CN115392698A - Complicated and simplified distribution method for execution item intensive management platform - Google Patents
Complicated and simplified distribution method for execution item intensive management platform Download PDFInfo
- Publication number
- CN115392698A CN115392698A CN202211019499.1A CN202211019499A CN115392698A CN 115392698 A CN115392698 A CN 115392698A CN 202211019499 A CN202211019499 A CN 202211019499A CN 115392698 A CN115392698 A CN 115392698A
- Authority
- CN
- China
- Prior art keywords
- case
- complex
- rule
- cases
- rules
- 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 43
- 230000008569 process Effects 0.000 claims abstract description 10
- 238000004422 calculation algorithm Methods 0.000 claims description 28
- 238000004458 analytical method Methods 0.000 claims description 15
- 238000005192 partition Methods 0.000 claims description 10
- 238000013507 mapping Methods 0.000 claims description 6
- 230000006399 behavior Effects 0.000 claims description 5
- 230000008030 elimination Effects 0.000 claims description 5
- 238000003379 elimination reaction Methods 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000007405 data analysis Methods 0.000 claims description 3
- 238000012546 transfer Methods 0.000 claims description 3
- 230000007717 exclusion Effects 0.000 claims description 2
- 210000000056 organ Anatomy 0.000 claims description 2
- 238000005516 engineering process Methods 0.000 description 3
- 238000004321 preservation Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000011835 investigation Methods 0.000 description 2
- 238000013508 migration Methods 0.000 description 2
- 230000005012 migration Effects 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000003058 natural language processing Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 238000005728 strengthening Methods 0.000 description 1
Images
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
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2455—Query execution
- G06F16/24564—Applying rules; Deductive queries
-
- 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
- G06Q50/18—Legal services
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- Tourism & Hospitality (AREA)
- Economics (AREA)
- General Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- General Health & Medical Sciences (AREA)
- Operations Research (AREA)
- Health & Medical Sciences (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Technology Law (AREA)
- Game Theory and Decision Science (AREA)
- Primary Health Care (AREA)
- Quality & Reliability (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses a complex and simple distribution method for an execution item intensive management platform, which comprises the following steps: configuring an element, wherein the element is converted from a case characteristic which can be defined and inquired in the system; configuring rules, wherein the rules are conditions for judging the complex and simple cases by combining one or more elements; wherein, the rule judging system comprises: according to the rule relation judgment, configuring the priority identification sequence of the complex case and the simple case, configuring the relation 'and', 'or' between a plurality of rules, and calculating the complex case and the simple case according to the identification sequence and the rule relation; and (4) according to the total score rule, configuring the simple case and the complex case score intervals, and according to the final case score falling in the score intervals, calculating the complex case and the simple case. The invention can accurately identify complex and simple cases according to the case characteristics, reasonably distribute the cases to the most suitable judges, reduce the labor force for manual identification to the maximum extent, and really realize an intensive case handling process for complex and simple distribution and specially-assigned persons.
Description
Technical Field
The invention relates to a technology for automatically identifying cases executed by a court, in particular to a complex and simple distribution method of an execution item intensive management platform.
Background
The traditional court system assigns cases according to the complexity of the cases through manual judgment. Many cases can not distinguish the complexity at a glance, manual checking is needed, and the case handling process is time-consuming and is not very willing to be implemented, so that the case handling process cannot be intensified, and the efficiency is low.
The prior art is used for complex and simple case identification, and the following problems exist: the recognition rules applicable to cases handled by various courts are not fully considered, and deviation between the recognition result of the partial case and the actual result may be caused.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides the complex and simple shunt method of the execution item intensive management platform, which can reduce the time for manually checking the complex and simple cases, thereby promoting complex and simple shunt case handling, realizing intensive management during handling and greatly improving case handling efficiency.
The purpose of the invention is realized by the following technical scheme.
A complex and simple distribution method for an execution item intensive management platform comprises the following steps:
s1, analyzing and converting into elements according to case characteristics which can be defined and inquired in a system;
s2, analyzing the most appropriate rule configuration according to the case handling process of each court officer;
and S3, according to the rule combination system and the score system, performing complex and simple distribution through dynamic programming and a numerical analysis algorithm.
