CN116957502A - Method and system for collaborative office - Google Patents
Method and system for collaborative office Download PDFInfo
- Publication number
- CN116957502A CN116957502A CN202310918297.9A CN202310918297A CN116957502A CN 116957502 A CN116957502 A CN 116957502A CN 202310918297 A CN202310918297 A CN 202310918297A CN 116957502 A CN116957502 A CN 116957502A
- Authority
- CN
- China
- Prior art keywords
- dispute
- contradictory
- contradiction
- data
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 51
- 230000008094 contradictory effect Effects 0.000 claims abstract description 119
- 238000012549 training Methods 0.000 claims abstract description 60
- 238000011156 evaluation Methods 0.000 claims abstract description 23
- 238000012545 processing Methods 0.000 claims abstract description 16
- 238000013210 evaluation model Methods 0.000 claims description 27
- 238000002372 labelling Methods 0.000 claims description 12
- 230000008569 process Effects 0.000 claims description 12
- 230000008859 change Effects 0.000 claims description 11
- 238000012360 testing method Methods 0.000 claims description 9
- 238000012795 verification Methods 0.000 claims description 9
- 238000004590 computer program Methods 0.000 claims description 7
- 238000010276 construction Methods 0.000 claims description 4
- 238000000605 extraction Methods 0.000 claims description 4
- 230000011218 segmentation Effects 0.000 claims description 4
- 238000012423 maintenance Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012502 risk assessment Methods 0.000 description 3
- 230000008676 import Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000012216 screening Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Computation (AREA)
- Evolutionary Biology (AREA)
- Tourism & Hospitality (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Marketing (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Health & Medical Sciences (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The embodiment of the invention discloses a method and a system for collaborative office, which are used for acquiring a certain amount of contradictory dispute data and extracting characteristic information of the contradictory dispute data; constructing a training set based on the characteristic information; inputting the training set into a contradictory dispute grade assessment model for training to obtain a trained contradictory dispute grade assessment model; extracting characteristic information of the to-be-classified contradiction dispute data, inputting the characteristic information of the to-be-classified contradiction dispute data into a trained contradiction dispute class assessment model, and obtaining contradiction dispute class information corresponding to the to-be-classified contradiction dispute data; and reporting the contradiction dispute data to the approval roles of the corresponding grades for approval processing based on the contradiction dispute grade information. The method for collaborative office solves the problem that in the prior art, intelligent grade evaluation cannot be carried out on contradictory dispute data, and the contradictory dispute data is distributed to corresponding approval roles according to grade for approval.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a method, a system, an electronic device, and a storage medium for collaborative office.
Background
The function of the letter visit maintenance is to positively solve the problem of mass reflection in the coming and visiting, and avoid contradiction deterioration, thereby leading the society to be more harmonious and stable;
however, at present, after intelligent grade evaluation is not performed on the obtained contradictory dispute data, the contradictory dispute data is distributed to corresponding approval roles according to grade for approval. The comprehensive investigation and the movement grasping of various contradiction disputes and hidden danger Miaotui by the trust maintenance department are difficult, the intercommunication and the sharing of information can not be realized rapidly, and the passivity of trust maintenance work is strong.
What is needed is a method for intelligently evaluating the level of contradictory dispute data and assigning the contradictory dispute data to corresponding approval roles for approval according to the level.
Disclosure of Invention
The embodiment of the invention aims to provide a method, a system, electronic equipment and a storage medium for collaborative office, which are used for solving the problem that in the prior art, intelligent grade evaluation cannot be carried out on contradictory dispute data, and the contradictory dispute data is distributed to corresponding approval roles according to grade for approval.
In order to achieve the above object, an embodiment of the present invention provides a method for collaborative office, including:
acquiring a certain amount of contradictory dispute data, and extracting characteristic information of the contradictory dispute data; constructing a training set based on the characteristic information;
constructing a contradiction dispute grade assessment model;
inputting the training set into the contradictory dispute class assessment model for training to obtain a trained contradictory dispute class assessment model;
extracting characteristic information of the to-be-classified contradiction dispute data, inputting the characteristic information of the to-be-classified contradiction dispute data into the trained contradiction dispute class assessment model, and obtaining contradiction dispute class information corresponding to the to-be-classified contradiction dispute data;
and reporting the contradiction dispute data to the approval roles of the corresponding grades based on the contradiction dispute grade information for approval processing.
