CN112396539A - Implementation method of administrative law enforcement self-adaptive auxiliary system based on artificial intelligence - Google Patents
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Abstract
The invention provides an implementation method of an administrative law enforcement self-adaptive auxiliary system based on artificial intelligence, which comprises the following steps: s1: establishing a law and regulation database and a digital case database; s2: the method comprises the following steps of utilizing an artificial neural network algorithm to realize the associated deep learning between laws and regulations and administrative law enforcement cases, training and learning the applicability of the laws and regulations and the cases, and forming a law and regulation adaptive case library; s3: verifying whether the deep learning algorithm is correct by verifying that the laws and regulations are applicable to a case base; s4: and forming an artificial intelligence-based administrative law enforcement adaptive auxiliary system, and applying the system to actual administrative law enforcement. The system provided by the invention can guide law enforcement personnel to complete each law enforcement procedure link step by step according to the standard procedures, thereby realizing the standardization, programming and refinement of the administrative law enforcement case processing.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to an implementation method of an administrative law enforcement self-adaptive auxiliary system based on artificial intelligence.
Background
With the rapid development of social economy, all levels of governments of the country are completely and deeply reformed and completely control the country according to law. The governments at all levels of the state have issued a plurality of policy rules, management rules and cutting standards, and the policy rules, the management rules and the cutting standards have good regulation effect on administrative enforcement. However, in the implementation of these policy and regulation, regulatory act and regulatory standards, because of the large number, wide range of applications and complicated content of each of the rules and standards, it is difficult to apply these rules and regulations and standards and to perform law enforcement on site, and law enforcement and regulatory errors may occur. Under the condition, modern information technology, database technology, neural network technology, full text retrieval technology, hypertext link technology and the like are fully utilized, a large number of policy and regulation, management regulations and cutting standards are digitally processed, information which can be used and managed is designed to be recognized and utilized by a computer, and an administrative law enforcement self-adaptive auxiliary system based on artificial intelligence is developed on the basis of the information, so that the system is significant in the current society.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an implementation method of an administrative law enforcement self-adaptive auxiliary system based on artificial intelligence. In the law enforcement process, the system provides law enforcement flow link guidance and guides law enforcement personnel to complete the law enforcement flow links step by step according to the standard flow, thereby realizing the standardization, programming and refinement of the administrative law enforcement case processing.
In order to achieve the above purpose, the invention provides an implementation method of an administrative law enforcement adaptive auxiliary system based on artificial intelligence, which comprises the following steps:
s1: establishing a law and regulation database and a digital case database;
s2: the method comprises the following steps of utilizing an artificial neural network algorithm to realize the associated deep learning between laws and regulations and administrative law enforcement cases, training and learning the applicability of the laws and regulations and the cases, and forming a law and regulation adaptive case library;
s3: verifying whether the deep learning algorithm is correct by verifying that the laws and regulations are applicable to a case base;
s4: and forming an artificial intelligence-based administrative law enforcement adaptive auxiliary system, and applying the system to actual administrative law enforcement.
Preferably, the step S1 includes: the text files such as various laws and regulations are digitalized, normalized and formatted in a database mode to form a database of laws and regulations.
Preferably, the step S1 includes: adopting a natural language analysis processing algorithm and combining with industrial characteristics to carry out natural language semantic analysis processing and manual determination on the digitized laws and regulations, obtaining characteristic words of each laws and regulations and sequencing according to the occurrence frequency; and forming a digital case database for various information, applicable laws and regulations and terms thereof, legal documents, processing flows, cutting standards and the like in cases in actual administrative law enforcement by referring to the digitalized rules of the laws and regulations.
Preferably, the database comprises a case type table, a law and regulation table, a cutting reference table, a case example table, a case cutting guide table, a case processing information table and a case processing keyword table.