Through court case characteristics, convert into corresponding element, make up the rule with the element again, specifically do: the method comprises the steps of combing specific case characteristics according to court handling cases, wherein the case characteristics comprise major cases, civil involvement, behavior execution, application of execution subject amount, enough compensation of checking and controlling or property protection, property checking, harm elimination, forcible removal, house transfer, real property needing to be treated, vehicles and machine equipment, upper-level court dealing, supervision cases, the number of parties, cases, difficult cases, contradiction excited cases, major cases of the court, party institutions, military involvement, simple small-amount cases, fussy small-amount cases, only harmonious execution and full-amount protection, mapping corresponding case characteristics to a corresponding calculation method, converting the corresponding case characteristics into elements, and establishing a rule identification system and a score identification system for each element.
According to the complex and simple shunt elements, intelligent identification is converted through dynamic programming and a numerical analysis algorithm, and the method specifically comprises the following steps: the rule system is characterized in that elements are combined into a 'AND', 'OR' recognition sequence rule and a score system through a dynamic programming algorithm, and the elements form a complex case and a simple case scoring interval through a weight score and a numerical analysis algorithm.
The method for forming the simplified and complicated division rule of each court comprises the following steps:
according to the complex and simple distribution rule system, complex cases and simple case combination rules are formed according to elements to obtain all rule combinations applicable to court, rules for preferentially identifying the complex cases and the simple cases are configured, and then mutual exclusion or complementation is configured among a plurality of rules of the complex cases and the simple cases;
according to the complex and simple distribution scoring system, binding weight scores to each element, then forming complex cases and simple case combination rules, and configuring inter-partition complex cases [ min, max ] and simple cases [ min, max ];
the complex and simple characteristics of the case to be handled are intelligently and accurately identified by using a recursive algorithm according to the complex and simple priority identification sequence and the complex and simple combination rule relation;
and (4) performing numerical analysis on the characteristic scores of the handled cases falling between the simplified and unsimplified scoring areas by using a Leeberg measure algorithm, and intelligently and accurately identifying the simplified and unsimplified characteristics of the handled cases.
Executing the steps through an element establishing module, a rule establishing module and an intelligent identification module;
the element establishing module is used for establishing a relation between elements and case characteristics by using a star model so as to analyze multi-dimensional case characteristic attributes for establishing a rule identification system and a score identification system as data bases; the element establishing module is used for combining simplified and simplified rules and establishing a simplified and simplified identification model; the rule establishing module selects elements to form a complex and simple rule according to different combination relations.
The element establishing module is specifically configured to: and (4) performing feature combing and summarizing on the court office by big data analysis, and combining execution targets and case related rules to establish a rule module by element combination.
The rule establishing module is specifically configured to: and establishing an intelligent learning model according to the characteristics of cases handled by the court, and establishing an intelligent identification model according to the intelligent learning model and the complex and simple distribution rule suitable for cases in the court.
Compared with the prior art, the invention has the advantages that: the invention can accurately identify complex and simple cases fully according to case characteristics, reasonably distributes the cases to the most suitable judges, reduces manpower for artificial identification to the greatest extent, is beneficial to reducing the conditions of more time consumption and unreasonable flow distribution for complex and simple identification and flow distribution, thereby effectively improving the efficiency of executing the cases by the judges, truly achieving complex and simple flow distribution and an intensive case handling process for specially-assigned persons.
Drawings
FIG. 1 is a schematic flow chart of a courthouse automatic identification complex and simple algorithm provided by the invention;
FIG. 2 is a detailed flowchart of step S3 in the automatic court letters identification and reduction algorithm provided by the present invention;
FIG. 3 is a schematic structural diagram of an automatic courthouse identification complexity system provided by the present invention;
Detailed Description
The invention is described in detail below with reference to the drawings and specific examples.
The method comprises the steps of firstly creating an element management configuration function, namely an element establishing module, sorting out case characteristics such as major cases, civil affairs, behavior execution, application of the amount of an execution target, enough compensation of checking and controlling or maintaining property, property checking, harm elimination, forced demolition, house migration, real property needing to be handled, vehicles and machine equipment and other high-value dynamic cases according to big data analysis cases, and characteristics such as superior court handling cases, supervision cases, the number of parties, case causes, difficult cases, contradiction excited cases, major cases of a hospital, party administration institutions, army, small-amount case (short), small-amount case (reproduction), negotiation execution only, full-amount maintenance and the like, using the case characteristics as names of elements created in the system, binding the case types such as the first execution case, execution recovery case and execution case after the elements are created, then binding SQL capable of defining and inquiring in the element binding system, directly judging the conditions of the case searching or converting the case types according to SQL of the search results, and judging whether the cases types are the types of the cases defined and the final saving cases. In conclusion, star modeling is performed.