Based on the technical scheme, the invention can also be improved as follows:
further, the obtaining a certain amount of contradictory dispute data, extracting feature information of the contradictory dispute data, and constructing a training set based on the feature information includes:
and labeling the contradictory dispute data to obtain a plurality of contradictory dispute data carrying labeling labels, wherein the labeling labels comprise high risk, medium risk and low risk.
Further, the step of inputting the training set into the paradox level assessment model for training to obtain a trained paradox level assessment model includes:
dividing the characteristic information into a training set, a verification set and a test set;
training the contradictory dispute class assessment model based on the training set;
performing performance evaluation on the trained contradictory dispute class evaluation model based on the verification set to obtain a contradictory dispute class evaluation model meeting performance conditions;
and evaluating the segmentation result of the contradictory dispute grade evaluation model meeting the performance condition based on the test set to obtain an evaluation index corresponding to the contradictory dispute grade evaluation model.
Further, the method for collaborative office further comprises:
responding to an establishing request of role information, and establishing a permission database, wherein the permission database comprises approval role information and permission information corresponding to each approval role;
and establishing the relationship between the approval role and the authority, and carrying out association.
Further, the method for collaborative office further comprises:
the approval roles participating in the approval process comprise a first approval role, a second approval role and a third approval role;
the first trial role processes the contradiction and dispute data with high risk as grade information;
the second trial role processing grade information is contradiction dispute data of the risk;
and the third trial role processes the contradiction and dispute data with low risk as grade information.
Further, the method for collaborative office further comprises:
after the approval of the contradictory dispute data is completed by the approval role, transacting and circulating the matters corresponding to the contradictory dispute data;
and when the contradiction dispute data is not approved by the approval role, carrying out withdrawal operation and backlog operation on the matters corresponding to the not approved contradiction dispute data based on the requirement information.
Further, the method for collaborative office further comprises:
when the contradictory dispute data is changed, obtaining change information, and sending the change information to the corresponding approval roles for approval.
A system for collaborative offices, comprising:
the acquisition module is used for acquiring a certain amount of contradictory dispute data;
the feature information extraction module is used for extracting feature information of the contradictory dispute data and feature information of the contradictory dispute data to be classified;
the construction module is used for constructing a training set based on the characteristic information;
the training module is used for inputting the training set into the contradictory dispute grade assessment model for training to obtain a trained contradictory dispute grade assessment model;
inputting the feature information of the to-be-classified contradiction dispute data into the trained contradiction dispute class assessment model to obtain the contradiction dispute class information corresponding to the to-be-classified contradiction dispute data;
and the reporting module is used for reporting the contradiction dispute data to the approval roles of the corresponding grades for approval processing based on the contradiction dispute grade information.
An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method when the computer program is executed.
A non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method.
The embodiment of the invention has the following advantages:
according to the collaborative office method, a certain amount of contradictory dispute data are obtained, characteristic information of the contradictory dispute data is extracted, and a training set is constructed based on the characteristic information; constructing a contradiction dispute grade assessment model; inputting the training set into the contradictory dispute class assessment model for training to obtain a trained contradictory dispute class assessment model; extracting characteristic information of the to-be-classified contradiction dispute data, inputting the characteristic information of the to-be-classified contradiction dispute data into the trained contradiction dispute class assessment model, and obtaining contradiction dispute class information corresponding to the to-be-classified contradiction dispute data; based on the contradiction dispute grade information, the contradiction dispute data are reported to the corresponding grade approval roles for approval processing, so that the problem that intelligent grade evaluation cannot be carried out on the contradiction dispute data in the prior art, and the contradiction dispute data are distributed to the corresponding approval roles according to the grade for approval is solved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It will be apparent to those skilled in the art from this disclosure that the drawings described below are merely exemplary and that other embodiments may be derived from the drawings provided without undue effort.