Preferably, the process of digitizing, normalizing and formatting the text files such as various laws and regulations in a database mode comprises the following steps: formatting and digitally processing the law and regulation text to form a law and regulation data table, wherein the specific format comprises basic information of the law and regulation, an application range, an upper law basis, an applicable case type, law and regulation provisions and detailed contents; and formatting and digitally processing the case data sheet, wherein the specific format comprises case basic information, law and regulation basis, amount of regulation basis, processing flow, processing document, investigation and evidence obtaining information, investigation inquiry information, document and evidence information, on-site investigation information and keyword information.
Preferably, the step S2 includes: and performing natural language semantic analysis processing and manual determination on the digitized case data by adopting a natural language analysis processing algorithm and combining with the industrial characteristics to obtain the characteristic words of each case data and sort according to the occurrence frequency.
Preferably, the step S2 includes: according to the applicable conditions of laws and regulations and the characteristic word data in the cases, an artificial neural network algorithm for correlation deep learning between the laws and regulations and administrative law enforcement cases is realized; and setting cases in the case base to form a training base, and training and learning the applicability of the legal rules to the cases to form a legal rule adaptive case base.
Preferably, the step S3 includes: and verifying the case library adapted by laws and regulations by inputting words of cases for other cases in the case library, and if the output result is consistent with or highly similar to the conclusion in the law enforcement case, indicating that the deep learning algorithm is correctly applied.
Preferably, the adaptive auxiliary system for the administrative law enforcement is installed on a mobile law enforcement instrument, and is used for law enforcement personnel to carry auxiliary supports for realizing the mobile law enforcement.
Preferably, the adaptive auxiliary system for administrative law enforcement provides case patrol management and case processing functions.
The administrative law enforcement self-adaptive auxiliary system can provide guidance for each law enforcement flow link and guide law enforcement personnel to complete each law enforcement flow link step by step according to the standard flow, thereby realizing the standardization, programming and refinement of the administrative law enforcement case processing.
The features and advantages of the present invention will become apparent by reference to the following drawings and detailed description of specific embodiments of the invention.
Drawings
FIG. 1 is a flow chart of an implementation method of an adaptive auxiliary system for law enforcement according to a first embodiment of the present invention;
FIG. 2 is a flow chart of a method for implementing the adaptive assistance system for law enforcement according to the second embodiment of the present invention;
fig. 3 is a flowchart of an application of the adaptive assistance system for law enforcement according to the third embodiment of the present invention.
Detailed Description
In order to make the technical solution of the present invention clearer and more clear, the following detailed description is made with reference to the accompanying drawings, and it should be understood that the specific embodiments described herein are only for explaining the present invention and are not intended to limit the present invention. It is to be noted that the features of the embodiments of the present invention can be combined with each other to form a new technical solution without contradiction.
Example one
Fig. 1 is a flowchart of an implementation method of an adaptive assistance system for law enforcement according to a first embodiment of the present invention. As shown in fig. 1, the present invention provides an implementation method of an artificial intelligence-based adaptive auxiliary system for administrative law enforcement, which includes the following steps:
s1: establishing a law and regulation database and a digital case database;
in the step, the established database comprises a law and regulation database and a digital case database, and when the law and regulation database is established, text files such as various laws and regulations and the like are digitized, normalized and formatted in a database mode to form the law and regulation database.
When a digital case database is established, natural language analysis processing algorithm is adopted and industry characteristics are combined, the digital laws and regulations are subjected to natural language semantic analysis processing and manual determination, and the characteristic words of each laws and regulations are obtained and are ordered according to the occurrence frequency; and forming a digital case database for various information, applicable laws and regulations and terms thereof, legal documents, processing flows, cutting standards and the like in cases in actual administrative law enforcement by referring to the digitalized rules of the laws and regulations.