Then, a rule management configuration function is established, namely a rule establishing module, a shunting rule is established according to case types such as a case to be executed for the first time and a case to be recovered to be executed, rule names are established according to courts and case types, a proper rule mode is formulated for the courts through the courts handled by the courts, the traditional Chinese and simple ratio and the case handling procedures of the courts handled by the courts are analyzed, and a proper rule mode is formulated for the courts according to a pure rule system and a proper score system;
the pure rule system is created, sub-rules such as a simple case rule set, a complex case rule set and the like are created in the rules according to the case type creation rules, courts and case type naming, and the rule set building process includes the steps of firstly selecting corresponding elements according to a complex and simple rule set and building a set rule name and a set rule description. Then, according to the individual requirements of each court, establishing the sequence of preferentially identifying the complex case and the simple case, and finally setting the effective relation ' or ' and ' of the complex and simple set rules.
And establishing the scoring system rule, establishing a rule according to the executed case type, and naming according to the court and the case type. The method comprises the steps of creating sub-rules such as a simple rule set and a complex rule set in a rule, and during the rule set establishment process, firstly, selecting corresponding elements according to the complex rule set, establishing a set rule name and a set rule description, defining a weight score for each sub-rule, and calculating the total score for subsequent use by the weight score. Then setting up the simple case division [ min, max ] and the complex case division [ min, max ] according to the individual requirements of each court.
The court automatic identification complex and simple method specifically comprises the following steps: obtaining a corresponding configuration rule according to the case type of the case currently handled by the court, finding a corresponding sub-rule according to the rule, namely a complex case set rule List < TRULEFa >, a simple case set rule List < TRULEJa >, traversing the set rule, finding query SQL configured in a binding element in the sub-rule, bringing a case identifier into the SQL as a query condition to query case characteristics or further performing service logic processing on a query result to convert the characteristics of the complex case which can be qualitatively determined, and finally calculating the complex type of the current case according to the recognition sequence of the complex case in the rule configuration, the ' or ' and ' relation of the rule combination by a program through a recursive algorithm and four arrangement combinations, wherein 1 preferentially recognizes the complex case and the rule combination or 2 preferentially recognizes the complex case and the rule combination, 3 preferentially recognizes the simple case and the rule combination or 4 preferentially recognizes the simple case and the rule combination to calculate the complex type of the current case
The court automatic identification complex and simple method specifically comprises the following scoring systems: and obtaining a rule which is correspondingly configured according to the case type of the case currently worked by the court, finding a corresponding sub-rule, namely a complex and simple set rule according to the rule, calculating the sum of the weight scores meeting the conditions in the set rule by a program through a recursive algorithm, and calculating the complex and simple of the case by falling between the simple case scoring areas or the complex case scoring areas.
Examples
As shown in fig. 1-3, a method for performing complex and simple splitting of an event intensive management platform includes the following steps:
s1, analyzing and converting into elements according to case characteristics which can be defined and inquired in a system;
s2, analyzing the most appropriate rule configuration according to the case handling process of each court officer;
and S3, according to the rule combination system and the score system, performing complex and simple distribution through dynamic programming and a numerical analysis algorithm.
In the embodiment of the invention, it can be understood that the characteristics of court cases are analyzed by combing, the characteristics are converted into element configuration by a star modeling means, and then the element configuration is bound to the case type. Rules are then established, case types are first selected, then elements that have been bound to case types can be selected, and then recognition orders, combined relationships 'or', 'and' between rules, rule scoring weights are configured. The program matches the algorithm corresponding to the identified case according to a recursive algorithm. The recursive matching is found in two ways, one of which is matched with the optimal rule of the current case according to the rule configuration sequence and the rule combination relationship. And according to the two groups of cases, the total score of the current case falls into a complex case interval [ Fmin, fmax ] or a simple case interval [ Jmin, jmax ] according to a numerical analysis algorithm, and finally the complex and simple types of the current case are identified.
Elements which accord with the case characteristics are matched according to the case types by utilizing a recursive algorithm, so that corresponding rules are found, and the complexity of the case is automatically identified.
As a specific implementation mode of the embodiment of the invention, an element system model is established according to the characteristics of case handling in the court, elements are bound to the case types, and then a rule system is established.