The structures, proportions, sizes, etc. shown in the present specification are shown only for the purposes of illustration and description, and are not intended to limit the scope of the invention, which is defined by the claims, so that any structural modifications, changes in proportions, or adjustments of sizes, which do not affect the efficacy or the achievement of the present invention, should fall within the scope of the invention.
FIG. 1 is a flow chart of a method for collaborative office according to the present invention;
FIG. 2 is a first architecture diagram of a system for collaborative offices of the present invention;
FIG. 3 is a second architecture diagram of the system for collaborative offices of the present invention;
fig. 4 is a schematic diagram of an entity structure of an electronic device according to the present invention.
Wherein the reference numerals are as follows:
the system comprises an acquisition module 10, a characteristic information extraction module 20, a construction module 30, a training module 40, a contradiction dispute grade assessment model 50, a reporting module 60, a permission setting module 70, a junction circulation module 80, a withdrawal and promotion module 90, a change module 100, an electronic device 110, a processor 1101, a memory 1102 and a bus 1103.
Detailed Description
Other advantages and advantages of the present invention will become apparent to those skilled in the art from the following detailed description, which, by way of illustration, is to be read in connection with certain specific embodiments, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Examples
Fig. 1 is a flowchart of an embodiment of a method for collaborative office according to the present invention, and as shown in fig. 1, the method for collaborative office according to the embodiment of the present invention includes the following steps:
s101, acquiring a certain amount of contradictory dispute data, extracting characteristic information of the contradictory dispute data, and constructing a training set based on the characteristic information;
specifically, staff of each unit letters and visits a working department, the module is used for inputting the contradiction and dispute problems which are checked out by the unit, contradiction and dispute data are generated based on the contradiction and dispute problems, and a contradiction and dispute checking and resolving work table account is formed. And labeling the contradictory dispute data to obtain a plurality of contradictory dispute data carrying labeling labels, wherein the labeling labels comprise high risk, medium risk and low risk. The high risk contradiction dispute data corresponds to a first trial batch role, the medium risk contradiction dispute data corresponds to a second trial batch role, and the low risk contradiction dispute data corresponds to a third trial batch role. And for the problems needing to be concerned by the upper-level units, after the input, the examination and approval are completed, the manager reports the problems, whether the problems needing to be concerned by the upper-level units are examined step by step, and the related information is known and mastered in a layering level.
S102, constructing a contradiction dispute grade assessment model;
s103, inputting the training set into a contradictory dispute class assessment model for training to obtain a trained contradictory dispute class assessment model;
specifically, the characteristic information is divided into a training set, a verification set and a test set;
training the contradictory dispute class assessment model based on the training set;
performing performance evaluation on the trained contradictory dispute class evaluation model based on the verification set to obtain a contradictory dispute class evaluation model meeting performance conditions;
and evaluating the segmentation result of the contradictory dispute grade evaluation model meeting the performance condition based on the test set to obtain an evaluation index corresponding to the contradictory dispute grade evaluation model.
Performing performance evaluation on the trained contradictory dispute class evaluation model based on the verification set to obtain a contradictory dispute class evaluation model meeting performance conditions; and evaluating the evaluation result of the contradictory dispute grade evaluation model meeting the performance condition based on the test set to obtain an evaluation index corresponding to the contradictory dispute grade evaluation model. Performing performance evaluation on the contradiction dispute grade evaluation model to obtain a percentage score (namely, the highest score is 100 points and the lowest score is 0 points), and determining the contradiction dispute grade evaluation model with the score larger than a set value based on the percentage score, wherein the contradiction dispute grade evaluation model with the score larger than 90 points is the contradiction dispute grade evaluation model meeting the performance condition;
and carrying out evaluation index calculation on the contradictory dispute grade evaluation model meeting the performance condition to obtain evaluation indexes of the contradictory dispute grade evaluation model, and calculating to obtain an evaluation value corresponding to each evaluation index, wherein the evaluation value is used for representing the capability value of the contradictory dispute grade evaluation model on the evaluation indexes.
S104, extracting characteristic information of the dispute data to be classified.
