CN113204567A - Big data judicial case analysis and processing system - Google Patents
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Abstract
The invention provides a big data judicial case analysis processing system, which comprises a data entry subsystem, a data indexing subsystem, a data classification subsystem, a data query subsystem, a data comparison subsystem, a data recommendation subsystem and a data output subsystem, wherein the data entry subsystem is used for storing data; the data entry subsystem enters judicial case data; the data indexing subsystem performs index analysis on the judicial case data; the data classification subsystem establishes a mapping relation between the judicial case data and a plurality of classification index databases; the data query subsystem receives query data input by a user; the data comparison subsystem compares a classification index database through a mapping relation; the data recommendation subsystem recommends target judicial case data based on the query data and the compared classified index database; and the data output subsystem outputs target judicial case data through a human-computer interaction interface. The technical scheme of the invention utilizes judicial big data to realize effective case analysis and avoid the condition of law bar failure.
Description
Technical Field
The invention belongs to the technical field of big data analysis, and particularly relates to a big data judicial case analysis processing system.
Background
In recent years, in order to promote the reform of judicial system, China successively provides systems such as official document disclosure, court trial information disclosure, execution disclosure and the like, a large amount of judicial data is stored to provide powerful data support for the construction of big data, and the construction of an intelligent court and an intelligent inspection service and the development of AI technology create good external environment for the development of the big data of the judicial system. At present, all countries in the world are actively carrying out courtroom intelligent reform, and deeply exploring the trial mode of 'internet + big data', such as 'Cyber Coort' in the United states and 'Online Cort' in the United kingdom, so as to realize automatic case classification. Also "just On Line" in Singapore, "E-court system" in Australia, and the like.
In 2010, the highest people court is discharged from the regulations on case guidance work, which marks the establishment of the case guidance system in China; since 2014, according to the regulations of the highest people's court on the publishing of official documents on the internet by people's court, the highest people's court establishes an official document network and uniformly publishes the effective official documents of various levels of people's court. Compared with judicial explanation, the application condition of the guiding case is more targeted, the law loopholes can be filled, and more specific rules can be created and applied to specific cases.
The Chinese patent application with the application number of CN202010273409.6 provides a method and a device for evaluating the reasonability of administrative punishment discretion based on big data, and the method comprises the steps of obtaining basic data; and performing characteristic extraction on the basic data, determining case law of the case according to the extracted characteristic information, determining a penalty amount range according to the case law, judging whether the penalty amount of the case is in the penalty amount range, constructing a penalty amount rationality evaluation model after judging that the penalty amount of the case is in the penalty amount range, and judging the rationality of the penalty amount of the case according to the penalty amount rationality evaluation model. The invention establishes the rationality evaluation method and the rationality evaluation device for the discretionary right, can assist law enforcement personnel to accurately exercise the administrative punishment discretionary right and scientifically enforce law enforcement, and provides a scientific and efficient solution for standardizing the application of the administrative punishment discretionary right and solving the problem of abusing the discretionary right in the administrative law enforcement.
However, when the current big data is applied to judicial case analysis, the purpose is to realize "case matching judgment", so the prior art mostly focuses on case retrieval, similarity comparison and the like. However, the inventor finds that in practical use (for example, search through a referee's paper web), since laws are constantly changing with the development of society, decisions need to be made based on current cases and current effective laws. If only case-based similarity retrieval is performed without considering the evolution of laws over time, the obtained recommendation result or similar cases are not applicable at all. For example, in 2016, China, 4 months, modified the crime related standards published "two high" 2000 years ago from a single "amount" to "amount + plot" according to the actual economic development level, and increased the amount accordingly. The situation of 'large amount' specified in the third eighty-six rules of criminal law is modified from the original specification of 'five thousand yuan to five ten thousand yuan' into 'thirty thousand yuan to twenty thousand yuan'. The situation of 'huge amount' is modified from the original regulation of 'five ten thousand yuan to ten thousand yuan' into 'twenty thousand yuan to three million yuan'; the condition of 'extremely large amount' is modified from the original regulation of 'more than one hundred thousand yuan' into 'more than three million yuan'. Therefore, the crime data committed 5 months ago in 2016 may have been "stale" and not be a reference for big data system decision making.
In view of the above technical problems, the prior art has not proposed an effective technical solution.