In the embodiment of the invention, for the characteristic analysis of the court case, the corresponding characteristics of the case comprise: major cases, civil involvement, behavior execution, application of execution target amount, investigation and control or property preservation of large-value animal cases such as enough compensation, property non-investigation, harm elimination, forced demolition, house transfer, real property treatment, vehicles and machine equipment and the like, and upper-level court submission, supervision cases, the number of people involved, cases, difficult cases, contradiction excited cases, major cases of the home, party administration organs, military involvement, small-amount case (simple), small-amount case (complex), cooperative execution only and full-amount preservation; the method mainly converts the characteristics into element configuration, and SQL can be flexibly and dynamically configured in the elements to inquire out corresponding characteristic judgment information. And binding the elements to case types, and finally combining into a multi-block rule group.
As a specific implementation way of the embodiment of the invention, different elements are bound according to different case types, and the elements are combined into rules in the same case type; and calculating the complex and simple types of the cases through configuration of complex and simple recognition sequences and rule combination relations.
In the embodiment of the invention, the automatic courseware case identification, reduction and multiplication algorithm provided by the invention establishes a score model according to cases handled by a court; wherein the scoring model of the court is: according to the features of the cases, weight scores are analyzed and given, then partition keys of the frequently-scored partition and the simply-scored partition are defined, and finally the final score of the current case is calculated through a numerical analysis algorithm to determine the frequently-scored partition and the simply-scored partition so as to identify the cases.
As a specific implementation mode of the embodiment of the invention, the intelligent complex and simple case recognition system calculates the total score of cases through a numerical analysis algorithm, and further calculates whether the score of the case is in a complex case interval or a simple case interval, and the method comprises the following steps of:
s281, configuring rule identification sequence and rule combination relation according to the rule combination system to obtain rule combinations configured under various cases;
s282, according to the scoring system and the element configuration weight scores, configuring a complex case obtaining partition space [ Fmin, fmax ] and a simple case obtaining partition space [ Jmin, jmax ], and calculating the total rule score of the current case configuration;
and S283, calculating the characteristics of the case or calculating the weight fraction of the rule to judge the complexity of the case according to the elements in the rule after the rule is determined according to the case type recursion matching rule by using the dynamic rule and the numerical analysis algorithm.
And mapping the characteristics of each court case into element definitions by using recursion, dynamic rules and numerical analysis algorithms in an intelligent complex and simple recognition system, and binding case types and element combination rule relations by using the elements to finish recognition of complex and simple branches.
As a specific implementation of the embodiment of the present invention, the element system module 101 is specifically configured to:
and analyzing the weight coefficient of each judge by using a natural language processing method, and establishing a star-shaped element system model.
In the embodiment of the invention, for element mapping and combing analysis, specific case characteristics are combed according to court cases, including major cases, civil-related cases, behavior execution, application of execution target values, sufficient compensation of checking and controlling or maintaining properties, property checking, harm elimination, forced removal, house migration, real property needing to be handled, vehicles and machine equipment and other high-value dynamic cases, and superior court handling, supervision cases, parties, cases, difficult cases, contradiction excited cases, local major cases, administrative parties, military agencies, small-amount cases (brief), small-amount cases (complex), only harmonious execution, full-amount preservation and the like, and the corresponding case characteristic mapping calculation method is converted into elements, so that effective data support can be provided for case complex and brief identification.
As a specific implementation manner of the embodiment of the present invention, the rule system module 102 is specifically configured to:
binding case types according to element configurations derived from case characteristics; and configuring a combination relation and an identification sequence in a combination mode for calculating the rule combination of various case types.
In the embodiment of the invention, the automatic complex and simple court case recognition algorithm provided by the invention establishes an intelligent recognition model according to the characteristic data of court cases; wherein the recognition model comprises: case characteristics of each court and rule combination of each court, wherein the rule combination comprises a sequential identification rule, a combination rule and a score rule for judging case complexity by the court.
As a specific implementation manner of the embodiment of the present invention, the scoring system module 103 is specifically configured to:
according to case feature derived element configuration, adding weights to elements for re-classification, binding case types, forming simplified rules according to case types, then formulating a complicated case score interval [ Fmin, fmax ] and a simplified case score interval [ Jmin, jmax ] according to big data, wherein the interval is used for calculating the total number of the complicated case scores and the total number of the simplified case scores after the current case type rule combination fall between the complicated case scores and the simplified case scores, and therefore the complicated case is calculated.
In the embodiment of the invention, the case characteristic result set is bound into various cases through element derivation and rule combination according to the case types, and the matching rules are found out through a recursive algorithm according to the case types during recognition, so that the complexity of the cases is calculated.
The embodiment of the invention has the following beneficial effects:
(1) The method provided by the invention fully combines the procedure of case handling in the court, so that the complicated and simple case shunting handling has data guarantee and data support, and the cases can be accurately and rapidly shunted out through the soundness of element modules and the rule combination and optimization, thereby accelerating the case handling efficiency and actively responding to the complicated and simple shunting reform called by the highest hospital number;
(2) The method provided by the invention can accelerate the case handling efficiency of small-amount litigation, greatly improve the rate of case handling, reduce the trial period of cases, refine the applicable standard, optimize the trial process, establish special teams, strengthen the quality control and comprehensively improve the quality of small-amount litigation cases.
(3) The invention perfects simple program rules. Simple procedure for simple civil cases to be announced can be applied. The simplified rules of the simple program case court trial and the referee document are defined, and the simple program trial limit regulation is perfected.
(4) The invention insists on strengthening the technology drive. The method fully utilizes modern technological means such as big data, cloud computing, artificial intelligence and the like to solve the reformation problem, improves judicial ability, and adopts advanced application of technological means such as intelligent assistance, intelligent execution and the like, appropriately enlarges the coverage range of online litigation, and promotes the realization of deep fusion of a trial mode, a litigation system and the internet technology.
Claims (7)
1. A complex and simple shunting method for an execution item intensive management platform is characterized by comprising the following steps:
s1, analyzing and converting into elements according to case characteristics which can be defined and inquired in a system;
s2, analyzing the most appropriate rule configuration according to the case handling process of each court officer;
and S3, according to the rule combination system and the score system, performing complex and simple distribution through dynamic programming and a numerical analysis algorithm.
2. The complexity distribution method for the execution item intensive management platform as claimed in claim 1, wherein the complexity distribution method is characterized in that the complexity distribution method converts the situation characteristics of the court into corresponding elements, and combines the elements into rules, and specifically comprises the following steps: the method comprises the steps of combing specific case characteristics according to case handling of the court, wherein the case characteristics comprise major cases, civil involvement, behavior execution, application of execution target amount, enough compensation of checking and controlling or property protection, property non-checking, harm elimination, forced demolition, house transfer, real property needing to be disposed, vehicles and machine equipment, upper-level court dealing, case supervising, number of parties, case routing, difficult cases, contradiction exciting cases, case of the court, party, administrative organ, military involvement, simple small-amount litigation, complicated small-amount litigation, only issuance of harmonious execution and full-amount protection, mapping corresponding case characteristics to a calculation method, converting the mapping into elements, and establishing a rule identification system and a score identification system for each element.
3. The method for performing task intensive management platform complex and simple splitting as claimed in claim 1, wherein the complex and simple splitting elements are converted into intelligent identification through dynamic programming and numerical analysis algorithms, specifically: and in the rule system, all elements are combined into a recognition sequence rule such as 'AND', 'OR' through a dynamic programming algorithm, a score system is obtained, and all elements form a complicated case and a simple case obtaining partition through a weight score and a numerical analysis algorithm.
4. The method for performing task intensive management platform complexity offload as claimed in claim 3, wherein forming each courthouse complexity offload rule comprises the steps of:
according to the complex and simple distribution rule system, complex cases and simple case combination rules are formed according to elements to obtain all rule combinations applicable to courts, rules for preferentially identifying complex cases and simple cases are configured, and then mutual exclusion or complementation among a plurality of rules of complex cases and simple cases is configured; according to the complex and simple distribution scoring system, binding weight scores to each element, then forming complex cases and simple case combination rules, and configuring inter-partition complex cases [ min, max ] and simple cases [ min, max ];
the complex and simple characteristics of the case to be handled are intelligently and accurately identified by using a recursive algorithm according to the complex and simple priority identification sequence and the complex and simple combination rule relation;
and (3) by using a Leber lattice measure algorithm, numerically analyzing the characteristic scores of the cases handled to fall between the simplified and unsimplified scoring areas, and intelligently and accurately identifying the simplified and unsimplified characteristics of the cases handled.
5. The method for performing task intensive management platform complex and simple flow distribution according to any one of claims 1 to 4, wherein the steps are performed by an element establishing module, a rule establishing module and an intelligent identification module;
the element establishing module is used for establishing a relation between elements and case characteristics by using a star model so as to analyze multi-dimensional case characteristic attributes for establishing a rule identification system and a score identification system as data bases; the element establishing module is used for combining simplified and simplified rules and establishing a simplified and simplified identification model; and the rule establishing module selects elements to form complex and simple group rules according to different combination relations.
6. The method of claim 5, wherein the element creation module is specifically configured to: and (4) performing feature combing and summarizing on the court office by big data analysis, and combining execution targets and case related rules to establish a rule module by element combination.
7. The method of claim 5, wherein the rule establishing module is specifically configured to: and establishing an intelligent learning model according to the characteristics of cases handled by the court, and establishing an intelligent identification model according to the intelligent learning model and the complex and simple distribution rule suitable for cases in the court.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211019499.1A CN115392698A (en) | 2022-08-24 | 2022-08-24 | Complicated and simplified distribution method for execution item intensive management platform |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211019499.1A CN115392698A (en) | 2022-08-24 | 2022-08-24 | Complicated and simplified distribution method for execution item intensive management platform |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115392698A true CN115392698A (en) | 2022-11-25 |
Family
ID=84121318
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211019499.1A Pending CN115392698A (en) | 2022-08-24 | 2022-08-24 | Complicated and simplified distribution method for execution item intensive management platform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115392698A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116187714A (en) * | 2023-04-19 | 2023-05-30 | 上海金桥信息股份有限公司 | Task intelligent distribution method, system, terminal and medium based on definable rule |
-
2022
- 2022-08-24 CN CN202211019499.1A patent/CN115392698A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116187714A (en) * | 2023-04-19 | 2023-05-30 | 上海金桥信息股份有限公司 | Task intelligent distribution method, system, terminal and medium based on definable rule |
| CN116187714B (en) * | 2023-04-19 | 2023-08-04 | 上海金桥信息股份有限公司 | Task intelligent distribution method, system, terminal and medium based on definable rule |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110162611B (en) | Intelligent customer service response method and system | |
| CN115392698A (en) | Complicated and simplified distribution method for execution item intensive management platform | |
| CN110097177B (en) | Network pruning method based on pseudo-twin network | |
| CN105654025A (en) | Fingerprint identification method, apparatus and electronic equipment thereof | |
| CN108428061B (en) | DEA-GA-BP-based intelligent bid evaluation decision system and bid evaluation method | |
| CN112182221A (en) | Knowledge retrieval optimization method based on improved random forest | |
| CN112200484A (en) | Intelligent case division system and method based on strategy definition | |
| CN110968950A (en) | Human-computer cooperation disassembly sequence planning method based on personnel fatigue | |
| CN113205808A (en) | AI (Artificial intelligence) consultation based cloud computing building method and system | |
| CN112435077A (en) | Sales forecasting method | |
| CN108509610A (en) | A kind of search method and system of activity and companion | |
| CN110365020B (en) | Reactive power optimization method based on ensemble learning | |
| CN115099334A (en) | Multi-party cooperative data learning system and learning model training method | |
| Subagyo et al. | Decision Supporting System Employee Performance Appraisal Narotama University with Simple Additive Weighting Method (SAW) | |
| CN114422147A (en) | Multi-party safety calculation method based on block chain | |
| Li et al. | Grey-incidence clustering decision-making method with three-parameter interval grey number based on regret theory | |
| CN109308565B (en) | Crowd performance grade identification method and device, storage medium and computer equipment | |
| Kudinov et al. | Identification of multivariable fuzzy systems | |
| Bruckner | From auditing to auditing 4.0: the impact of artificial intelligence and blockchain technology on the business model of the big four auditing companies/Author Florian Bruckner, BSc | |
| CN110728299A (en) | Multi-extreme learning machine-based transient stability hierarchical evaluation method after power system fault | |
| CN106156184A (en) | The expert's comment inductive algorithm clustered based on emotional semantic classification and SOM | |
| CN115907674B (en) | Intelligent efficiency analysis method and system based on AI algorithm and neural engine | |
| CN115545799B (en) | Information technology service quality evaluation method, device, equipment and medium | |
| Hujala et al. | Knowledge Management for Integrated Health and Social Care–The Case of Keusote in Finland | |
| Liu et al. | Federated Learning Model Training Mechanism with Edge Cloud Collaboration for Services in Smart Cities |
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 |