S105, inputting the characteristic information of the to-be-classified contradiction dispute data into a trained contradiction dispute class assessment model to obtain contradiction dispute class information corresponding to the to-be-classified contradiction dispute data.
S106, reporting the contradiction dispute data to the approval roles of the corresponding grades based on the contradiction dispute grade information to carry out approval processing;
specifically, establishing a permission database, wherein the permission database comprises approval role information and permission information corresponding to each approval role;
and establishing the relationship between the approval role and the authority, and carrying out association.
The approval roles participating in the approval process comprise a first approval role, a second approval role and a third approval role;
the first trial role processes the contradiction and dispute data with high risk as grade information;
the second trial role processing grade information is contradiction dispute data of the risk;
and the third trial role processes the contradiction and dispute data with low risk as grade information.
After the approval of the contradictory dispute data is completed by the approval role, transacting and circulating the matters corresponding to the contradictory dispute data;
and when the contradiction dispute data is not approved by the approval role, carrying out withdrawal operation and backlog operation on the matters corresponding to the not approved contradiction dispute data based on the requirement information.
When the contradictory dispute data is changed, obtaining change information, and sending the change information to the corresponding approval roles for approval.
The letter work management department receives the auditing message through waiting to do, checks the related information, fulfills auditing and approval procedures, and submits to complete auditing and approval registration. The information can be screened and checked according to the conditions of item types, examination forms and the like.
For the selected problems needing to be concerned by the superior units, the manager selects reporting and then flows to staff of the superior unit letter visit working department. The staff and the units of the upper level visit to inquire the contradiction and dispute problems, and report the contradiction and dispute problems to the examination and approval together to form a standing book (the high risk, the medium risk and the low risk are also selected for the contradiction and dispute problems recorded in the upper level), and the same flow needing the attention of the upper level is selected and reported, and then the attention of the upper level unit is reported.
After the responsibility units update the related disputes, the units at all levels can synchronously see the update information and the accessory data. The archival material can be uploaded as new advances in contradiction resolution work exist, including: the method mainly comprises the steps of main situations of contradictory disputes, main resolving measures of the contradictory disputes, resolving results of the contradictory disputes and related suggestions for effectively implementing resolving measures of the contradictory disputes.
The sponsor submits the examination and approval comments, the corresponding management responsible person needs to fill in the examination and approval comments, and after the approval comments are approved by the responsible person, the contradiction disputes are examined, converted and the transaction circulation is conducted.
The administrator may edit the summary ledger.
The authorized user can add, delete, check, change and the like the standing book. The upper level unit can check the lower level unit ledger. And exporting the recorded contradiction dispute information ledger to the local according to the selected field.
The user enters a social stability risk assessment list page, an upper level unit can check a lower level unit account, the user can set screening options in a self-defined mode, and information is checked correspondingly according to screening content; only a certain manager is supported to set whether the form field is displayed or not and to take effect uniformly.
The live logging module supports withdrawal and reissue operations for live transactions, and retransmission functions for withdrawn transactions.
The staff of each unit uses the module, can select the local file to upload, import the contradiction information, and return the import result; and supporting the user to select the account information download file to be exported to the local.
According to the method for collaborative office, a certain amount of contradiction dispute data are obtained, characteristic information of the contradiction dispute data is extracted, and a training set is constructed based on the characteristic information; constructing a contradiction dispute grade assessment model; inputting the training set into the contradictory dispute class assessment model for training to obtain a trained contradictory dispute class assessment model; extracting characteristic information of dispute data to be classified; inputting the feature information of the to-be-classified contradiction dispute data into the trained contradiction dispute class assessment model to obtain the contradiction dispute class information corresponding to the to-be-classified contradiction dispute data; and reporting the contradiction dispute data to the approval roles of the corresponding grades based on the contradiction dispute grade information for approval processing. The method solves the problem that in the prior art, intelligent grade evaluation cannot be carried out on the contradictory dispute data, and the contradictory dispute data is distributed to corresponding approval roles according to grades for approval.