The method adopts a natural language processing algorithm, and the algorithm steps for extracting the characteristic words (key words) are as follows:
1) and extracting words. Performing vocabulary segmentation on an input text by adopting a dictionary lookup segmentation algorithm and a probability statistics segmentation algorithm of a trigeminal Trie, performing full segmentation on a text sentence according to a basic word bank to generate an adjacent chain table type word diagram, and generating optimal segmentation words by using a dynamic programming algorithm on the basis of the word diagram to further generate a full segmentation word diagram;
2) the weight calculation ordering of the single word. In order to adjust parameters used in the calculation process, a keyword extraction training library can be established, wherein the training library comprises training files and corresponding keyword files, the weight of each candidate keyword is calculated, namely the product of the word frequency and the total times of the words appearing in the document is calculated, then the weight is defined according to the position, the part-of-speech information (the word at the end of a noun or a noun), whether the words appear in a title, whether the words in punctuation marks exist and the like, then the words and the corresponding weights thereof are calculated one by one, and then the words are sorted according to the size of word-taking calculation data;
3) the words are calculated to have a high proportion or a high rank in the above conditions, and are considered as keywords, and the keywords are stored in a keyword database.
The database comprises a case type table, a law and regulation table, a measurement reference table, a case example table, a case measurement guide table, a case processing information table and a case processing keyword table.
The process of digitizing, standardizing and formatting text files of various laws and regulations and the like in a database mode comprises the following steps: formatting and digitalizing the law and regulation text to form a law and regulation data table, wherein the specific format comprises basic information of the law and regulation, an application range, an upper law basis, an application case type, law and regulation provisions and detailed contents.
And formatting and digitally processing the case data sheet, wherein the specific format comprises case basic information, law and regulation basis, amount of regulation basis, processing flow, processing document, investigation and evidence obtaining information, investigation inquiry information, document and evidence information, on-site investigation information and keyword information.
S2: the method comprises the following steps of utilizing an artificial neural network algorithm to realize the associated deep learning between laws and regulations and administrative law enforcement cases, training and learning the applicability of the laws and regulations and the cases, and forming a law and regulation adaptive case library;
in the step, natural language analysis processing algorithm is adopted and industry characteristics are combined, natural language semantic analysis processing and manual determination are carried out on the digitized case data, and the feature words of each case data are obtained and are sequenced according to the occurrence frequency.
The step of extracting the feature words (keywords) by using a natural language processing algorithm is the same as that in step S1, and is not described herein again.
In the step, an artificial neural network algorithm for associated deep learning between law and law enforcement cases is realized according to the applicable conditions of the law and the law in the cases and the characteristic word data; and setting cases in the case base to form a training base, and training and learning the applicability of the legal rules to the cases to form a legal rule adaptive case base.
In this step, the deep learning based on the artificial neural network algorithm comprises the following steps:
1) setting a random number which defines a certain range to initialize the weight of the neural network;
2) reading in a training case set, wherein the training case set is a set formed by a plurality of case information data recording neural network input relations;
3) taking out a piece of data from the training case set, calculating an output value of the neural network by using the data, calculating the output value of the neural network, comparing the output value with the output of the training case set to obtain an error of the neural network, and then adjusting the weight by using the error to perform a back propagation algorithm of the neural network, wherein the adjustment relates to a plurality of levels, namely the weight of an output layer, the weight of a middle layer and the like, until the data in the training case data set is calculated again by using the adjusted weight to obtain the output consistent with the training case data set, and then the weight calculation is finished;
4) outputting the weight after deep learning and the corresponding neural network output based on the training case data set;
5) the weights of the outputs and their corresponding neural networks based on the learning data sets are used to substitute new administrative enforcement cases to obtain the desired outputs.
S3: verifying whether the deep learning algorithm is correct by verifying that the laws and regulations are applicable to a case base;
and verifying the legal and legal regulation adaptive case library by inputting words of cases, namely keywords/characteristic words, in other cases in the case library, and if the output result is consistent with or highly similar to the conclusion in the law enforcement case, indicating that the deep learning algorithm is correctly applied.
Through keyword extraction, a plurality of words or phrases representing the central thought of the article can be extracted from information data in a single or a plurality of laws and regulations and case databases, so that keywords are formed and can be used for semantic query, quick matching and the like.
S4: and forming an artificial intelligence-based administrative law enforcement adaptive auxiliary system, and applying the system to actual administrative law enforcement.
The legal and legal regulation case library is applied to actual administrative law enforcement, and possible attributes of the case, possibly applicable legal and legal regulations and corresponding terms, cutting standards and the like can be quickly found in the artificial intelligent legal and legal regulation library by inputting simple information of the case.
The system and the database formed according to the steps can be docked with other administrative law enforcement systems to carry out artificial intelligence law and regulation self-adaption auxiliary administrative law enforcement in various fields.
Furthermore, the administrative law enforcement self-adaptive auxiliary system utilizes the administrative law enforcement case library and law enforcement data generated in the law enforcement process to carry out deep learning of an artificial neural network algorithm, so as to form the administrative law enforcement case library with artificial intelligence.
Preferably, the adaptive auxiliary system for the administrative law enforcement is installed on a mobile law enforcement instrument, and is used for law enforcement personnel to carry auxiliary supports for realizing the mobile law enforcement.
Preferably, the system of the invention provides case patrol management and case processing functions, can provide auxiliary support for law and regulation and past cases in field law enforcement for law enforcement personnel in actual law enforcement patrol and case processing, and improves patrol and case processing efficiency and accuracy.
The administrative law enforcement self-adaptive auxiliary system based on artificial intelligence has the following functions: legal and legal help management, data modeling management, legal and legal management, case information management and case deep learning management.
Example two
Fig. 2 is a flowchart of an implementation method of the adaptive assistance system for law enforcement according to the second embodiment of the present invention. As shown in fig. 2, the present invention provides a flow chart of an artificial intelligence-based adaptive auxiliary system for administrative law enforcement, which forms a processing flow by algorithms and is embodied in a software system to complete the administrative law enforcement system, and assists workers in assisting in processing in administrative law enforcement, and the adaptive auxiliary method includes:
s101, digitalizing, standardizing and formatting process of laws and regulations
Carrying out digitalization, standardization and formatting treatment on text files such as various laws and regulations in a database mode to form a database of laws and regulations;
s102, natural language processing of laws and regulations
Adopting a natural language analysis processing algorithm and combining with industrial characteristics to carry out natural language semantic analysis processing and manual determination on the digitized laws and regulations, obtaining characteristic words of each laws and regulations and sequencing according to the occurrence frequency;
s103, establishing a digital case database
Forming a digital case database for various information, applicable laws and regulations and terms thereof, legal documents, processing flows, cutting standards and the like in cases in actual administrative law enforcement by referring to a law and regulation digitization method;
s104, natural language processing of digital case database
Adopting a natural language analysis processing algorithm and combining with industrial characteristics to carry out natural language semantic analysis processing and manual determination on the digitized case data to obtain the characteristic words of each case data and sort according to the occurrence frequency;
s105, deep learning algorithm of law and regulation case library
According to the applicable conditions of laws and regulations and the characteristic word data in the cases, an artificial neural network algorithm for correlation deep learning between the laws and regulations and administrative law enforcement cases is realized;
s106, training and learning of case database by laws and regulations
Setting cases in the case base to form a training base, and training and learning the applicability of the legal rules to the cases according to the algorithm in the step five to form a legal rule adaptation case base;
s107, verifying the case base adapted to laws and regulations
Verifying the law and regulation adaptive case library for a plurality of words of the inputted cases by other cases in the case library, and if the output of the case and the conclusion in the law enforcement case are consistent or close to each other in height, indicating that the deep learning algorithm is correctly applicable;
s108, law and regulation case library application
The legal and legal case library is applied to actual administrative law enforcement, and possible attributes of the case, possibly applicable laws and regulations, corresponding terms, cutting standards and the like can be quickly found in the artificial intelligent legal and legal case library by inputting simple information of the case;
s109, realizing of interface of legal case database and application system
The system and the database formed according to the steps can be butted with other administrative law enforcement systems to form artificial intelligence law and regulation self-adaption auxiliary administrative law enforcement in various fields.
In this embodiment, a natural language processing algorithm is adopted, the step of extracting keywords, and the step of deep learning based on an artificial neural network algorithm are the same as those in the first embodiment, and are not described herein again.
EXAMPLE III
Fig. 3 is a flowchart of an application of the adaptive assistance system for law enforcement according to the third embodiment of the present invention.
In order to apply the system to administrative law enforcement and provide auxiliary support for administrative law enforcement, the adaptive auxiliary system for administrative law enforcement of the present invention provides case patrol management and case processing functions, and in this embodiment, when case processing is performed by using the adaptive auxiliary system for administrative law enforcement, a conventional case processing procedure is followed, which may specifically refer to the procedure shown in fig. 3, and details are not described in this embodiment.
The embodiment realizes that the auxiliary support of laws and regulations and past cases in the field law enforcement is provided for law enforcement personnel in the actual process of law enforcement patrol and case treatment, and the efficiency and the accuracy of patrol and case treatment are improved.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the contents of the present specification and the accompanying drawings, or directly/indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. An implementation method of an administrative law enforcement adaptive auxiliary system based on artificial intelligence is characterized by comprising the following steps:
s1: establishing a law and regulation database and a digital case database;
s2: the method comprises the following steps of utilizing an artificial neural network algorithm to realize the associated deep learning between laws and regulations and administrative law enforcement cases, training and learning the applicability of the laws and regulations and the cases, and forming a law and regulation adaptive case library;
s3: verifying whether the deep learning algorithm is correct by verifying that the laws and regulations are applicable to a case base;
s4: and forming an artificial intelligence-based administrative law enforcement adaptive auxiliary system, and applying the system to actual administrative law enforcement.
2. The method according to claim 1, wherein the step S1 includes: the text files such as various laws and regulations are digitalized, normalized and formatted in a database mode to form a database of laws and regulations.
3. The method according to claim 2, wherein the step S1 includes: adopting a natural language analysis processing algorithm and combining with industrial characteristics to carry out natural language semantic analysis processing and manual determination on the digitized laws and regulations, obtaining characteristic words of each laws and regulations and sequencing according to the occurrence frequency; and forming a digital case database for various information, applicable laws and regulations and terms thereof, legal documents, processing flows, cutting standards and the like in cases in actual administrative law enforcement by referring to the digitalized rules of the laws and regulations.
4. The method according to any one of claims 1 to 3, wherein the database includes a case type table, a law and regulation table, a cutting reference table, a case example table, a case cutting guide table, a case processing information table, and a case processing keyword table.
5. The method of claim 2, wherein the step of digitizing, normalizing and formatting the text files of various legal regulations in a database comprises: formatting and digitally processing the law and regulation text to form a law and regulation data table, wherein the specific format comprises basic information of the law and regulation, an application range, an upper law basis, an applicable case type, law and regulation provisions and detailed contents; and formatting and digitally processing the case data sheet, wherein the specific format comprises case basic information, law and regulation basis, amount of regulation basis, processing flow, processing document, investigation and evidence obtaining information, investigation inquiry information, document and evidence information, on-site investigation information and keyword information.
6. The method according to claim 1, wherein the step S2 includes: and performing natural language semantic analysis processing and manual determination on the digitized case data by adopting a natural language analysis processing algorithm and combining with the industrial characteristics to obtain the characteristic words of each case data and sort according to the occurrence frequency.
7. The method according to claim 6, wherein the step S2 includes: according to the applicable conditions of laws and regulations and the characteristic word data in the cases, an artificial neural network algorithm for correlation deep learning between the laws and regulations and administrative law enforcement cases is realized; and setting cases in the case base to form a training base, and training and learning the applicability of the legal rules to the cases to form a legal rule adaptive case base.
8. The method according to claim 1, wherein the step S3 includes: and verifying the case library adapted by laws and regulations by inputting words of cases for other cases in the case library, and if the output result is consistent with or highly similar to the conclusion in the law enforcement case, indicating that the deep learning algorithm is correctly applied.
9. The method according to claim 1, characterized in that said adaptive auxiliary system for law enforcement on administration is installed on a mobile law enforcement instrument, for law enforcement personnel to carry auxiliary supports for implementing mobile law enforcement.
10. The method according to claim 1, wherein said administrative law enforcement adaptive assistance system provides case patrol management and case handling functions.
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Application publication date: 20210223 |