CN110489458A - Analysis method based on semantics recognition - Google Patents
Analysis method based on semantics recognition Download PDFInfo
- Publication number
- CN110489458A CN110489458A CN201910702575.0A CN201910702575A CN110489458A CN 110489458 A CN110489458 A CN 110489458A CN 201910702575 A CN201910702575 A CN 201910702575A CN 110489458 A CN110489458 A CN 110489458A
- Authority
- CN
- China
- Prior art keywords
- bullet cabinet
- information
- background server
- bullet
- semantics recognition
- 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
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computational Linguistics (AREA)
- Probability & Statistics with Applications (AREA)
- Software Systems (AREA)
- Mathematical Physics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Fuzzy Systems (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a kind of analysis methods based on semantics recognition, include the following steps: A) bullet cabinet information management system is logged in, background server obtains the user information of active user；B) background server sends Learning Scheme, study schedule, written historical materials, video data and notice information to active user by bullet cabinet information management system according to user information；C) background server carries out preliminary audit survey to active user or group's ability according to the study schedule of active user, then sets up audit meeting by bullet cabinet management group and carries out secondary audit；D secondary auditing result, bullet cabinet assembly situation and bullet cabinet industry big data) are subjected to comprehensive analysis, and adjust the way to manage of bullet cabinet based on the analysis results.Implement the analysis method of the invention based on semantics recognition, has the advantages that the development for being conducive to bullet cabinet management organization, development and the improvement direction that can preferably obtain bullet cabinet management organization, it being capable of quick adjustable strategies.
Description
Technical field
The present invention relates to semantics recognition field, in particular to a kind of analysis method based on semantics recognition.
Background technique
The system management platform of bullet cabinet is the part of an important composition in Intelligent bullet cabinet because for
Take and go back one of rifle examination & approval, the online real-time management of firearms and ammunition and to be on statistical form be all can be by this part
To realize.This is mainly by the control centre on backstage, the operation interfaces such as control executing agency, network communication and front end of identification
It is equal above to constitute.
Existing bullet cabinet management method has certain drawbacks when in use: (1) bullet cabinet management organization is difficult to institute
There is the ability of employee timely to be understood, profile can only be judged by various vouchers, due to the difference of profile, energy
Power sockdolager cannot timely reuse, and influence the reasonable utilization of human resources；(2) existing bullet cabinet management organization decision
It is all to be formulated by management level, but management level personnel cannot timely understand change of the market to product demand, it is this
There is very big unstability in management method, meanwhile, poor in timeliness, specific aim are weaker.
As definition in recent years and the industry division of labor are more fine, speech recognition is divided into speech recognition and semantics recognition two gradually
A offspring.Although voice and semantic only the change of one wordThe difference lies in a single word, but it is as far apart as heaven and earth.A simple analogy is played, speech recognition is suitable
In the ear of people, and semantics recognition is then brain, and speech recognition helps machine acquisition and output information, and semantics recognition is then pair
These information are processed.Semantics recognition is brain, and speech recognition helps machine acquisition and output information, and semantics recognition is then
These information are processed.The accuracy of semantics recognition is able to ascend by method for recognizing semantics, while can be more rapidly simple
The span from speech recognition to semantics recognition is realized promptly, shortens the process of semantics recognition, promotes the usage experience of user.So
And traditional technology is not also by semantics recognition technical application to bullet cabinet field.
Summary of the invention
The technical problem to be solved in the present invention is that in view of the above drawbacks of the prior art, providing one kind and being conducive to bullet
The development of cabinet management organization, development and the improvement direction that can preferably obtain bullet cabinet management organization, can quickly adjust plan
The analysis method based on semantics recognition slightly.
The technical solution adopted by the present invention to solve the technical problems is: constructing a kind of analysis side based on semantics recognition
Method includes the following steps:
A bullet cabinet information management system) is logged in, background server obtains the user information of active user；
B) background server is according to the user information, by the bullet cabinet information management system to active user
Send Learning Scheme, study schedule, written historical materials, video data and notice information；
C) background server tentatively examine to active user or group's ability according to the study schedule of active user
Then core sets up audit meeting by bullet cabinet management group and carries out secondary audit；
D) by secondary auditing result, bullet cabinet assembly situation and bullet cabinet industry big data progress comprehensive analysis, and according to
Analyze the way to manage of result adjustment bullet cabinet.
In the analysis method of the present invention based on semantics recognition, the step A) further comprise:
A1 the bullet cabinet information management system) is logged in, and inputs user's letter in the bullet cabinet information management system
Breath, and send bullet cabinet to the background server and assemble status inquiry application；
A2) background server receives the bullet cabinet and assembles status inquiry application, and bullet cabinet is inquired from database
Situation is assembled, and query result is sent to background server, the query result is sent to described by the background server
Bullet cabinet information management system is shown.
In the analysis method of the present invention based on semantics recognition, the user information includes job information, profession
Information and mission bit stream, into background server, understand bullet cabinet dress when the bullet cabinet assembles status inquiry application qualification
Underproof information is sent to active user when bullet cabinet assembly status inquiry application is unqualified with situation.
In the analysis method of the present invention based on semantics recognition, the background server is according to the personal energy of user
Force information, bullet library assembly information and bullet cabinet industry big data information comprehensive analysis send a variety of study sides to active user
Case.
In the analysis method of the present invention based on semantics recognition, the notice information includes voice messaging, text
Information and video information, the background server by semantics recognition and analysis, by the bullet cabinet information management system to
Active user sends the notice information after discriminance analysis.
In the analysis method of the present invention based on semantics recognition, the step C) further comprise:
C1) background server carries out learning training by the Learning Scheme, semantics recognition model is established, to bullet cabinet pipe
It manages relevant departments and issues video advice audit, carry out video audit；
C2) according to video auditing result, auditing result is sent to active user by the bullet cabinet information management system.
In the analysis method of the present invention based on semantics recognition, the bullet cabinet industry big data includes bullet cabinet
Enterprise management level decision data and bullet cabinet enterprise local decision making data.
In the analysis method of the present invention based on semantics recognition, the background server detection active user
Habit progress.
Implement the analysis method of the invention based on semantics recognition, has the advantages that due to logging in bullet cabinet letter
Management system is ceased, background server obtains the user information of active user；Background server passes through bullet cabinet according to user information
Information management system sends Learning Scheme, study schedule, written historical materials, video data and notice information to active user；From the background
Server carries out preliminary audit survey to active user or group's ability according to the study schedule of active user, then by bullet cabinet management
Group sets up audit meeting and carries out secondary audit；By secondary auditing result, bullet cabinet assembly situation and bullet cabinet industry big data
Comprehensive analysis is carried out, and adjusts the way to manage of bullet cabinet based on the analysis results；By by semantics recognition technical application to bullet
Cabinet field, the present invention be conducive to the development of bullet cabinet management organization, can preferably obtain the development of bullet cabinet management organization with
Improvement direction, being capable of quick adjustable strategies.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
It obtains other drawings based on these drawings.
Fig. 1 is that the present invention is based on the flow charts in analysis method one embodiment of semantics recognition；
Fig. 2 is that bullet cabinet information management system is logged in the embodiment, and background server obtains the user of active user
The specific flow chart of information；
Fig. 3 is for background server in the embodiment according to the study schedule of active user to active user or group's ability
Preliminary audit survey is carried out, the specific flow chart that audit meeting carries out secondary audit is then set up by bullet cabinet management group.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
In the analysis method embodiment the present invention is based on semantics recognition, it is somebody's turn to do the process of the analysis method based on semantics recognition
Figure is as shown in Figure 1.In Fig. 1, it is somebody's turn to do the analysis method based on semantics recognition and includes the following steps:
Step S01 logs in bullet cabinet information management system, and background server obtains the user information of active user: this step
In, by input account and password, bullet cabinet information management system is logged in, background server can be obtained according to the account of login
The user information of active user.The user information includes job information, specialized information and mission bit stream, when bullet cabinet assembles situation
When inquiry application is qualified, into background server, understands bullet cabinet and assemble situation, when bullet cabinet assembly status inquiry application does not conform to
When lattice, underproof information is sent to active user.
Above-mentioned bullet cabinet information management system is a software systems, is mounted on computer or mobile phone.The bullet cabinet information
Management system include it is interconnected get bullet unit, equipment give back unit, new storage unit, bullet assembly unit, library
Deposit dot element, gun dynamic cell, System Management Unit, security system administrative unit, statistical analysis unit, equipment management list
Member, video media unit and network management O&M unit.
Wherein, bullet unit is got for realizing receiving application, receive that examination & approval, equipment is predetermined and equipment is led with bullet
With；Equipment gives back unit and leads rifle people to carry out going back rifle by way of certification for making；New storage unit is for realizing newly-increased rifle
The storage of branch；Bullet assembly unit assembles for realizing gun, ammunition assembly and gun are removed stage makeup and costume；Stock-taking unit is for entering
The single-row surface and interface in library selects a storehouse in organisational directory column, all gun in selected storehouse can be seen in interface
With the quantity and assembly situation of ammunition；Gun dynamic cell is used to enter the single-row surface and interface in library, selects in organisational directory column
One storehouse can see the dynamic of all gun and last the case where using in selected storehouse at interface；System administration
Unit is for realizing user password modification, information department management, user management, operation log management, alarm log management and sets
Standby log management；Security system administrative unit is for realizing real-time video and alarm system management, and video recording query function；System
Meter analytical unit is for checking all kinds of registers；Device management unit is for realizing video equipment management, alarm host machine management, cloth
It withdraws a garrison management, entrance guard management and server admin；Video media unit is for realizing comprehensive inquiry, local hard disc media, video
Equipment media, centrally stored media and the inquiry of multichannel period；Network management O&M unit is for realizing alarm statistics, equipment fault
Inquiry and server state monitoring.
Step S02 background server is sent to active user by bullet cabinet information management system and is learned according to user information
Habit scheme, study schedule, written historical materials, video data and notice information: in this step, background server is according to the current of acquisition
The user information of user sends Learning Scheme, study schedule, text to active user by bullet cabinet information management system and provides
Material, video data and notice information.Wherein, background server can detecte the study schedule of active user.Notice information includes
Voice messaging, text information and video information, background server pass through bullet cabinet information management system by semantics recognition and analysis
The notice information united after active user's transmission discriminance analysis.
It is noted that background server assembles letter according to profile's information of user, bullet library in the present embodiment
Breath and bullet cabinet industry big data information comprehensive analysis send a variety of Learning Schemes to active user.
Step S03 background server tentatively examine to active user or group's ability according to the study schedule of active user
Then core sets up audit meeting by bullet cabinet management group and carries out secondary audit: in this step, background server is used according to current
The study schedule at family carries out preliminary audit survey to active user or group's ability, then sets up audit meeting by bullet cabinet management group
Carry out secondary examination.
Secondary auditing result, bullet cabinet assembly situation and bullet cabinet industry big data are carried out comprehensive analysis by step S04, and
The way to manage of bullet cabinet is adjusted based on the analysis results: in this step, by secondary auditing result, bullet cabinet assembly situation and bullet
Cabinet industry big data carries out comprehensive analysis, is analyzed as a result, simultaneously adjusting the way to manage of bullet cabinet based on the analysis results.It is worth
One is mentioned that, above-mentioned bullet cabinet industry big data includes bullet cabinet enterprise management level decision data and bullet cabinet enterprise local decision making
Data.
By the way that by semantics recognition technical application to bullet cabinet field, the analysis method of the invention based on semantics recognition is advantageous
In bullet cabinet management organization development, can preferably obtain development and the improvement direction of bullet cabinet management organization, can be quick
Adjustable strategies.
For the present embodiment, above-mentioned steps S01 can also be refined further, and the flow chart after refinement is as shown in Figure 2.
In Fig. 2, above-mentioned steps S01 further comprises following steps:
Step S11 logs in bullet cabinet information management system, and inputs user information in bullet cabinet information management system, and
Bullet cabinet is sent to background server and assembles status inquiry application: in this step, by input account and password, logging in bullet cabinet
Then information management system inputs user information in bullet cabinet information management system, and passes through bullet cabinet information management system
Bullet cabinet, which is sent, to background server assembles status inquiry application.
Step S12 background server receives bullet cabinet and assembles status inquiry application, and bullet cabinet assembly is inquired from database
Situation, and query result is sent to background server, query result is sent to bullet cabinet information management system by background server
System is shown: in this step, background server receives bullet cabinet assembly status inquiry application, inquires rifle from its database
It plays cabinet and assembles situation, and query result is returned to background server, background server sends query result by network
Bullet cabinet information management system is given, query result is shown by bullet cabinet information management system.S11 is to step through the above steps
S12 is realized and is logged in bullet cabinet information management system, and makes the user information of background server acquisition active user.
For the present embodiment, above-mentioned steps S03 can also be refined further, and the flow chart after refinement is as shown in Figure 3.
In Fig. 3, above-mentioned steps S03 further comprises following steps:
Step S31 background server carries out learning training by Learning Scheme, semantics recognition model is established, to bullet cabinet pipe
It manages relevant departments and issues video advice audit, carry out video audit: in this step, background server passes through Learning Scheme
Training is practised, to establish semantics recognition model, then video advice audit is issued to bullet cabinet management relevant departments, by bullet cabinet
It manages relevant departments and carries out video audit.
Semantics recognition model is a kind of identification model structure of typical artificial intelligence, has identification inference function and instruction
Practice the ability of study, and the semantics recognition model is different from traditional artificial intelligence model, mainly for knowledge-base design.
That is, in order to realize that the natural language to user's input identifies, it is necessary first to lead the different applications collected
The professional knowledge in domain is converted into the identification sentence for identifying reasoning, and forms semantics recognition model according to these identification sentences.
Basic submodel, sentence pattern relationship submodel, general submodel and semantic relation are included at least in above-mentioned semantics recognition model
Submodel.Above-mentioned semantic relation submodel includes relevant to basic submodel, sentence pattern relationship submodel and general submodel
Relationship and fuzzy semantics relationship, these relationships can for example be indicated with relationship number.
By establishing semantics recognition model, it is able to ascend the accuracy of semantics recognition, while can be more rapidly quickly and easily real
The now span from speech recognition to semantics recognition shortens the process of semantics recognition, promotes the usage experience of user.
Step S32 sends auditing result to active user according to video auditing result, by bullet cabinet information management system:
In this step, according to video auditing result, bullet cabinet information management system sends auditing result to active user.In other words, it uses
Family can see auditing result by bullet cabinet information management system.
The present invention is based on the analysis methods of semantics recognition with the continuous extension of audit time, bullet cabinet management organization problem
Quantity also constantly increase, the excessive development progress for influencing bullet cabinet management organization of problem accumulation, the present invention can be very good
Solve the problems, such as this.
In short, in the present embodiment, by the way that semantics recognition technical application to bullet cabinet field, and is established semantics recognition mould
Type, the analysis method of the invention based on semantics recognition are conducive to the development of bullet cabinet management organization, can preferably obtain rifle
The development of Dan Gui management organization and improvement direction, being capable of quick adjustable strategies.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Within mind and principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (8)
1. a kind of analysis method based on semantics recognition, which comprises the steps of:
A bullet cabinet information management system) is logged in, background server obtains the user information of active user；
B) background server is sent by the bullet cabinet information management system to active user according to the user information
Learning Scheme, study schedule, written historical materials, video data and notice information；
C) background server carries out preliminary audit survey to active user or group's ability according to the study schedule of active user, so
Audit meeting is set up by bullet cabinet management group afterwards and carries out secondary audit；
D secondary auditing result, bullet cabinet assembly situation and bullet cabinet industry big data) are subjected to comprehensive analysis, and according to analysis
As a result the way to manage of bullet cabinet is adjusted.
2. the analysis method according to claim 1 based on semantics recognition, which is characterized in that the step A) into one
Step includes:
A1 the bullet cabinet information management system) is logged in, and inputs user information in the bullet cabinet information management system, and
Bullet cabinet, which is sent, to the background server assembles status inquiry application；
A2) background server receives the bullet cabinet and assembles status inquiry application, and bullet cabinet assembly is inquired from database
Situation, and query result is sent to background server, the query result is sent to the bullet by the background server
Cabinet information management system is shown.
3. the analysis method according to claim 1 based on semantics recognition, which is characterized in that the user information includes duty
Position information, specialized information and mission bit stream, when the bullet cabinet assembles status inquiry application qualification, into background server,
Understand bullet cabinet and assemble situation, when bullet cabinet assembly status inquiry application is unqualified, is sent to active user unqualified
Information.
4. the analysis method according to claim 1 based on semantics recognition, which is characterized in that the background server according to
Profile's information, bullet library assembly information and the bullet cabinet industry big data information comprehensive analysis of user is sent out to active user
Send a variety of Learning Schemes.
5. the analysis method according to claim 1 based on semantics recognition, which is characterized in that the notice information includes language
Message breath, text information and video information, the background server pass through the bullet cabinet information by semantics recognition and analysis
Management system to active user send discriminance analysis after notice information.
6. according to claim 1 to described in 5 any one based on the analysis method of semantics recognition, which is characterized in that the step
Rapid C) further comprise:
C1) background server carries out learning training by the Learning Scheme, establishes semantics recognition model, manages phase to bullet cabinet
Pass department issues video advice audit, carries out video audit；
C2) according to video auditing result, auditing result is sent to active user by the bullet cabinet information management system.
7. according to claim 1 to described in 5 any one based on the analysis method of semantics recognition, which is characterized in that the rifle
Playing cabinet industry big data includes bullet cabinet enterprise management level decision data and bullet cabinet enterprise local decision making data.
8. according to claim 1 to described in 5 any one based on the analysis method of semantics recognition, which is characterized in that after described
The study schedule of platform server detection active user.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910702575.0A CN110489458A (en) | 2019-07-31 | 2019-07-31 | Analysis method based on semantics recognition |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910702575.0A CN110489458A (en) | 2019-07-31 | 2019-07-31 | Analysis method based on semantics recognition |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110489458A true CN110489458A (en) | 2019-11-22 |
Family
ID=68549141
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910702575.0A Pending CN110489458A (en) | 2019-07-31 | 2019-07-31 | Analysis method based on semantics recognition |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110489458A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102663567A (en) * | 2012-04-27 | 2012-09-12 | 江伟东 | Management system and method based on bullet cabinets |
| CN107657017A (en) * | 2017-09-26 | 2018-02-02 | 百度在线网络技术（北京）有限公司 | Method and apparatus for providing voice service |
| CN108563633A (en) * | 2018-03-29 | 2018-09-21 | 腾讯科技（深圳）有限公司 | A kind of method of speech processing and server |
| CN109726981A (en) * | 2018-12-12 | 2019-05-07 | 安徽讯呼信息科技有限公司 | A kind of enterprise management method with deep learning and semantics recognition and analysis |
-
2019
- 2019-07-31 CN CN201910702575.0A patent/CN110489458A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102663567A (en) * | 2012-04-27 | 2012-09-12 | 江伟东 | Management system and method based on bullet cabinets |
| CN107657017A (en) * | 2017-09-26 | 2018-02-02 | 百度在线网络技术（北京）有限公司 | Method and apparatus for providing voice service |
| CN108563633A (en) * | 2018-03-29 | 2018-09-21 | 腾讯科技（深圳）有限公司 | A kind of method of speech processing and server |
| CN109726981A (en) * | 2018-12-12 | 2019-05-07 | 安徽讯呼信息科技有限公司 | A kind of enterprise management method with deep learning and semantics recognition and analysis |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107330706A (en) | A kind of electricity battalion's customer service system and commercial operation pattern based on artificial intelligence | |
| Beierle et al. | Values, conflict, and trust in participatory environmental planning | |
| CN104809933B (en) | A kind of power grid is without script emergency drilling system, drilling method and equipment | |
| CN110210762A (en) | A kind of employee performance dynamic wire examination method based on big data analysis | |
| CN113468296B (en) | Model self-iteration type intelligent customer service quality inspection system and method capable of configuring business logic | |
| Omrane et al. | Entrepreneurial competencies and entrepreneurial process: a dynamic approach | |
| Prebble et al. | Applying multiple perspectives to the design of a commercialization process | |
| CN114186983B (en) | Video interview multidimensional scoring method, system, computer equipment and storage medium | |
| CN110880077A (en) | Enterprise intelligent consultation cloud platform | |
| CN106847310A (en) | A kind of sentiment analysis system based on speech recognition | |
| CN109840705A (en) | A kind of electric power field work personnel smart allocation application method | |
| Ilori et al. | Technology decision making in organisations | |
| CN110489458A (en) | Analysis method based on semantics recognition | |
| Aravopoulou et al. | Strategic decision-making process (SDMP) in times of crisis: Evidence from Greek banks | |
| Martin et al. | Do HRD investment strategies pay? Exploring the relationship between lifelong learning and psychological contracts | |
| Ritchie-Dunham | Informing mental models for strategic decision making with ERPs and the balanced scorecard: A simulation–based experiment | |
| da Cunha et al. | Towards a substantive theory of decision-making in software project management: Preliminary findings from a qualitative study | |
| CN109658148A (en) | A kind of marketing activity complaint risk prediction technique based on natural language processing technique | |
| Tandiono et al. | Analysis of a Country Readiness in Adopting Continuous Auditing Technology-The Case of Indonesia | |
| Baradari | Develop the strategic outsourcing with consideration of core competency criteria independence | |
| Leonhardsen et al. | The process of integrating risk management: usefulness, standardisation and adaptation | |
| Onugha et al. | Planned change and organizational effectiveness, the moderating role of organizational culture | |
| Nicolò | Metaproject analysis: multiagent virtual project networks for strategic decisions in preplanning | |
| Wibawa et al. | Business process analysis of cloud INCIDENT management service with activity assignment: A case of PT. XYZ | |
| Liche et al. | A fuzzy cognitive maps approach for analyzing the integration of two organizations of the same corporation |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20191122 |
|
| RJ01 | Rejection of invention patent application after publication |