The maintenance management is mainly suitable for a interview manager, provides various effective information supports for the interview manager, records maintenance information and improves a maintenance system. The front-end function of the system mainly comprises the input, approval and deletion of the contradictory dispute ledgers; registering social stability risk assessment information, checking information and uploading information; inputting, inquiring and exporting social stability risk assessment expert database information; entering, associating, early warning, issuing and checking a stable risk source account; each dimension analyzes data statistics, report generation and data export.
FIGS. 2-3 are flowcharts of embodiments of a system for collaborative offices according to the present invention; as shown in fig. 2-3, a system for collaborative office provided in an embodiment of the present invention includes the following steps:
an acquisition module 10 for acquiring a certain amount of contradictory dispute data;
the feature information extracting module 20 is configured to extract feature information of the contradictory dispute data and feature information of the contradictory dispute data to be classified;
a construction module 30 for constructing a training set based on the feature information;
the training module 40 is configured to input the training set into the paradox level assessment model 50 for training, so as to obtain a trained paradox level assessment model 50;
inputting the feature information of the to-be-classified contradiction dispute data into the trained contradiction dispute class assessment model 50 to obtain the contradiction dispute class information corresponding to the to-be-classified contradiction dispute data;
and the reporting module 60 is configured to report the contradictory dispute data to the approving roles of the corresponding level for approval processing based on the contradictory dispute level information.
The acquisition module 10 is further configured to:
and labeling the contradictory dispute data to obtain a plurality of contradictory dispute data carrying labeling labels, wherein the labeling labels comprise high risk, medium risk and low risk.
The training module 40 is further configured to:
dividing the characteristic information into a training set, a verification set and a test set;
training the contradictory dispute rating assessment model 50 based on the training set;
performing performance evaluation on the trained contradictory dispute class evaluation model 50 based on the verification set to obtain a contradictory dispute class evaluation model 50 meeting performance conditions;
and evaluating the segmentation result of the contradictory dispute class evaluation model 50 meeting the performance condition based on the test set to obtain an evaluation index corresponding to the contradictory dispute class evaluation model 50.
The system for collaborative offices further includes a rights setting module 70, the rights setting module 70 further being configured to:
establishing a permission database, wherein the permission database comprises approval role information and permission information corresponding to each approval role;
and establishing the relationship between the approval role and the authority, and carrying out association.
The approval roles participating in the approval process comprise a first approval role, a second approval role and a third approval role;
the first trial role processes the contradiction and dispute data with high risk as grade information;
the second trial role processing grade information is contradiction dispute data of the risk;
and the third trial role processes the contradiction and dispute data with low risk as grade information.
The transaction circulation module 80 is configured to perform transaction circulation on items corresponding to the contradictory dispute data after the contradictory dispute data is approved by the approval role;
the withdrawal and sponsoring module 90 is configured to, when the contradictory dispute data is not approved by the approval character, perform a withdrawal operation and a sponsoring operation on items corresponding to the not approved contradictory dispute data based on the requirement information.
And the change module 100 is used for acquiring change information when the contradictory dispute data is changed, and sending the change information to the corresponding approval roles for approval.
According to the system for collaborative office, a certain amount of contradiction dispute data is acquired through the acquisition module 10; extracting feature information of the contradictory dispute data and feature information of the contradictory dispute data to be classified by the feature information extraction module 20; building a training set based on the feature information by a building module 30; inputting the training set into the contradictory dispute class assessment model 50 through a training module 40 for training to obtain a trained contradictory dispute class assessment model 50; inputting the feature information of the to-be-classified contradiction dispute data into the trained contradiction dispute class assessment model 50 to obtain the contradiction dispute class information corresponding to the to-be-classified contradiction dispute data; the report module 60 reports the dispute data to the approval roles of the corresponding grades for approval processing based on the dispute grade information.
