the method embodiments being relevant.

The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

The foregoing is merely one or more embodiments of the present description and is not intended to limit the present description. Various modifications and alterations to one or more embodiments of this description will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, or the like, which is within the spirit and principles of one or more embodiments of the present description, is intended to be included within the scope of the claims of the present description.

Claims

1. A business processing method for a garment customization enterprise based on a knowledge graph, the method comprising:

dividing the execution form of each sub-service to be processed corresponding to the service to be processed into a multi-department cooperative service or a single-department execution service according to the working content of each related department in the department information corresponding to the service to be processed and the personnel processing authority in each department, and storing the execution form in a preset processing module so as to determine the processing form and the processing sequence of each sub-service to be processed in the service to be processed based on the preset processing module;

the method comprises the steps of dividing execution forms of all sub-services to be processed corresponding to the services to be processed into multi-department collaborative services or single-department execution services according to the working contents of all relevant departments in the department information corresponding to the services to be processed and personnel processing authorities in all departments, wherein the execution forms of all sub-services to be processed corresponding to the services to be processed are divided into multi-department collaborative services or single-department execution services specifically comprising:

and if the departments corresponding to the sub-services to be processed are determined according to the department information corresponding to the sub-services to be processed, acquiring personnel processing authorities of all the departments, and determining the execution form of the sub-services to be processed as multi-department parallel collaborative services or multi-department serial collaborative services based on the personnel processing authorities.

2. The business processing method of a clothing customization enterprise based on a knowledge graph according to claim 1, wherein before whether a function label corresponding to the function label to be processed exists in a preset knowledge graph of the inquiring clothing customization enterprise, the method further comprises:

3. The business processing method of a clothing customizing enterprise based on a knowledge graph as claimed in claim 1, wherein before extracting the keywords in the processing request information according to the association relation between the words in the processing request information and the attribute of each word, the method further comprises:

4. The business processing method of a garment customization enterprise based on a knowledge graph according to claim 1, wherein the extracting keywords in the processing request information according to the association relation between words in the processing request information and the attribute of each word specifically comprises:

5. The business processing method of a clothing customization enterprise based on a knowledge graph according to claim 1, wherein after querying whether a function label corresponding to the function label to be processed exists in a preset knowledge graph stored in a clothing customization enterprise database, the method further comprises:

6. The business processing method of a clothing customizing enterprise based on a knowledge graph as claimed in claim 5, wherein before determining at least one candidate scene intention corresponding to the target scene based on an association relation between a preset business processing scene and a scene intention, the method further comprises:

7. The business processing method of a clothing customizing enterprise based on a knowledge graph as claimed in claim 1, wherein the method further comprises, after dividing the execution form of each sub-business to be processed corresponding to the business to be processed into a multi-department collaborative business or a single-department execution business according to the work content of each related department in the department information corresponding to the business to be processed and the personnel processing authority in each department:

8. The business processing method of a clothing customizing enterprise based on a knowledge graph as claimed in claim 7, wherein after determining the processing form and the processing sequence of each sub-business to be processed in the business to be processed based on the preset processing module, the method further comprises:

determining a business processing flow of the business to be processed in the clothing customizing enterprise based on the processing form and the processing sequence of each sub business to be processed in the business to be processed, so as to obtain at least one clothing production link corresponding to the business processing flow in the clothing customizing enterprise;

determining a plurality of pieces of personnel information to be processed corresponding to the at least one clothing production link and a plurality of business processing stages corresponding to the at least one clothing production link in the personnel to be selected according to the clothing detail design demand information and the clothing tailoring process information in the processing request information;

9. An enterprise business processing device based on a knowledge graph, the device comprising: a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the device to perform the method of any of claims 1-8.