CN117332772A - Legal case applicable treaty analysis matching system based on mobile internet - Google Patents
Legal case applicable treaty analysis matching system based on mobile internet Download PDFInfo
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- CN117332772A CN117332772A CN202311191286.1A CN202311191286A CN117332772A CN 117332772 A CN117332772 A CN 117332772A CN 202311191286 A CN202311191286 A CN 202311191286A CN 117332772 A CN117332772 A CN 117332772A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/205—Parsing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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- 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/18—Legal services; Handling legal documents
Abstract
The invention relates to the technical field of legal cases, and particularly discloses a legal case applicable condition analysis and matching system based on a mobile internet, which comprises the following steps: the system comprises a case input module, a case processing module, a history lease case related information acquisition module, a history lease case evaluation module, a history lease case screening module, a legal provision ordering analysis module, a recommended legal provision analysis module and a cloud database, wherein the similarity of a case currently submitted by a target person and the history lease case is analyzed in the history lease case evaluation module, the analysis comprises analysis of lease time, lease total amount, payment mode and evidence audio/video, and analysis of identity state and identity id of the target person, so that the problem of low suitability of the recommended legal provision is solved, the processing progress of the house lease case is ensured to a certain extent, and more accurate service is provided for related processing personnel.
Description
Technical Field
The invention relates to the technical field of legal case electronic data analysis, in particular to a legal case applicable treaty analysis and matching system based on the mobile internet.
Background
Along with development of science and technology and internet, part of legal cases can be used for searching proper legal regulations by software or small programs, and in legal cases, the number base of house leasing cases is large, so that analysis of applicable legal regulations of house leasing cases is extremely important for improving the working efficiency of the house leasing cases, for example, the analysis result of applicable legal regulations of the house leasing cases is inaccurate, on one hand, the processing progress of the house leasing cases is affected, the tracking time of relevant personnel of the cases is prolonged to a certain extent, on the other hand, the image of relevant management personnel is affected, and therefore, the analysis of applicable legal regulations of the house leasing cases is very necessary.
The prior art is not high in suitability for analysis of applicable legal provision of house renting cases, and is specifically embodied in:
(1) In the prior art, when the similarity analysis of the case currently submitted by the target person and the historical lease case is performed, the similarity of lease contracts is often relied on for analysis, the analysis strength of evidence audio and video, the identity state and the identity id of the target person is insufficient, the analysis level is insufficient for multiple, and the accuracy of the similarity analysis result of the case currently submitted by the target person and the historical lease case is further reduced, so that the powerful data support is difficult to be provided for the analysis of the follow-up recommended legal provision to a certain extent.
(2) In the prior art, analysis on the application times of historical legal provision is lacking, the application times of the historical legal provision reflect the suitability of the legal provision, the more the application times of the legal provision are, the wide application range of the legal provision is indicated, the suitability of the recommended legal provision for analysis is not high due to the neglect of the aspect of the prior art, the phenomenon that the reference value of the recommended legal provision for analysis is not high possibly exists, the processing progress of house lease cases is affected, more accurate service cannot be provided for related processing personnel, and the processing difficulty of the related processing personnel is further increased.
Disclosure of Invention
In order to overcome the defects in the background technology, the invention provides a legal case applicable provision analysis and matching system based on the mobile Internet, which is used for solving the problem of low suitability of recommended legal provision.
The invention adopts the following technical scheme: a legal case applicable treaty analysis matching system based on the mobile internet, comprising:
the case input module is used for inputting a lease contract, inputting evidence information and inputting case related description voice by a target user;
the case processing module is used for acquiring case characteristic information based on a lease contract input by a target user and converting case related description voice input by the target user into case related description text corresponding to the target user;
the cloud database is used for storing lease contracts, evidence information and case related description voices corresponding to each historical lease case, storing identity states of the applicant belonging to each historical lease case and storing case characteristic information corresponding to the lease contract belonging to each historical lease case;
the historical lease case related information acquisition module is used for extracting lease contracts corresponding to each historical lease case from the cloud database, acquiring case characteristic information corresponding to each lease case, and further acquiring evidence information corresponding to each historical lease case and case related description voice from the cloud database;
the historical lease case evaluation module is used for comprehensively analyzing evaluation coefficients corresponding to each historical lease case;
the historical lease case screening module is used for screening each adaptive historical lease case corresponding to the target user according to the evaluation coefficient corresponding to each historical lease case;
the legal provision ordering analysis module is used for extracting each practical application legal provision corresponding to each history leasing case from the cloud database, and analyzing a basic ordering value corresponding to each practical application legal provision according to the practical application legal provision;
and the recommended legal provision analysis module is used for analyzing each recommended legal provision corresponding to the target user according to the adaptive historical leasing case corresponding to the target user and the basic ranking value corresponding to each actual application legal provision, and sending the recommended legal provision to related processing personnel.
The case characteristic information comprises a lease start time point, a lease end time point, a lease total amount and a payment mode.
Evidence information, comprising: each evidence picture, each evidence audio and each evidence video.
Specifically, the analysis method for the evaluation coefficients corresponding to each history lease case comprises the following substeps:
s1.1, acquiring the identity state of a target person, acquiring the identity state of the applicant belonging to each historical lease case from a cloud database, and analyzing that the identity of the target person and the applicant belonging to each historical lease case accords with an index epsilon i I represents the number of each history rental case, i=1, 2, n;
s1.2, acquiring the identity id of a target person, acquiring the identity id of a lessor and the identity id of a lessee to which each history leasing case belongs from cloud data, and analyzing the matching coefficient eta of the identity id of the target person and the identity id of an associated person to which the history leasing case belongs i ；
S1.3, analyzing evaluation coefficients corresponding to each historical lease case, wherein the formula is as follows:
wherein mu i E is expressed as a natural constant for the evaluation coefficient of the i-th historical rental case;
expressed as similarity, sigma, of lease contract to which target user belongs and lease contract to which ith historical lease case belongs i An evaluation index indicating that the evidence information of the target user corresponds to the evidence information of the ith historical lease case,/I>The adaptation index corresponding to the case related description text of the target user and the case related description text of the i-th historical lease case is represented;
λ 1 、λ 2 、λ 3 、λ 4 、λ 5 respectively representing the influence weight factors corresponding to the preset identity state coincidence, identity id matching, lease contract similarity, evidence information evaluation and case related description text.
In step 1.3, the similarity between the lease contract to which the target user belongs and the lease contract to which each history lease case belongs, and the analysis method comprises the following sub-steps:
s2.1, extracting a lease start time point T from case feature information of a lease contract to which a target user belongs Starting up Rental end time T Terminal (A) The total leasing amount M and the payment mode;
s2.2, extracting lease starting time points T of lease contracts of each history lease case from a cloud database i ′ Starting up Rental end time T i ′ Terminal (A) Total leasing amount M' i And payment means;
s2.3, acquiring the lease duration SC of the lease contract to which the target user belongs according to the lease start time point and the lease end time point of the lease contract to which the target user belongs;
s2.4, obtaining lease duration SC of lease contracts of each history lease case by using the same method of the step S2.3 i ′；
S2.5, comparing the payment mode of the lease contract to which the target user belongs with the payment modes of lease cases to which each history lease case belongs, and analyzing the payment mode matching coefficient FJ of the target user corresponding to each history lease case i ；
S2.6, analyzing the similarity between the lease contract of the target user and the lease contract of each history lease case, wherein the formula is as follows:
wherein T' is represented as a preset allowable rental start time error, TG is represented as a preset allowable rental end time error, gamma 1 、γ 2 、γ 3 、γ 4 、γ 5 Respectively expressed as the similarity of preset lease starting time pointsThe corresponding duty factors of similar lease ending time points, lease total amount, payment mode matching and lease duration.
In step 1.3, the evaluation index corresponding to the evidence information of the target user and the evidence information of each historical lease case, the analysis method comprises the following sub-steps:
s3.1, extracting each evidence picture, each evidence audio and each evidence video from evidence information of a target user;
s3.2, acquiring each payment date R corresponding to the target user according to each evidence picture to which the target user belongs m Where m is denoted as the number of each payment date, m=1, 2, i;
s3.3, acquiring each date R 'corresponding to the target user according to the lease contract corresponding to the target user' m ；
S3.4, analyzing a payment date evaluation coefficient PL corresponding to the target user, wherein the formula is as follows:
wherein R' represents a preset allowable payment extension period;
s3.5, obtaining a payment date evaluation coefficient PL 'corresponding to each historical lease case by using the same method of the step S3.4' i ；
S3.6, analyzing a keyword set B corresponding to the target user according to each evidence audio and each evidence video corresponding to the target user;
s3.7, analyzing and obtaining a keyword set B 'corresponding to each history lease case by using the same method as the step S3.6' i ；
S3.8, analyzing the keyword similarity coefficient tau corresponding to each historical lease case of the target user i The formula is as follows:
s3.9, analyzing evaluation indexes corresponding to the evidence information of the target user and the evidence information of each historical lease case:
wherein χ is 1 、χ 2 Respectively representing the preset payment date evaluation coefficient and the weight coefficient corresponding to the keyword similarity.
In step 1.3, the adaptation index corresponding to the case related description text of the target user and the case related description text of each historical lease case is specifically analyzed by the method comprising: the analysis method of the keyword similarity coefficient corresponding to each historical lease case of the target user is consistent with that of the target user, and the adaptation index corresponding to the case related description of the target user and the case description text of each historical lease case is analyzed
Further, the specific analysis method of the basic ranking value corresponding to each practical application legal provision is as follows:
summarizing each practical application legal provision corresponding to each historical lease case to obtain the application times of each practical application legal provision;
and sequencing the practical application legal provision according to the sequence of the application times from high to low, and obtaining a basic sequencing value corresponding to the practical application legal provision.
Further, the analysis method for each recommended legal provision corresponding to the target user comprises the following steps:
acquiring each actual application legal provision corresponding to each adapting historical lease case according to each actual application legal provision corresponding to each historical lease case, and marking the actual application legal provision as each legal provision to be analyzed corresponding to each adapting historical lease case;
the analysis method is consistent with the analysis method of the basic ranking value corresponding to each practical application legal provision, and ranking value PA corresponding to each legal provision to be analyzed is obtained through analysis d Where d is the number of each legal provision to be analyzed, d=1, 2,..f;
acquiring a basic ranking value PA 'corresponding to each legal provision to be analyzed according to the basic ranking value corresponding to each actual application legal provision' d ；
Analyzing the recommended index TJ corresponding to each legal provision to be analyzed d The formula is as follows:
where f is expressed as the number of legal provisions to be analyzed, delta 1 、δ 2 The weight factor is represented as a preset sorting value and a weight factor corresponding to a basic sorting value;
and analyzing each recommended legal provision of the target user according to the recommended index corresponding to each legal provision to be analyzed.
Compared with the prior art, the technical scheme provided by the invention has the following technical effects:
(1) In the case input module, the target user inputs the related information and uploads the information to the processing center, so that basic data support is provided for subsequent case processing.
(2) According to the invention, the case characteristic information is extracted from the lease contract uploaded by the target user in the case processing module, and other related information is processed, so that a foundation is laid for the evaluation of the subsequent historical lease case.
(3) According to the invention, the related information of the historical lease case is acquired in the related information acquisition module of the historical lease case, so that powerful data support is provided for evaluation of the historical lease case.
(4) According to the invention, the similarity between the case currently submitted by the target person and the historical lease case is analyzed in the historical lease case evaluation module, not only is the lease time, the lease total amount, the payment mode and some evidence audios and videos analyzed, but also the identity state and the identity id of the target person are analyzed, the defect that the analysis strength of the evidence audios and videos and the identity state and the identity id of the target person is not deep enough in the prior art is overcome, the accuracy of the analysis result of the similarity between the case currently submitted by the target person and the historical lease case is improved, the analysis level is diversified, and powerful data support is provided for the analysis of the follow-up recommended legal provision to a certain extent.
(5) According to the invention, the application frequency of similar case legal provision is considered in the recommended legal provision analysis module, the application frequency of historical legal provision is considered, the problem of low suitability of the recommended legal provision is solved, the phenomenon that the reference medium of the recommended legal provision is not high in analysis is avoided, the processing progress of house leasing cases is ensured to a certain extent, and more accurate service is provided for related processing staff.
Drawings
FIG. 1 is a block diagram of a system module of the legal case applicable treaty analysis matching system of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides a legal case applicable treaty analysis matching system based on a mobile internet, comprising: the system comprises a case input module, a case processing module, a history lease case related information acquisition module, a history lease case evaluation module, a history lease case screening module, a legal provision ordering analysis module, a recommended legal provision analysis module and a cloud database.
The case input module is connected with the case processing module, the case processing module and the history lease case related information acquisition module are connected with the history lease case evaluation module, the history lease case evaluation module is connected with the history lease case screening module, the history lease case screening module is connected with the legal provision ordering analysis module, the legal provision ordering analysis module is connected with the recommended legal provision analysis module, and the cloud database is connected with the history lease case evaluation module.
The case input module is used for inputting a lease contract, inputting evidence information and inputting case related description voice by a target user.
In a specific embodiment of the present invention, the evidence information includes evidence pictures, evidence audios and evidence videos.
In the case input module, the target user inputs the related information and uploads the information to the processing center, so that basic data support is provided for subsequent case processing.
The case processing module is used for acquiring case characteristic information based on a lease contract input by a target user, and further converting case related description voice input by the target user into case related description text corresponding to the target user.
In a specific embodiment of the present invention, the case feature information includes a rental start time point, a rental end time point, a rental total amount, and a payment method.
According to the invention, the case characteristic information of the lease contract uploaded by the target user is extracted in the case processing module, and other related information is processed, so that a foundation is laid for the evaluation of the subsequent historical lease case.
The cloud database is used for storing lease contracts, evidence information and case related description voice corresponding to each historical lease case, storing identity states of the applicant to which each historical lease case belongs, and storing lease starting time points, lease ending time points, lease total amount and payment modes of the lease contracts to which each historical lease case belongs.
The history lease case related information acquisition module is used for extracting lease contracts corresponding to each history lease case from the cloud database, acquiring case characteristic information corresponding to each history lease case, and further acquiring evidence information corresponding to each history lease case and case related description voice from the cloud database.
According to the invention, the related information of the historical lease case is acquired in the related information acquisition module of the historical lease case, so that powerful data support is provided for evaluation of the historical lease case.
The history lease case evaluation module is used for comprehensively analyzing evaluation coefficients corresponding to each history lease case.
In a specific embodiment of the present invention, the specific analysis method of the evaluation coefficient corresponding to each historical rental case includes: acquiring the identity state of the target personnel, acquiring the identity state of the applicant belonging to each history leasing case from the cloud database, and further analyzing that the identity of the target personnel and the applicant belonging to each history leasing case accords with an index epsilon i I is denoted as the number of each historical rental case, i=1, 2,..n.
It should be noted that, comparing the identity state of the target person with the identity state of the applicant to which each historical rental case belongs, if the identity state of the target person is successfully matched with the identity state of the applicant to which a certain historical rental case belongs, marking the identity coincidence index of the target person and the applicant to which the historical rental case belongs as α, otherwise marking the identity coincidence index as α'.
Acquiring the identity coincidence index epsilon of target personnel and applicant to which each historical lease case belongs i Wherein ε is i =α or α'.
It should be noted in particular that the status of the identity is in particular a lessor and a lessee.
Acquiring the identity id of a target person, acquiring the identity id of a renter and the identity id of a lessee to which each historical lease case belongs from cloud data, and further analyzing the matching coefficient eta of the identity id of the target person and the identity id of an associated person to which the historical lease case belongs i 。
It should be noted that, comparing the identity id of the target person with the identity id of the lessor and the identity id of the lessee to which each history leasing case belongs, if the identity id of the target person is not successfully matched with the identity id of the lessor to which a certain history leasing case belongs and the identity id of the lessee, marking the matching coefficient of the identity id of the target person and the identity id of the associated person to which the history leasing case belongs as β, otherwise, marking the matching coefficient as β'.
Acquiring identity of target personid and the matching coefficient eta of the associated personnel identity id of the history lease case i Wherein eta i =β or β'.
Analyzing evaluation coefficients corresponding to each historical lease case
Wherein e is expressed as a natural constant,expressed as similarity, sigma, of lease contract to which target user belongs and lease contract to which ith historical lease case belongs i An evaluation index indicating that the evidence information of the target user corresponds to the evidence information of the ith historical lease case,/I>An adaptation index lambda representing correspondence of a case related description text to which a target user belongs and an i-th historical rental case related description text 1 、λ 2 、λ 3 、λ 4 、λ 5 Respectively representing the influence weight factors corresponding to the preset identity state coincidence, identity id matching, lease contract similarity, evidence information evaluation and case related description text.
In a specific embodiment of the present invention, the similarity between the lease contract to which the target user belongs and the lease contract to which each historical lease case belongs is specifically analyzed by: extracting a lease start time point T from case feature information of lease contract to which a target user belongs Starting up Rental end time T Terminal (A) A rental total amount M, and a payment method.
Extracting lease starting time point T of lease contract of each history lease case from cloud database i ' Start, lease end time Point T i 'final, lease Total amount M' i And payment means.
And acquiring the lease duration SC of the lease contract to which the target user belongs according to the lease starting time point and the lease ending time point of the lease contract to which the target user belongs.
Similarly, lease duration SC 'of lease contract to which each history lease case belongs is obtained' i 。
Comparing the payment mode of the lease contract to which the target user belongs with the payment modes of lease cases to which each history lease case belongs, and analyzing the payment mode matching coefficient FJ corresponding to the target user and each history lease case i 。
It should be noted that, the specific method for analyzing the payment mode matching coefficient corresponding to each historical lease case by the target user is as follows: matching the payment mode of the lease contract of the target user with the payment modes of the historical lease cases, if the payment mode of the lease contract of the target user is successfully matched with the payment mode of a certain historical lease case, marking the payment mode matching coefficient corresponding to the target user and the historical lease case as X, otherwise marking the payment mode matching coefficient as X', and further obtaining the payment mode matching coefficient FJ corresponding to the target user and the historical lease cases i Wherein FJ i =χ or χ'.
Analyzing the similarity of the lease contract of the target user and the lease contract of each history lease case:
wherein T' is represented as a preset allowable rental start time error, TG is represented as a preset allowable rental end time error, gamma 1 、γ 2 、γ 3 、γ 4 、γ 5 The corresponding duty factors are respectively indicated as the similar preset lease start time points, the similar lease end time points, the lease total amount, the matched payment mode and the similar lease duration.
In a specific embodiment of the present invention, the evaluation index corresponding to the evidence information of the target user and the evidence information of each historical lease case includes: and extracting each evidence picture, each evidence audio and each evidence video from the evidence information of the target user.
It should be noted that each evidence picture includes a payment screenshot picture.
Acquiring each payment date R corresponding to the target user according to each evidence picture to which the target user belongs m Where m is denoted as the number of each payment date, m=1, 2.
Acquiring each payable date R 'corresponding to the target user according to the lease contract corresponding to the target user' m 。
Analyzing payment date assessment coefficients corresponding to target usersWhere R' represents a preset allowable payment extension period.
Similarly, analysis is carried out to obtain a payment date evaluation coefficient PL 'corresponding to each historical lease case' i 。
And analyzing a keyword set B corresponding to the target user according to each evidence audio and each evidence video corresponding to the target user.
It should be noted that, according to each evidence audio and each evidence video corresponding to the target user, the keyword set B corresponding to the target user is analyzed, and the specific method is as follows:
and converting each evidence audio corresponding to the target user into each evidence text.
And extracting the audio corresponding to each evidence video from each evidence video corresponding to the target user, and similarly, converting the audio into each evidence video text.
And summarizing the keywords of each evidence text corresponding to the target user and the keywords of each evidence video text, thereby obtaining a keyword set B corresponding to the target user.
Similarly, analyzing and obtaining a keyword set B corresponding to each history lease case i ′。
Analyzing keyword similarity coefficients corresponding to each historical lease case of target user
The evaluation indexes corresponding to the evidence information of the target user and the evidence information of each historical lease case are analyzed as follows:
wherein χ is 1 、χ 2 Respectively representing the preset payment date evaluation coefficient and the weight coefficient corresponding to the keyword similarity.
In a specific embodiment of the present invention, the adaptation index corresponding to the case related description text to which the target user belongs and the case related description text to which each historical rental case belongs is specifically analyzed by: the analysis method of the keyword similarity coefficient corresponding to each historical lease case of the target user is consistent with that of the target user, and the adaptation index corresponding to the case related description of the target user and the case description text of each historical lease case is analyzed
According to the invention, the similarity between the case currently submitted by the target person and the historical lease case is analyzed in the historical lease case evaluation module, not only is the lease time, the lease total amount, the payment mode and some evidence audios and videos analyzed, but also the identity state and the identity id of the target person are analyzed, the defect that the analysis strength of the evidence audios and videos and the identity state and the identity id of the target person is not deep enough in the prior art is overcome, the accuracy of the analysis result of the similarity between the case currently submitted by the target person and the historical lease case is improved, the analysis level is diversified, and powerful data support is provided for the analysis of the follow-up recommended legal provision to a certain extent.
The history lease case screening module is used for screening each adaptive history lease case corresponding to the target user according to the evaluation coefficient corresponding to each history lease case.
It should be noted that, the specific method for screening the adapted historical rental case corresponding to the target user is as follows: comparing the evaluation coefficient corresponding to each history lease case with a preset evaluation coefficient threshold, and if the evaluation coefficient corresponding to a certain history lease case is greater than or equal to the evaluation coefficient threshold, marking the history lease case as an adaptation history lease case, thereby obtaining each adaptation history lease case corresponding to a target user
The legal provision ordering analysis module is used for extracting each practical application legal provision corresponding to each history leasing case from the cloud database, and further analyzing the basic ordering value corresponding to each practical application legal provision accordingly.
In a specific embodiment of the present invention, the specific analysis method of the basic ranking value corresponding to each practical application legal provision is as follows: summarizing each practical application legal provision corresponding to each historical lease case, and further obtaining the application times of each practical application legal provision.
And sequencing the practical application legal provision according to the sequence of the application times from high to low, so as to obtain a basic sequencing value corresponding to the practical application legal provision.
The recommended legal provision analysis module is used for analyzing each recommended legal provision corresponding to the target user according to the adaptive history leasing case corresponding to the target user and the basic sorting value corresponding to each actual application legal provision, and sending the recommended legal provision to related processing personnel.
In a specific embodiment of the present invention, the specific analysis method of each recommended legal provision corresponding to the target user is as follows: and acquiring each actual application legal provision corresponding to each adapting historical lease case according to each actual application legal provision corresponding to each historical lease case, and marking the actual application legal provision as each legal provision to be analyzed corresponding to each adapting historical lease case.
The analysis method is consistent with the analysis method of the basic ranking value corresponding to each practical application legal provision, and ranking value PA corresponding to each legal provision to be analyzed is obtained through analysis d Where d is denoted as the number of each legal provision to be analyzed, d=1, 2.
Acquiring a basic ranking value PA 'corresponding to each legal provision to be analyzed according to the basic ranking value corresponding to each actual application legal provision' d 。
Analyzing recommendation indexes corresponding to legal provisions to be analyzed:
where f is expressed as the number of legal provisions to be analyzed, delta 1 、δ 2 The weight factors are expressed as preset sorting values and weight factors corresponding to basic sorting values.
And analyzing each recommended legal provision of the target user according to the recommendation index corresponding to each legal provision to be analyzed.
It should be noted that, comparing the recommendation index corresponding to each legal provision to be analyzed with a preset recommendation index threshold, if the recommendation index corresponding to a certain legal provision to be analyzed is greater than or equal to the recommendation index threshold, marking the legal provision to be analyzed as a recommended legal provision, and further obtaining each recommended legal provision of the target user.
According to the invention, the application frequency of similar case legal provision is considered in the recommended legal provision analysis module, the application frequency of historical legal provision is considered, the problem of low suitability of the recommended legal provision is solved, the phenomenon that the reference medium of the recommended legal provision is not high in analysis is avoided, the processing progress of house leasing cases is ensured to a certain extent, and more accurate service is provided for related processing staff.
It should be noted that the foregoing description of the specific embodiments is merely illustrative and explanatory of the structures of the invention, and various modifications, additions and substitutions are possible, by those skilled in the art, of the described specific embodiments without departing from the scope of the invention as disclosed in the accompanying claims.
Claims (10)
1. The legal case applicable treaty analysis matching system based on the mobile Internet is characterized by comprising the following components:
the case input module is used for inputting a lease contract, inputting evidence information and inputting case related description voice by a target user;
the case processing module is used for acquiring case characteristic information based on a lease contract input by a target user and converting case related description voice input by the target user into case related description text corresponding to the target user;
the cloud database is used for storing lease contracts, evidence information and case related description voices corresponding to each historical lease case, storing identity states of the applicant belonging to each historical lease case and storing case characteristic information corresponding to the lease contract belonging to each historical lease case;
the historical lease case related information acquisition module is used for extracting lease contracts corresponding to each historical lease case from the cloud database, acquiring case characteristic information corresponding to each lease case, and further acquiring evidence information corresponding to each historical lease case and case related description voice from the cloud database;
the historical lease case evaluation module is used for comprehensively analyzing evaluation coefficients corresponding to each historical lease case;
the historical lease case screening module is used for screening each adaptive historical lease case corresponding to the target user according to the evaluation coefficient corresponding to each historical lease case;
the legal provision ordering analysis module is used for extracting each practical application legal provision corresponding to each history leasing case from the cloud database, and analyzing a basic ordering value corresponding to each practical application legal provision according to the practical application legal provision;
and the recommended legal provision analysis module is used for analyzing each recommended legal provision corresponding to the target user according to the adaptive historical leasing case corresponding to the target user and the basic ranking value corresponding to each actual application legal provision, and sending the recommended legal provision to related processing personnel.
2. The mobile internet-based legal case applicable treaty analysis matching system of claim 1, wherein the case feature information includes: a rental start time point, a rental end time point, a rental total amount, and a payment method.
3. The mobile internet-based legal case applicable treaty analysis matching system of claim 2, wherein the evidence information includes: evidence pictures, evidence audio and evidence video.
4. The legal case applicable treaty analysis and matching system based on the mobile internet of claim 3, wherein the analysis method comprises the following sub-steps:
s1.1, acquiring the identity state of a target person, acquiring the identity state of the applicant belonging to each historical lease case from a cloud database, and analyzing that the identity of the target person and the applicant belonging to each historical lease case accords with an index epsilon i I represents the number of each history rental case, i=1, 2, n;
s1.2, acquiring the identity id of a target person, acquiring the identity id of a lessor and the identity id of a lessee to which each history leasing case belongs from cloud data, and analyzing the matching coefficient eta of the identity id of the target person and the identity id of an associated person to which the history leasing case belongs i ；
S1.3, analyzing evaluation coefficients corresponding to each historical lease case, wherein the formula is as follows:
wherein mu i E is expressed as a natural constant for the evaluation coefficient of the i-th historical rental case;
expressed as similarity, sigma, of lease contract to which target user belongs and lease contract to which ith historical lease case belongs i An evaluation index indicating that the evidence information of the target user corresponds to the evidence information of the ith historical lease case,/I>The adaptation index corresponding to the case related description text of the target user and the case related description text of the i-th historical lease case is represented;
λ 1 、λ 2 、λ 3 、λ 4 、λ 5 respectively representing the influence weight factors corresponding to the preset identity state coincidence, identity id matching, lease contract similarity, evidence information evaluation and case related description text.
5. The legal case applicable treaty analysis and matching system based on mobile internet of claim 4, wherein in step S1.3, the similarity between the lease contract to which the target user belongs and the lease contract to which each historical lease case belongs, the analysis method includes the following sub-steps:
s2.1, extracting a lease start time point T from case feature information of a lease contract to which a target user belongs Starting up Rental end time T Terminal (A) The total leasing amount M and the payment mode;
s2.2, extracting lease starting time points T of lease contracts of each history lease case from a cloud database i ′ Starting up Rental end time T i ′ Terminal (A) Total rental amount M i ' and payment means;
s2.3, acquiring the lease duration SC of the lease contract to which the target user belongs according to the lease start time point and the lease end time point of the lease contract to which the target user belongs;
s2.4, obtaining lease duration SC of lease contracts of each history lease case by using the same method of the step S2.3 i ′；
S2.5, comparing the payment mode of the lease contract to which the target user belongs with the payment modes of lease cases to which each history lease case belongs, and analyzing the payment mode matching coefficient FJ of the target user corresponding to each history lease case i ；
S2.6, analyzing the similarity between the lease contract of the target user and the lease contract of each history lease case, wherein the formula is as follows:
wherein T' is represented as a preset allowable rental start time error, TG is represented as a preset allowable rental end time error, gamma 1 、γ 2 、γ 3 、γ 4 、γ 5 The corresponding duty factors are respectively indicated as the similar preset lease start time points, the similar lease end time points, the lease total amount, the matched payment mode and the similar lease duration.
6. The legal case applicable treaty analysis matching system based on mobile internet of claim 5, wherein in step S1.3, the evaluation index corresponding to the evidence information of the target user and the evidence information of each historical lease case includes the following sub-steps:
s3.1, extracting each evidence picture, each evidence audio and each evidence video from evidence information of a target user;
s3.2, acquiring each payment date R corresponding to the target user according to each evidence picture to which the target user belongs m Where m is denoted as the number of each payment date, m=1, 2, i;
s3.3, acquiring each date R 'corresponding to the target user according to the lease contract corresponding to the target user' m ；
S3.4, analyzing a payment date evaluation coefficient PL corresponding to the target user, wherein the formula is as follows:
wherein R' represents a preset allowable payment extension period;
s3.5, obtaining a payment date evaluation coefficient PL corresponding to each historical lease case by using the same method of the step S3.4 i ′；
S3.6, analyzing a keyword set B corresponding to the target user according to each evidence audio and each evidence video corresponding to the target user;
s3.7, analyzing and obtaining a keyword set B corresponding to each history lease case by using the same method as the step S3.6 i ′；
S3.8, analyzing the keyword similarity coefficient tau corresponding to each historical lease case of the target user i The formula is as follows:
s3.9, analyzing evaluation indexes corresponding to the evidence information of the target user and the evidence information of each historical lease case:
wherein χ is 1 、χ 2 Respectively representing the preset payment date evaluation coefficient and the weight coefficient corresponding to the keyword similarity.
7. The mobile internet-based legal case applicable treaty analysis and matching system of claim 6, wherein in step S1.3, the adaptation index corresponding to the case related description text to which the target user belongs and the case related description text to which each history rental case belongs is specifically analyzed by the following method: the analysis method of the keyword similarity coefficient corresponding to each historical lease case of the target user is consistent with that of the target user, and the adaptation index corresponding to the case related description of the target user and the case description text of each historical lease case is analyzed
8. The mobile internet-based legal case applicable treaty analysis and matching system of claim 1, wherein the basic ranking values corresponding to the practical applicable legal cases are specifically analyzed by the following steps:
summarizing each practical application legal provision corresponding to each historical lease case to obtain the application times of each practical application legal provision;
and sequencing the practical application legal provision according to the sequence of the application times from high to low, and obtaining a basic sequencing value corresponding to the practical application legal provision.
9. The mobile internet-based legal case applicable treaty analysis and matching system of claim 8, wherein the analysis method includes:
acquiring each actual application legal provision corresponding to each adapting historical lease case according to each actual application legal provision corresponding to each historical lease case, and marking the actual application legal provision as each legal provision to be analyzed corresponding to each adapting historical lease case;
the analysis method is consistent with the analysis method of the basic ranking value corresponding to each practical application legal provision, and ranking value PA corresponding to each legal provision to be analyzed is obtained through analysis d Where d is the number of each legal provision to be analyzed, d=1, 2,..f;
acquiring a basic ranking value PA 'corresponding to each legal provision to be analyzed according to the basic ranking value corresponding to each actual application legal provision' d ；
Analyzing the recommended index TJ corresponding to each legal provision to be analyzed d The formula is as follows:
where f is expressed as the number of legal provisions to be analyzed, delta 1 、δ 2 The weight factor is represented as a preset sorting value and a weight factor corresponding to a basic sorting value;
and analyzing each recommended legal provision of the target user according to the recommended index corresponding to each legal provision to be analyzed.
10. The mobile internet-based legal case applicable condition analysis and matching system according to any one of claims 1 to 9, wherein the case entry module is connected with the case processing module, the case processing module and the history rental case related information acquisition module are both connected with the history rental case evaluation module, the history rental case evaluation module is connected with the history rental case screening module, the history rental case screening module is connected with the legal condition sorting analysis module, the legal condition sorting analysis module is connected with the recommended legal condition analysis module, and the cloud database is connected with the history rental case related information acquisition module and the history rental case evaluation module.
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