Fig. 4 is a schematic diagram of an entity structure of an electronic device according to an embodiment of the present invention, as shown in fig. 4, an electronic device 110 includes: a processor 1101 (processor), a memory 1102 (memory), and a bus 1103;
the processor 1101 and the memory 1102 perform communication with each other through a bus 1103;
the processor 1101 is configured to invoke program instructions in the memory 1102 to perform the methods provided by the above-described method embodiments, for example, including: acquiring a certain amount of contradictory dispute data, extracting characteristic information of the contradictory dispute data, and constructing a training set based on the characteristic information; constructing a contradiction dispute grade assessment model; inputting the training set into the contradictory dispute class assessment model for training to obtain a trained contradictory dispute class assessment model; extracting characteristic information of dispute data to be classified; inputting the feature information of the to-be-classified contradiction dispute data into the trained contradiction dispute class assessment model to obtain the contradiction dispute class information corresponding to the to-be-classified contradiction dispute data; and reporting the contradiction dispute data to the approval roles of the corresponding grades based on the contradiction dispute grade information for approval processing.
The present embodiment provides a non-transitory computer readable storage medium storing computer instructions that cause a computer to perform the methods provided by the above-described method embodiments, for example, including: acquiring a certain amount of contradictory dispute data, extracting characteristic information of the contradictory dispute data, and constructing a training set based on the characteristic information; constructing a contradiction dispute grade assessment model; inputting the training set into the contradictory dispute class assessment model for training to obtain a trained contradictory dispute class assessment model; extracting characteristic information of dispute data to be classified; inputting the feature information of the to-be-classified contradiction dispute data into the trained contradiction dispute class assessment model to obtain the contradiction dispute class information corresponding to the to-be-classified contradiction dispute data; and reporting the contradiction dispute data to the approval roles of the corresponding grades based on the contradiction dispute grade information for approval processing.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware associated with program instructions, where the foregoing program may be stored in a computer readable storage medium, and when executed, the program performs steps including the above method embodiments; and the aforementioned storage medium includes: various storage media such as ROM, RAM, magnetic or optical disks may store program code.
The apparatus embodiments described above are merely illustrative, wherein elements illustrated as separate elements may or may not be physically separate, and elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on such understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the embodiments or the methods of some parts of the embodiments.
While the invention has been described in detail in the foregoing general description and specific examples, it will be apparent to those skilled in the art that modifications and improvements can be made thereto. Accordingly, such modifications or improvements may be made without departing from the spirit of the invention and are intended to be within the scope of the invention as claimed.
Claims (10)
1. A method for collaborative office, the method comprising:
acquiring a certain amount of contradictory dispute data, extracting characteristic information of the contradictory dispute data, and constructing a training set based on the characteristic information;
constructing a contradiction dispute grade assessment model;
inputting the training set into the contradictory dispute class assessment model for training to obtain a trained contradictory dispute class assessment model;
extracting characteristic information of dispute data to be classified;
inputting the feature information of the to-be-classified contradiction dispute data into the trained contradiction dispute class assessment model to obtain the contradiction dispute class information corresponding to the to-be-classified contradiction dispute data;
and reporting the contradiction dispute data to the approval roles of the corresponding grades based on the contradiction dispute grade information for approval processing.
2. The method for collaborative office according to claim 1, wherein the obtaining a quantity of contradictory dispute data, extracting feature information of the contradictory dispute data, and constructing a training set based on the feature information, comprises:
and labeling the contradictory dispute data to obtain a plurality of contradictory dispute data carrying labeling labels, wherein the labeling labels comprise high risk, medium risk and low risk.
3. The method for collaborative office according to claim 1, wherein the inputting the training set into the contradictory dispute rating assessment model for training to obtain a trained contradictory dispute rating assessment model comprises:
dividing the characteristic information into a training set, a verification set and a test set;
training the contradictory dispute class assessment model based on the training set;
performing performance evaluation on the trained contradictory dispute class evaluation model based on the verification set to obtain a contradictory dispute class evaluation model meeting performance conditions;
and evaluating the segmentation result of the contradictory dispute grade evaluation model meeting the performance condition based on the test set to obtain an evaluation index corresponding to the contradictory dispute grade evaluation model.
4. The method for collaborative office according to claim 1, further comprising:
responding to an establishing request of role information, and establishing a permission database, wherein the permission database comprises approval role information and permission information corresponding to each approval role;
and establishing the relationship between the approval role and the authority, and carrying out association.
