CN111125319A - Enterprise basic law intelligent consultation terminal, system and method - Google Patents
Enterprise basic law intelligent consultation terminal, system and method Download PDFInfo
- Publication number
- CN111125319A CN111125319A CN201911399248.9A CN201911399248A CN111125319A CN 111125319 A CN111125319 A CN 111125319A CN 201911399248 A CN201911399248 A CN 201911399248A CN 111125319 A CN111125319 A CN 111125319A
- Authority
- CN
- China
- Prior art keywords
- case
- legality
- matching
- user
- analysis
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 33
- 238000004458 analytical method Methods 0.000 claims abstract description 49
- 238000011156 evaluation Methods 0.000 claims abstract description 24
- 238000010276 construction Methods 0.000 claims abstract description 20
- 238000012216 screening Methods 0.000 claims description 16
- 230000000694 effects Effects 0.000 claims description 15
- 238000012217 deletion Methods 0.000 description 5
- 230000037430 deletion Effects 0.000 description 5
- 230000008451 emotion Effects 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 230000003993 interaction Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000013019 agitation Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000002996 emotional effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/334—Query execution
- G06F16/3344—Query execution using natural language analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/338—Presentation of query results
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Tourism & Hospitality (AREA)
- General Engineering & Computer Science (AREA)
- Marketing (AREA)
- Databases & Information Systems (AREA)
- Entrepreneurship & Innovation (AREA)
- Data Mining & Analysis (AREA)
- General Business, Economics & Management (AREA)
- Computational Linguistics (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Artificial Intelligence (AREA)
- Technology Law (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Health & Medical Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to the technical field of legal service systems, in particular to an enterprise basic law intelligent consultation terminal, system and method, wherein the method comprises the following steps: an input acquisition step of acquiring description contents input by a user; a semantic parsing step, namely performing semantic parsing on the description content input by the user to obtain semantic keywords; an intelligent evaluation step, namely analyzing the case according to the semantic keywords and generating an analysis result and a consultation suggestion; the intelligent evaluation step specifically comprises: case construction, namely matching a case construction model to generate case content; case analysis, namely matching related legal items and cases according to case contents to generate an analysis result; and a consulting suggestion step of generating consulting suggestions according to the analysis results. The enterprise basic law intelligent consultation terminal, the system and the method provided by the invention can quickly and accurately solve the problem of law consultation for enterprise managers, reduce the consultation waiting time of enterprises and reduce the cost of enterprise law operation.
Description
Technical Field
The invention relates to the technical field of legal service systems, in particular to an enterprise basic law intelligent consultation terminal, system and method.
Background
With the continuous improvement of the law in China, civil disputes are increasingly common to be solved through litigation. However, since law is a special technology, the strategy and the process sequence adopted by litigation are very important to the outcome of litigation.
The law-related decision-making work of the existing enterprises is to consult expert teams, the existing law consultation processing modes adopt manual processing, the enterprises communicate with law professionals in a network, telephone and interview mode to know the details of laws and obtain consultation results, and therefore legal rights and interests of the enterprises are maintained by means of laws. However, the processing method of manual consultation occupies a lot of manpower and time, the enterprise needs to wait or make advance reservation, the working efficiency of legal consultation service is low, the manpower cost is high, and the legal operation cost of the enterprise is increased.
Disclosure of Invention
The invention provides an enterprise basic law intelligent consultation terminal, system and method, which can quickly and accurately solve the problem of law consultation for enterprise managers, reduce the consultation waiting time of enterprises and reduce the cost of enterprise law operation.
In order to solve the technical problem, the present application provides the following technical solutions:
an enterprise basic law intelligent consultation method comprises the following steps: an input acquisition step of acquiring description contents input by a user; a semantic parsing step, namely performing semantic parsing on the description content input by the user to obtain semantic keywords; an intelligent evaluation step, namely analyzing the case according to the semantic keywords and generating an analysis result and a consultation suggestion; the intelligent evaluation step specifically comprises: a case construction step, namely matching a case construction model according to the semantic keywords, and interacting with a user according to the case construction model to generate case content; the case content is a set of a plurality of case events arranged in sequence according to time, and the case events comprise time, people, places, cause and effect and items; case analysis, namely matching related law bars and cases according to case contents, and performing legality analysis on the case contents according to the law bars and the cases to generate an analysis result; and a consulting suggestion step of generating consulting suggestions according to the analysis results.
In the technical scheme of the invention, the description content of a user is acquired through an input acquisition module, semantic keywords such as characters, time, items, places, numerical values and the like in the description content of the user are acquired through a semantic analysis module, a case construction module reconstructs and restores the case content through the semantic keywords, which is equivalent to combing the description content of the user to change the description content of the user into content which can be identified by a computer, a matching module matches corresponding laws and cases according to the semantic keywords and the case content, an evaluation suggestion module analyzes the case content according to the laws and cases to finally generate legal flow suggestions to be displayed to the user, for enterprises, the technical scheme of the invention can quickly push proper cases and laws for the enterprises according to the description content and generate the legal flow suggestions, and a large number of cases are integrated through a big data technology, the system can quickly and accurately show related results for enterprise managers, reduce the consulting time of enterprises on related laws, cases and the like, and can help the enterprise managers to quickly understand related contents through the cases and further quickly solve the problems of the enterprises on the basis of the analysis results of data without depending on the personal experience of experts, so that the decision-making results are more objective and accurate, and the common problems can be quickly solved by the system, and the cost in the aspect of enterprise legal operation is reduced.
Further, the method also comprises the pushing step: and pushing the legal provision, the case and the consultation suggestion related to the case content to the user terminal. The user can conveniently check the consultation result in time.
Further, the case situation analyzing step comprises:
matching similar cases from a case library according to case contents, and obtaining related laws of the case contents according to laws related to the cases;
a legality analysis step, namely evaluating the legality of the items of each character in each case event according to the laws, cases and case contents to obtain illegal risk items of the items of each character and corresponding laws and cases;
and an outcome analysis step, namely generating the outcome of each figure according to the analysis result, the law, the case and the case content of the legality analysis step, wherein the outcome comprises the illegal penalty cost and the claim profit. And the legality and the final result of each character item in each case event are evaluated, so that the evaluation is more comprehensive.
Further, the step of legality analysis specifically comprises:
a time legality evaluation step, which is used for carrying out legality analysis on the time in the case event to obtain a time legality score;
an item legality evaluation step, namely carrying out legality analysis on the items in the case event to obtain item legality scores;
a cause and effect legality evaluation step, wherein the cause and effect in case events are subjected to legality analysis to obtain a cause and effect legality score;
a site legality evaluation step, which is to analyze the legality of the site in the case event to obtain a site legality score;
and obtaining the illegal risk item according to the time legality score, the item legality score, the cause-effect legality score and the place legality score. And (4) carrying out legality evaluation on time, matters, cause and effect and places in case content, further discovering places possibly illegal and comprehensively finding out illegal risk items.
Further, the case matching step comprises:
a matching parameter analyzing step, namely acquiring matching parameters according to case content, wherein the matching parameters comprise case types, case time ranges, case character relations, personnel numbers and case involved money;
a screening step, namely screening a matching range library from the database according to the semantic keywords and the matching parameters; and calculating the coincidence rate of each case in the matching range library and the case events of the case contents, and selecting the first N cases with the highest coincidence rate as matching results.
The case content can be matched and screened from the aspects of types and the like through the matching parameters, and the matching speed and accuracy are further improved.
Further, the input acquiring step includes:
a voice input acquisition step, which is used for acquiring the voice of a user and converting the voice content of the user into text content;
and a text input acquisition step, namely acquiring text input by a user or text content converted by voice as description content input by the user. The user can input conveniently through various modes such as voice, text and the like.
Further, the method also comprises the matching feedback adjustment step: and collecting the times of checking or collecting each case and each legal provision by the user, and adjusting the screening parameters of the matching range library according to the times of checking or collecting. The matching is more accurate by adjusting the screening parameters of the matching range library.
Furthermore, corresponding laws and cases are matched according to the semantic keywords and the association degree of the matching parameters and the matching range libraries in the screening step, and the association degree is corrected according to the checking and collecting times of the laws and cases in the feedback adjusting step. And adjusting the screening parameters by correcting the correlation degree.
Furthermore, the invention also discloses an enterprise basic law intelligent consultation system which uses any one of the enterprise basic law intelligent consultation methods.
Furthermore, the invention also discloses an enterprise basic law intelligent consultation terminal loaded with the enterprise basic law intelligent consultation system.
By using the enterprise basic law intelligent consultation method, appropriate cases and laws can be quickly pushed for enterprises, legal flow suggestions are generated, a large number of cases are integrated through a big data technology, relevant results can be quickly and accurately displayed for enterprise managers, the consultation time of the enterprises on relevant laws, cases and the like is reduced, the decision results are based on the analysis results of data, the method does not depend on the personal experience of experts, is more objective and accurate, and the cost of enterprise legal operation is reduced.
Drawings
FIG. 1 is a flowchart of an embodiment of an intelligent consulting method for enterprise basic law according to the present invention.
Detailed Description
The following is further detailed by way of specific embodiments:
example one
As shown in fig. 1, the method for intelligent consulting of enterprise basic law in this embodiment includes the following steps:
an input acquisition step of acquiring description contents input by a user; in this embodiment, the input acquiring step includes:
a voice input acquisition step, namely acquiring user voice and converting the user voice content into text content, wherein a voice recognition algorithm module of science news is adopted to convert the user voice content into text in the embodiment;
and a text input acquisition step, namely acquiring text input by a user or text content converted by voice as description content input by the user. The user can input conveniently through various modes such as voice, text and the like.
A semantic parsing step, namely performing semantic parsing on the description content input by the user to obtain semantic keywords; in this embodiment, the semantic parsing step adopts an artificial intelligence semantic parsing algorithm based on RNNs, such as an Tencent cloud NPL engine, to perform word segmentation, semantic parsing and the like of the description content, and obtains semantic keywords according to a keyword library stored in a database, where the semantic keywords include case keywords including five types of time, people, places, cause and effect, and matters.
An intelligent evaluation step, namely analyzing the case according to the semantic keywords and generating an analysis result and a consultation suggestion; the intelligent evaluation step specifically comprises:
a case construction step, namely matching a case construction model according to the semantic keywords, and interacting with a user according to the case construction model to generate case content; the case content is a set of a plurality of case events arranged in sequence according to time, and the case events comprise time, people, places, cause and effect and items; in this embodiment, various commonly used case construction models are stored in the database, different models correspond to different types of case events, for example, a case construction model for contract time default, a case construction model for loan disputes, a case construction model for infringement, and the like, different case construction models have different interaction problems, in the case construction step, interaction is performed with a user according to the case construction model, contents required for case construction are acquired by inquiring an interaction form, and finally, case contents are completely supplemented according to the acquired semantic keywords and the contents acquired in the interaction process to form case contents.
Case analysis, namely matching related law bars and cases according to case contents, and performing legality analysis on the case contents according to the law bars and the cases to generate an analysis result; in this embodiment, the case analysis step includes a case matching step, a validity analysis step, and an outcome analysis step.
Matching similar cases from a case library according to case contents in the case matching step, and obtaining related laws of the case contents according to laws related to the cases; the case matching step specifically comprises a matching parameter analyzing step, a screening step and a matching feedback adjusting step.
In the matching parameter analyzing step, matching parameters are obtained according to case content, and the matching parameters comprise case types, case time ranges, case character relations, personnel numbers and case involved money;
in the screening step, a matching range library is screened from a database according to the semantic keywords and the matching parameters; in this embodiment, each matching range library is provided with a degree of association with each semantic keyword and matching parameter, in the screening step, corresponding rules and cases are matched according to the degree of association between the semantic keywords and the matching parameters and each matching range library, and the coincidence rate of case events of each case and case content in the matching range library is calculated.
And in the matching feedback adjustment step, the checking or collecting times of each case and each legal provision by the user are collected, and the screening parameters of the matching range library are adjusted according to the checking or collecting times. The matching is more accurate by adjusting the screening parameters of the matching range library.
And in the feedback adjustment step, the correlation degree is corrected according to the viewing and collection times of each rule and case. And adjusting the screening parameters by correcting the correlation degree.
In the legality analysis step, the legality of the items of each character in each case event is evaluated according to the laws, cases and case contents to obtain illegal risk items of the items of each character and corresponding laws and cases; the legality analyzing step specifically comprises the following steps:
a time legality evaluation step, which is used for carrying out legality analysis on the time in the case event to obtain a time legality score;
an item legality evaluation step, namely carrying out legality analysis on the items in the case event to obtain item legality scores;
a cause and effect legality evaluation step, wherein the cause and effect in case events are subjected to legality analysis to obtain a cause and effect legality score;
a site legality evaluation step, which is to analyze the legality of the site in the case event to obtain a site legality score;
and obtaining the illegal risk item according to the time legality score, the item legality score, the cause-effect legality score and the place legality score. The time, the items, the cause and the place in the case content are evaluated according to the steps, so that the places possibly illegal are found, and the illegal risk items are comprehensively found.
In the consequence analysis step, the consequences of each figure are generated according to the analysis result, the law, the case and the case content in the legality analysis step, wherein the consequences comprise illegal penalty cost and claim profit. And the legality and the final result of each character item in each case event are evaluated, so that the evaluation is more comprehensive.
And a consulting suggestion step of generating consulting suggestions according to the analysis results.
A pushing step: and pushing the legal provision, the case and the consultation suggestion related to the case content to the user terminal. The user can conveniently check the consultation result in time.
The embodiment also discloses an enterprise basic law intelligent consultation system which uses any one of the enterprise basic law intelligent consultation methods.
The embodiment also discloses an enterprise basic law intelligent consultation terminal loaded with the enterprise basic law intelligent consultation system.
By using the enterprise basic law intelligent consultation method, the system and the terminal, appropriate cases and laws can be quickly pushed for enterprises, legal flow suggestions are generated, a large number of cases are integrated through a big data technology, relevant results can be quickly and accurately displayed for enterprise managers, the consultation time of the enterprises for relevant laws, cases and the like is reduced, the decision-making results are based on the analysis results of data, the method does not depend on the personal experience of experts, is more accurate, and the cost of enterprise legal operation is reduced.
Example two
The difference between this embodiment and the first embodiment is that, in this embodiment, the input acquiring step further includes:
the method comprises the steps of acquiring emotion, namely detecting the jitter frequency of an input terminal and the text error rate in description content, and judging whether related personnel have emotional excitement or not according to whether the input text error rate is higher than an error early warning value or not and whether the jitter frequency exceeds the jitter early warning value or not;
and a placation information playing step: and when judging that excited emotion occurs to related personnel, playing soothing information, such as pre-recorded soothing language or some successful cases and the like.
And an input sorting step, namely prompting a user to revise and adjust the input description content after playing the soothing information.
The input sorting step comprises:
and a deletion recording step, recording deletion operation of the user when the user revises the description content, judging deletion intervals between each sentence (the division of the sentence can be comma or full stop, in the embodiment, the sentence is divided by full stop), and storing the sentences of which the deletion intervals are not more than 0.5 second as the same prompt information in a prompt information base.
And a prompt input step, namely matching prompt information from a prompt information base based on input words when the user re-inputs the words, and displaying the successfully matched promotion information.
When the user is excited, the situations of logic confusion and word inadequacy easily occur, so that the input description content is easy to be inaccurate. When the emotion agitation of the user is detected, the pacifying information is played, so that the user can be effectively pacified, and the user can be cooled and calmed down. When the user calms down, the user can probably feel unreasonable by looking at the previous input, and then the user can delete the input and input again. In this embodiment, sentences whose deletion intervals do not exceed 0.5 second are stored in the prompt information library as the same piece of prompt information, so that the same part of content can be stored in a concentrated manner. When the user re-inputs, the prompt information is matched from the prompt information base based on the input words, the successfully matched promoting information is displayed, the same part of content can be displayed to the user, the user can select whether to copy, the input efficiency of the user is improved, and the time spent on re-input is reduced.
For example, the user a inputs 10 sentences when the emotion is excited, feels that the 10 sentences input after the emotion is pacified are not correct, and then deletes the 10 sentences, first deletes the last 2 sentences (namely 9-10 sentences), deletes 2-8 sentences after 1s, and deletes the 1 st sentence after 1 s. Finally, 2 sentences are stored in the prompt information base as a whole, and 2-8 sentences and 1 st sentence are also stored in the prompt information base as a whole respectively. Then the user A feels that the last 2 sentences need to be spoken first and starts to typewrite again, at the moment, the user side matches prompt information from the prompt information base based on input words, the last 2 sentences which are successfully matched are displayed, and the user can directly copy and paste.
The above are merely examples of the present invention, and the present invention is not limited to the field related to this embodiment, and the common general knowledge of the known specific structures and characteristics in the schemes is not described herein too much, and those skilled in the art can know all the common technical knowledge in the technical field before the application date or the priority date, can know all the prior art in this field, and have the ability to apply the conventional experimental means before this date, and those skilled in the art can combine their own ability to perfect and implement the scheme, and some typical known structures or known methods should not become barriers to the implementation of the present invention by those skilled in the art in light of the teaching provided in the present application. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. An enterprise basic law intelligent consultation method is characterized in that: the method comprises the following steps:
an input acquisition step of acquiring description contents input by a user; a semantic parsing step, namely performing semantic parsing on the description content input by the user to obtain semantic keywords;
an intelligent evaluation step, namely analyzing the case according to the semantic keywords and generating an analysis result and a consultation suggestion; the intelligent evaluation step specifically comprises:
a case construction step, namely matching a case construction model according to the semantic keywords, and interacting with a user according to the case construction model to generate case content; the case content is a set of a plurality of case events arranged in sequence according to time, and the case events comprise time, people, places, cause and effect and items;
case analysis, namely matching related law bars and cases according to case contents, and performing legality analysis on the case contents according to the law bars and the cases to generate an analysis result;
and a consulting suggestion step of generating consulting suggestions according to the analysis results.
2. The intelligent consulting method of enterprise basic law according to claim 1, wherein: further comprising a pushing step: and pushing the legal provision, the case and the consultation suggestion related to the case content to the user terminal.
3. The intelligent consulting method of enterprise basic law according to claim 2, wherein: the case situation analysis step comprises:
matching similar cases from a case library according to case contents, and obtaining related laws of the case contents according to laws related to the cases;
a legality analysis step, namely evaluating the legality of the items of each character in each case event according to the laws, cases and case contents to obtain illegal risk items of the items of each character and corresponding laws and cases;
and an outcome analysis step, namely generating the outcome of each figure according to the analysis result, the law, the case and the case content of the legality analysis step, wherein the outcome comprises the illegal penalty cost and the claim profit.
4. The intelligent consulting method of enterprise basic law according to claim 3, wherein: the legality analyzing step specifically comprises the following steps:
a time legality evaluation step, which is used for carrying out legality analysis on the time in the case event to obtain a time legality score;
an item legality evaluation step, namely carrying out legality analysis on the items in the case event to obtain item legality scores;
a cause and effect legality evaluation step, wherein the cause and effect in case events are subjected to legality analysis to obtain a cause and effect legality score;
a site legality evaluation step, which is to analyze the legality of the site in the case event to obtain a site legality score;
and obtaining the illegal risk item according to the time legality score, the item legality score, the cause-effect legality score and the place legality score.
5. The intelligent consulting method of enterprise basic law according to claim 4, wherein: the case matching step comprises:
a matching parameter analyzing step, namely acquiring matching parameters according to case content, wherein the matching parameters comprise case types, case time ranges, case character relations, personnel numbers and case involved money;
a screening step, namely screening a matching range library from the database according to the semantic keywords and the matching parameters; and calculating the coincidence rate of each case in the matching range library and the case events of the case contents, and selecting the first N cases with the highest coincidence rate as matching results.
6. The intelligent consulting method of enterprise basic law according to claim 5, wherein: the input acquisition step includes:
a voice input acquisition step, which is used for acquiring the voice of a user and converting the voice content of the user into text content;
and a text input acquisition step, namely acquiring text input by a user or text content converted by voice as description content input by the user.
7. The method for intelligent consulting of enterprise basic law as claimed in claim 6, wherein: further comprising the matching feedback adjustment step: and collecting the times of checking or collecting each case and each legal provision by the user, and adjusting the screening parameters of the matching range library according to the times of checking or collecting.
8. The method of claim 7, wherein the method comprises the following steps: and in the screening step, corresponding laws and cases are matched according to the semantic keywords and the association degree of the matching parameters and each matching range library, and in the feedback adjusting step, the association degree is corrected according to the viewing and collecting times of each law and case.
9. The utility model provides an enterprise basic law intelligence consultation system which characterized in that: the method of intelligent consulting of business basic law as claimed in any one of claims 1 to 8 is used.
10. The utility model provides an enterprise basic law intelligence consultation terminal which characterized in that: the enterprise basic law intelligent consultative system of claim 9 is loaded.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911399248.9A CN111125319A (en) | 2019-12-30 | 2019-12-30 | Enterprise basic law intelligent consultation terminal, system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911399248.9A CN111125319A (en) | 2019-12-30 | 2019-12-30 | Enterprise basic law intelligent consultation terminal, system and method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111125319A true CN111125319A (en) | 2020-05-08 |
Family
ID=70505536
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911399248.9A Pending CN111125319A (en) | 2019-12-30 | 2019-12-30 | Enterprise basic law intelligent consultation terminal, system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111125319A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113535933A (en) * | 2021-06-01 | 2021-10-22 | 科大讯飞股份有限公司 | Case retrieval method and device, electronic equipment and storage device |
-
2019
- 2019-12-30 CN CN201911399248.9A patent/CN111125319A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113535933A (en) * | 2021-06-01 | 2021-10-22 | 科大讯飞股份有限公司 | Case retrieval method and device, electronic equipment and storage device |
| CN113535933B (en) * | 2021-06-01 | 2023-07-25 | 科大讯飞股份有限公司 | Case retrieval method and device, electronic equipment and storage device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20190043506A1 (en) | Methods and systems for transcription | |
| US10769552B2 (en) | Justifying passage machine learning for question and answer systems | |
| US8407253B2 (en) | Apparatus and method for knowledge graph stabilization | |
| CN110619506B (en) | Post image generation method, post image generation device and electronic equipment | |
| WO2021047186A1 (en) | Method, apparatus, device, and storage medium for processing consultation dialogue | |
| US8117177B2 (en) | Apparatus and method for searching information based on character strings in documents | |
| US20070220063A1 (en) | Event data translation system | |
| CN112800170A (en) | Question matching method and device and question reply method and device | |
| US8719025B2 (en) | Contextual voice query dilation to improve spoken web searching | |
| US20130262104A1 (en) | Procurement System | |
| CN109299245B (en) | Method and device for recalling knowledge points | |
| CN112487140A (en) | Question-answer dialogue evaluating method, device, equipment and storage medium | |
| US10586174B2 (en) | Methods and systems for finding and ranking entities in a domain specific system | |
| CN109101551B (en) | Question-answer knowledge base construction method and device | |
| US11553085B2 (en) | Method and apparatus for predicting customer satisfaction from a conversation | |
| US20200286485A1 (en) | Methods and systems for transcription | |
| CN112765974B (en) | Service assistance method, electronic equipment and readable storage medium | |
| CN110008308B (en) | Method and device for supplementing information for user question | |
| CN117194602B (en) | Local knowledge base updating method and system based on large language model and BERT model | |
| CN111144087A (en) | Enterprise legal flow assistant decision-making system and method based on artificial intelligence | |
| CN116775879A (en) | Fine tuning training method of large language model, contract risk review method and system | |
| CN111145053A (en) | Enterprise law consultant management system and method based on artificial intelligence | |
| CN111125319A (en) | Enterprise basic law intelligent consultation terminal, system and method | |
| CN105405051A (en) | Financial event prediction method and apparatus | |
| US20230081891A1 (en) | System and method of managing knowledge for knowledge graphs |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20200508 |
|
| WD01 | Invention patent application deemed withdrawn after publication |