Disclosure of Invention
In order to solve the technical problems, the invention provides a big data judicial case analysis processing system, which comprises a data entry subsystem, a data indexing subsystem, a data classification subsystem, a data query subsystem, a data comparison subsystem, a data recommendation subsystem and a data output subsystem; the data entry subsystem enters judicial case data; the data indexing subsystem performs index analysis on the judicial case data; the data classification subsystem establishes a mapping relation between the judicial case data and a plurality of classification index databases; the data query subsystem receives query data input by a user; the data comparison subsystem compares a classification index database through a mapping relation; the data recommendation subsystem recommends target judicial case data based on the query data and the compared classified index database; and the data output subsystem outputs target judicial case data through a human-computer interaction interface.
In terms of specific implementation, the specific functions of each subsystem in the technical scheme of the invention are as follows:
the data entry subsystem is used for entering judicial case data, and the judicial case data comprises a decision document;
the data indexing subsystem is used for performing index analysis on the judicial case data to generate a plurality of case indexes;
the data classification subsystem establishes a mapping relation between the judicial case data and a plurality of classification index databases based on the case indexes;
the data query subsystem is used for receiving query data input by a user, wherein the query data comprise a plurality of keywords, and the keywords are associated with the case index;
the data comparison subsystem compares at least one classified index database through the mapping relation based on case indexes associated with the query data;
the data recommendation subsystem recommends at least one target judicial case data based on the query data and the compared at least one classified index database;
and the data output subsystem outputs the at least one target judicial case data through a human-computer interaction interface.
More specifically, the case indexes include a time index, a crime index and a law enforcement index.
The data classification subsystem comprises a plurality of classification index databases and case collection databases;
and each classified index database stores different case indexes and storage positions of collected cases corresponding to the case indexes in the case collection database.
The data query subsystem is used for receiving query data input by a user, and the query data comprises a combination of a time keyword and one of the following keywords: the keyword of the name of a crime and the keyword of a law bar.
The data comparison subsystem compares a plurality of classified index databases through the mapping relation based on case indexes associated with the query data;
and the data recommendation subsystem executes data intersection operation on the plurality of compared classified index databases based on the query data and recommends at least one target judicial case data.
It is worth pointing out that, in the present invention, the data entry subsystem directly enters the judicial case data without performing document structure analysis or splitting operations.
The technical scheme of the invention utilizes judicial big data to realize effective case analysis and avoid the condition of law bar failure.
Specifically, when case data are input, timeliness of judicial case data is identified through time indexes contained in case indexes, and classified storage of criminal names and law bar indexes is performed on the basis of timeliness; when a case is queried, time element keywords are considered at first, and then data intersection operation is performed based on other keywords, so that the output recommended result case is ensured to be a case which is matched with the current query case and has an effective rule, and the condition that the rule is invalid is avoided; meanwhile, in the technical scheme of the invention, different from the method of executing document structure analysis in the prior art, the method of directly inputting and directly traversing the judicial case data does not execute document structure analysis or splitting operation, and does not need element analysis.
Further advantages of the invention will be apparent in the detailed description section in conjunction with the drawings attached hereto.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a block diagram of a big data judicial case analysis processing system according to an embodiment of the present invention
FIG. 2 is a data control flow diagram of the system of FIG. 1 for logging data and querying data
FIG. 3 is a schematic view of the process of entering official documents by the system of FIG. 1
FIG. 4 is a schematic flow chart illustrating a process for receiving user query input by the system of FIG. 1
Detailed Description
The invention is further described with reference to the following drawings and detailed description.
Referring to fig. 1, a subsystem structure diagram of a big data judicial case analysis processing system according to an embodiment of the present invention is shown.
In fig. 1, the big data judicial case analysis processing system is composed of a data entry subsystem, a data indexing subsystem, a data classification subsystem, a data query subsystem, a data comparison subsystem, a data recommendation subsystem, and a data output subsystem.
In the following, with reference to fig. 2, the functional implementation of each of the different subsystems is specifically described.
The data entry subsystem is used for entering judicial case data, and the judicial case data comprises a decision document.
Preferably, in this embodiment, the judicial case data entered by the data entry subsystem includes a plurality of different decision documents of the same judicial case, including validated decision documents and non-validated decision documents.
It is worth noting that in the prior art, the existing big data judicial database is not complete, and the data has the problems of missing accuracy, repeated occurrence and the like.
Taking the existing official document network mechanism as an example, the published document can not disclose the first opinion judgment document but disclose the cases which reject the second opinion and maintain the original judgment, and the other cases which are revised in the second opinion judgment can not disclose the first opinion judgment document and can not really realize the complete disclosure of the officials. In addition, the published documents have the problems of repeated uploading, wrong transmission and the like, and particularly, the errors affect larger words such as 'power' and 'right', 'legal' and 'legal'. The data base has problems in integrity, accuracy and uniqueness.
In order to solve the above problem, in this embodiment, if an effective decision document is entered for the same judicial case, a part of the previously entered non-effective decision document having the same content as the effective decision document is deleted.
As a further improvement, the interference of human factors on data collection is reduced as much as possible in the data acquisition process, the authenticity of data collection is ensured, and errors in the initial stage are avoided.
Next, referring to fig. 3, the data indexing subsystem performs index analysis on the judicial case data, specifically including:
traversing the judgment document according to preset index words to obtain a plurality of case indexes of the judgment document, wherein the case indexes comprise time indexes, criminal name indexes and law bar indexes.
Different from the prior art, when the judicial case data is input, the method directly inputs and directly executes traversal without processes such as additional structural analysis or document element splitting. This is because the present invention subsequently directly collects the judicial case data itself, records the actual mapping relationship thereof and saves the mapping location.
Specifically, in fig. 1, the data classification subsystem includes a plurality of classification index databases and case collection databases;
and each classified index database stores different case indexes and storage positions of collected cases corresponding to the case indexes in the case collection database.
The data classification subsystem establishes a mapping relation between the judicial case data and a plurality of classification index databases based on the case indexes, and then stores the judicial case data to a designated position in the case collection database, wherein the designated position is determined by the mapping relation.
Referring next to FIG. 4, the data query subsystem is configured to receive user-entered query data including a combination of a temporal keyword and one of: the keyword of the name of a crime and the keyword of a law bar.
The data comparison subsystem compares a plurality of classified index databases through the mapping relation based on case indexes associated with the query data;
the compared classification index databases comprise a combination of a time classification index database and the following classification index databases: a guilty name classification index database and a French classification index database.
The data comparison subsystem compares a plurality of classified index databases through the mapping relation based on case indexes associated with the query data;
and the data recommendation subsystem executes data intersection operation on the plurality of compared classified index databases based on the query data and recommends at least one target judicial case data.
Preferably, the performing a data intersection operation on the compared multiple classification index databases based on the query data may be represented as follows:
wherein the content of the first and second substances,
wherein:
n is the number of the compared multiple classification index databases; di is the ith classification index database, U is a union operation symbol, n is an intersection operation symbol, J is the data intersection operation result, | | is the number of elements contained in the set, and lambdaiThe weights are controlled for the element proportions.
And C is the classification index database of which the matching degree with the query data is greater than a preset threshold value in the compared classification index databases.
It is noted that, in the above embodiments, the data output subsystem displays the target judicial case data on the human-computer interaction interface and highlights a portion of the target judicial case data associated with the query data.
Obviously, the technical scheme of the invention starts from two aspects and improves the prior art.
In the aspect of data entry, a direct entry and direct traversal analysis mode is adopted, so that structural analysis or element analysis of the document is avoided, the document is directly entered and stored, and the integrity of data is kept; meanwhile, corresponding mapping analysis is executed based on the time element as a reference, so that the legality timeliness of the data in subsequent use is ensured;
in the aspect of data query, time element keywords are considered at first, and then data intersection operation is performed based on other keywords, so that the output recommended result case is the case which is matched with the current query case and has valid legal provisions, and the condition that the legal provisions are invalid is avoided.
Practices prove that the technical scheme of the invention provides a roughly uniform judgment scale for different courts examining similar cases through informatization resource sharing, and avoids the problem that different judgments and laws of the same case are not uniformly applicable. In specific practice, on the basis of the invention, a case weight coefficient and evaluation index system can be established by utilizing big data, the workload of a judge is determined, and scientific member quota allocation and case shunting are carried out. The mining of data investigation clues can be deepened by utilizing judicial big data in the aspect of criminal investigation, early warning and initial investigation of case-like criminal investigation are realized, the investigation function is exerted by utilizing artificial intelligence, and the value of data is mined by an intelligent means.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. A big data judicial case analysis processing system comprises a data entry subsystem, a data indexing subsystem, a data classification subsystem, a data query subsystem, a data comparison subsystem, a data recommendation subsystem and a data output subsystem;
the method is characterized in that:
the data entry subsystem is used for entering judicial case data, and the judicial case data comprises a decision document;
the data indexing subsystem is used for performing index analysis on the judicial case data to generate a plurality of case indexes;
the data classification subsystem establishes a mapping relation between the judicial case data and a plurality of classification index databases based on the case indexes;
the data query subsystem is used for receiving query data input by a user, wherein the query data comprise a plurality of keywords, and the keywords are associated with the case index;
the data comparison subsystem compares at least one classified index database through the mapping relation based on case indexes associated with the query data;
the data recommendation subsystem recommends at least one target judicial case data based on the query data and the compared at least one classified index database;
and the data output subsystem outputs the at least one target judicial case data through a human-computer interaction interface.
2. The big data judicial case analysis processing system of claim 1, wherein:
the judicial case data entered by the data entry subsystem comprises a plurality of different decision documents of the same judicial case, wherein the different decision documents comprise effective decision documents and non-effective decision documents;
if the effective judgment documents are input aiming at the same judicial case, deleting the parts, which have the same content with the effective judgment documents, in the previously input non-effective judgment documents.
3. The big data judicial case analysis processing system of claim 1, wherein: the data indexing subsystem performs index analysis on the judicial case data, and specifically comprises the following steps:
traversing the judgment document according to preset index words to obtain a plurality of case indexes of the judgment document, wherein the case indexes comprise time indexes, criminal name indexes and law bar indexes.
4. A big data judicial case analysis processing system according to claim 1 or 3, wherein:
the data classification subsystem comprises a plurality of classification index databases and case collection databases;
and each classified index database stores different case indexes and storage positions of collected cases corresponding to the case indexes in the case collection database.
5. The big data judicial case analysis processing system of claim 4, wherein:
and the data classification subsystem establishes a mapping relation between the judicial case data and a plurality of classification index databases based on the case indexes, and then stores the judicial case data to a specified position in the case collection database, wherein the specified position is determined by the mapping relation.
6. The big data judicial case analysis processing system of any one of claims 1-3 or 5, wherein:
the data query subsystem is used for receiving query data input by a user, and the query data comprises a combination of a time keyword and one of the following keywords: the keyword of the name of a crime and the keyword of a law bar.
7. The big data judicial case analysis processing system of claim 6, wherein:
the data comparison subsystem compares a plurality of classified index databases through the mapping relation based on case indexes associated with the query data;
the compared classification index databases comprise a combination of a time classification index database and the following classification index databases: a guilty name classification index database and a French classification index database.
8. The big data judicial case analysis processing system of claim 6, wherein:
the data comparison subsystem compares a plurality of classified index databases through the mapping relation based on case indexes associated with the query data;
and the data recommendation subsystem executes data intersection operation on the plurality of compared classified index databases based on the query data and recommends at least one target judicial case data.
9. The big data judicial case analysis processing system of claim 1 or 8, wherein:
and the data output subsystem displays the target judicial case data on the human-computer interaction interface and highlights a part, associated with the query data, of the target judicial case data.
10. A big data judicial case analysis and processing system according to any one of claims 1 to 3, wherein:
and the data entry subsystem directly enters the judicial case data without executing document structure analysis or splitting operation.
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| CN114461760A (en) * | 2022-02-10 | 2022-05-10 | 北京华宇元典信息服务有限公司 | Method and device for matching case fact with law bar |
| CN117473074A (en) * | 2023-11-01 | 2024-01-30 | 中国通信建设集团有限公司数智科创分公司 | Judicial case intelligent information matching system and method based on artificial intelligence |
| CN117610990A (en) * | 2023-11-13 | 2024-02-27 | 中国通信建设集团有限公司数智科创分公司 | Intelligent judicial case quality evaluation system and method based on big data |
| CN117610990B (en) * | 2023-11-13 | 2024-06-28 | 中国通信建设集团有限公司数智科创分公司 | Intelligent judicial case quality evaluation system and method based on big data |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114461760A (en) * | 2022-02-10 | 2022-05-10 | 北京华宇元典信息服务有限公司 | Method and device for matching case fact with law bar |
| CN117473074A (en) * | 2023-11-01 | 2024-01-30 | 中国通信建设集团有限公司数智科创分公司 | Judicial case intelligent information matching system and method based on artificial intelligence |
| CN117610990A (en) * | 2023-11-13 | 2024-02-27 | 中国通信建设集团有限公司数智科创分公司 | Intelligent judicial case quality evaluation system and method based on big data |
| CN117610990B (en) * | 2023-11-13 | 2024-06-28 | 中国通信建设集团有限公司数智科创分公司 | Intelligent judicial case quality evaluation system and method based on big data |
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