5. The method for collaborative office according to claim 4, further comprising:
the approval roles participating in the approval process comprise a first approval role, a second approval role and a third approval role;
the first trial role processes the contradiction and dispute data with high risk as grade information;
the second trial role processing grade information is contradiction dispute data of the risk;
and the third trial role processes the contradiction and dispute data with low risk as grade information.
6. The method for collaborative office according to claim 1, further comprising:
after the approval of the contradictory dispute data is completed by the approval role, transacting and circulating the matters corresponding to the contradictory dispute data;
and when the contradiction dispute data is not approved by the approval role, carrying out withdrawal operation and backlog operation on the matters corresponding to the not approved contradiction dispute data based on the requirement information.
7. The method for collaborative office according to claim 1, further comprising:
when the contradictory dispute data is changed, obtaining change information, and sending the change information to the corresponding approval roles for approval.
8. A system for collaborative offices, comprising:
the acquisition module is used for acquiring a certain amount of contradictory dispute data;
the feature information extraction module is used for extracting feature information of the contradictory dispute data and feature information of the contradictory dispute data to be classified;
the construction module is used for constructing a training set based on the characteristic information;
the training module is used for inputting the training set into the contradictory dispute grade assessment model for training to obtain a trained contradictory dispute grade assessment model;
inputting the feature information of the to-be-classified contradiction dispute data into the trained contradiction dispute class assessment model to obtain the contradiction dispute class information corresponding to the to-be-classified contradiction dispute data;
and the reporting module is used for reporting the contradiction dispute data to the approval roles of the corresponding grades for approval processing based on the contradiction dispute grade information.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 7 when the computer program is executed.
10. A non-transitory computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310918297.9A CN116957502A (en) | 2023-07-25 | 2023-07-25 | Method and system for collaborative office |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310918297.9A CN116957502A (en) | 2023-07-25 | 2023-07-25 | Method and system for collaborative office |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116957502A true CN116957502A (en) | 2023-10-27 |
Family
ID=88456110
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310918297.9A Pending CN116957502A (en) | 2023-07-25 | 2023-07-25 | Method and system for collaborative office |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116957502A (en) |
-
2023
- 2023-07-25 CN CN202310918297.9A patent/CN116957502A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112395325A (en) | Data management method, system, terminal equipment and storage medium | |
| CN109271368B (en) | Database system and maintenance method of fire safety assessment system | |
| CN104217276A (en) | Rule-based automatic auditing method and system | |
| US20090204517A1 (en) | Intercompany accounting data analytics | |
| US10430413B2 (en) | Data information framework | |
| US20150019303A1 (en) | Data quality integration | |
| CN111897866B (en) | Remote sensing monitoring image spot docking system and application method thereof | |
| CN113408890A (en) | Artificial intelligence-based method and system for generating evaluation report after industrial investment project | |
| CN113807747A (en) | Enterprise budget management maturity evaluation system | |
| CN104899143A (en) | Software peer review system realizing device for providing DM (Data Mining) | |
| CN111178680A (en) | Wind power plant engineering quality overall process management system, method and equipment | |
| CN105868956A (en) | Data processing method and device | |
| CN117827792A (en) | Data asset management method and system | |
| CN113065737A (en) | DevOps-based efficiency measurement method and system | |
| CN116957502A (en) | Method and system for collaborative office | |
| CN111415138A (en) | Creative processing method and system, client and server | |
| CN111191086A (en) | Test data identification method | |
| CN116796950A (en) | Online review system and method for power distribution network project capable of being researched | |
| CN111160681A (en) | Method, device and storage medium for evaluating user income level based on user income and expenditure data | |
| CN115600972A (en) | Method, device, equipment and storage medium for verifying and selling of bad assets | |
| CN113010611A (en) | Method and system for automatically generating relations between relational database tables | |
| CN115564332B (en) | Government risk analysis method and system based on big data | |
| CN114298831A (en) | Enterprise rating system based on artificial intelligence algorithm | |
| CN113610594B (en) | Equipment review price data processing method and system | |
| CN113674115B (en) | University data management auxiliary system and method based on data management technology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |