CN109102111A - A method of measurement director cooperates possibility with performer - Google Patents
A method of measurement director cooperates possibility with performer Download PDFInfo
- Publication number
- CN109102111A CN109102111A CN201810835050.XA CN201810835050A CN109102111A CN 109102111 A CN109102111 A CN 109102111A CN 201810835050 A CN201810835050 A CN 201810835050A CN 109102111 A CN109102111 A CN 109102111A
- Authority
- CN
- China
- Prior art keywords
- director
- performer
- path
- node
- optimal path
- 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
- 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
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Economics (AREA)
- General Physics & Mathematics (AREA)
- Development Economics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Game Theory and Decision Science (AREA)
- General Engineering & Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The method for cooperating possibility with performer is directed the invention discloses a kind of measurement, which comprises the following steps: step 1: according to director and cooperative relationship between performer, performer and performer and cooperation number, building director's Actor Collaboration Network network figure;Step 2: similarity matrix between director, the similarity between acquiring each director with formula are established, and establishes similarity matrix;Step 3: it determines and whether there is optimal path between director and performer, the process for finding optimal path is: searching out performer aiWith director djBetween All Paths, then select the shortest path in these paths, weight and maximum path, as optimal path on path selected in set of minimal paths;Step 4: the cooperation degree between director and performer is calculated;From network structure and director, two aspect of performer's oneself factor, the limitation that conventional method passes through merely cooperation possibility between the box office measurement director performer for cooperating film is breached.
Description
Technical field
It a kind of is led the present invention relates to data mining technology field more particularly to based on director and the measurement of Actor Collaboration Network network
Drill the method for cooperating possibility between performer.
Background technique
It is mostly at present the network constituted based on similar node, and research method or list for the research of film social networks
Purely from network structure feature, or excessive user mutual behavior feature is considered, causes method in practical applications
It is difficult to carry out.Method for cooperating uncertain proposition between director and performer is all based on the cooperation box office between director performer, but drills
Member is difficult accurately to measure to the box office contribution of film, and the director performer established on this basis cooperates uncertain proposition method very
Therefore inaccuracy solves the problems, such as this kind of be particularly important.
Summary of the invention
In view of the deficiencies of the prior art, the method for cooperating possibility with performer is directed the present invention provides a kind of measurement, from
It sets out and in terms of network structure and director, performer's oneself factor two, breach the box office that conventional method passes through merely cooperation film
Cooperate the limitation of possibility between measurement director performer.
To solve the above-mentioned problems, the method for cooperating possibility with performer is directed the present invention provides a kind of measurement, it is special
Sign is, comprising the following steps:
Step 1: according to cooperative relationship between director and performer, performer and performer and cooperation number, building director performer is closed
Make network;
Step 2: similarity matrix between director is established
Use formulaThe similarity between each director is acquired, and establishes similarity matrix;
Step 3: it determines and whether there is optimal path between director and performer
The process for finding optimal path is: searching out performer aiWith director djBetween All Paths, then select these
Shortest path in path selects weight and maximum path, as optimal path on path, if depositing in set of minimal paths
In a plurality of optimal path, then optional one is as optimal path;
Step 4: the cooperation degree between director and performer is calculated
The cooperation degree between director and performer is calculated according to the judgement result of step 3, if actor node aiWith director's node
djBetween there are optimal paths, and on the path direct node there was only dj, then a is first acquirediAnd djBetween optimal path length l=len
(pk), then utilize formulaCalculate performer aiWith director dj's
Cooperation degree index Condeg (ai,dj).If performer aiWith director djBetween there is no deposit on optimal path or optimal path
In director node djDirector's node in addition is then successively traversed according to similarity size and director djSimilar director, until traversal
To director's node dm, with performer aiThere are only include director node d on optimal path and respective pathsm, then utilize
FormulaDirector d is calculatedmWith performer aiCooperation degree
condeg(ai,dm), finally utilize condeg (ai,dj)=sim (dj,dm)*condeg(ai,dm) acquire aiAnd djCooperation
Degree.
Further improvement lies in that: director, performer are abstracted as two distinct types of network node, director and performer, performer
Cooperative relationship between performer is abstracted as two distinct types of nonoriented edge, and the cooperation number between corresponding personnel is abstracted as on side
Weight, performer's set A is defined as { a1,a2,...,ai,...,an, aiI-th bit performer in set is represented, n represents set
The number of middle performer, director set D are defined as { d1,d2,d3...,dj,...dm, djRepresent j-th of director, m in director's set
Represent the number directed in set.Film types set T is defined as { t1,t2,t3,...,tk,...,tu, tkRepresent film class
Kth seed type in type set, u represent the kind number of film types in set.Performer aiWith ajBetween weight w (ai,aj) table
Show, performer aiWith director djBetween weight w (ai,dj) indicate, director-Actor Collaboration Network network is established accordingly.
Path: arbitrary node v is definediTo node vjPath be from viTo vjSequence " the v on the vertex and side passed throughi<
vi,vk> vk…vs< vl,vj> vj" wherein vi, vs,vk, vjEtc. being node viTo node vjAll nodes passed through.Two nodes
viAnd vjBetween side sequence idol < vi,vj> is indicated.As shown in Figure 1, node d0To node a2A paths be d0< d0,a1>
a1< a1,a2> a2.There may be mulitpath between two nodes, node d as shown in figure 10To a2Between there are three paths: d0<
d0,a1> a1< a1,a2> a2、d0< d0,a3> a3< a3,a2> a2And d0< d0,a4> a4< a4,a5> a5< a5,a2> a2。
Path length: it is defined as the sum of undirected number of edges in path, as shown in figure 1 node d0To a2A paths d0< d0,a1
> a1< a1,a2> a2There are 2 sides, i.e. < d0,a1>, < a1,a2>, therefore node d0To a2The paths length be 2.
Shortest path: two node v are definediAnd vjBetween path set pathi,jFor { p1,p2,p3…pk…,pz, wherein
Z represents node viAnd vjBetween path item number, pkIndicate viAnd vjBetween kth paths.Path pkPath length be denoted as len
(pk).There are a paths prSo that for arbitrary path pkThere is len (pr) <=len (pk), wherein pr,pk∈
pathi,j, claim path prFor node viAnd vjBetween shortest path, there may be a plurality of shortest paths between two nodes, as shown in figure 1
Node a0To a2Between there are three paths: d0< d0,a1> a1< a1,a2> a2、d0< d0,a3> a3< a3,a2> a2And d0
< d0,a4> a4< a4,a5> a5< a5,a2> a2, it is denoted as p respectively1、p2And p3, len (p1)=len (p2< len (the p of)=23)
=3, therefore p1And p2It is all node d0And a2Between shortest path.Definition node viAnd vjBetween set of minimal paths path_
shortijFor { pr|pr∈pathi,j,len(pr)=min { len (pl),len(p2),...,len(pz), wherein z represents vi
And vjBetween path item number, pathi,jRepresent node viAnd vjBetween path set.
Optimal path: defining the maximum path of average weight in point-to-point transmission shortest path is optimal path.Define any road
Diameter pkAverage weight w_ave (pk) be the paths on all weights sum and number of edges quotient, i.e.,Wherein len (pk) it is path pkLength l, riRepresent performerThe serial number in performer's set A.Such as Fig. 1, node d0And a2Between shortest path p1With path p2Path length be all 2,
Path p1Average weight isPath p2Average weight isNode d0And a2Between optimal path be p1.Definition
Node viTo vjOptimal path set path_bestijFor { pq|pq∈path_shortij,w_ave(pq)=max { w_ave
(p1),w_ave_(p2),…,w_ave(pt), wherein t represents node viAnd vjBetween shortest path item number, path_
shortijRepresent node viAnd vjBetween shortest path set.
Similarity between director: definition director djFeature vector be vector_dj(movie_num,t1_num,t2_num,
Award1_num, award2_num), movie_num represents director djWhole film quantity of shooting, t1_num、t2_ num difference
Represent director djShoot t1、t2The number of type movie accounts for the ratio of its captured whole film, and award1_num indicates director dj
The number of foreign films awards is obtained, external awards include U.S.'s Oscar Golden Statuettes, Golden Ball Award, the gold of cannes of france film festival
Palm prize, the Golden Bear Award and the Gold Lion award of Venice, Italy film festival of Berlin, Germany film festival.Award2_num expression is led
Drill djThe number of internal film awards is obtained, internal film awards include the Golden Rooster awards in continent, the Oscar Award in Hong Kong and China
The Golden Horse Prize in Taiwan.
Performer aiWith director djCooperation degree is Condeg (ai,dj), cooperate possibility between director and performer for measuring.
If performer aiAnd djBetween there are optimal path pq, and path pqUpper only includes director's node dj, then aiAnd djCooperation
It is as follows to spend calculation formula:
In formula (1), riRepresent performerOrder in performer's set A, i represent performerIn optimal path pqOn
Order,Represent optimal path pqUpper i-th of performer.L represents optimal path pqPath length.Such as Fig. 2, a2To d1Most
Good path is a2< a2,a5> a5< a5,d1> d1< d1,a2> a2< a2,a5> a5It can be expressed as on this pathsThe the 1st, 2,3 node on the paths is represented, wherein r1、r2Corresponding performer a2And a5It is corresponding in performer's set A
Subscript 2 and 5.a2To d1Optimal path on only director node d1, therefore a can be calculated with formula (1)2And d1Between conjunction
Degree of work.
If performer aiWith director djBetween there is no optimal path or optimal path include djOther directors section in addition
Point, then aiAnd djCooperation degree calculation formula it is as follows:
Condeg(ai,dj)=sim (dj,dm)*condeg(ai,dm) (2)
Sim (the d in formula (2)j,dm) represent director djWith director dmBetween similarity.dmRepresenting has road with performer ai
Diameter up to and with director djThe maximum director of similarity.Wherein sim (dj,dm) calculating formula of similarity are as follows:|dj.dm| represent director djAnd dmThe absolute value of vector product, | dj|、|dm| represent director dj、dmIt is special
Levy absolute value of a vector.In the following figure: a3To d2Optimal path be a3< a3,d1> d1< d1,a5> a5< a5,d2> d2, but
It is this optimal path in addition to directing node d2It outside further include director node d1, therefore a can be calculated with formula (2)3And d2Between
Cooperation degree.
The beneficial effects of the present invention are: measurement director of the invention cooperates possibility method with performer, from network structure with
It sets out in terms of director, performer's oneself factor two, breaches the box office measurement director performer that conventional method passes through merely cooperation film
Between cooperate possibility limitation;For cooperating the measurement of possibility between the director performer that had not cooperated, this patent method is same
It is applicable in;Algorithm in this patent calculates simplicity, and the time complexity of algorithm can excavate cooperation possibility close to linearly quickly
Big director performer combination, present invention can apply to movie director performer Team, film investment decision, film investment risks
Control, products propaganda popularization etc..
Detailed description of the invention
Fig. 1 is director and Actor Collaboration Network network schematic diagram of the invention.
Fig. 2 is similarity matrix format between present invention director.
Fig. 3 is present invention director and Actor Collaboration Network network figure.
Fig. 4 is director and Actor Collaboration Network network Local map in Fig. 3.
Fig. 5 is director and performer's similarity matrix.
Fig. 6 is director and performer's cooperation degree.
Specific embodiment
In order to deepen the understanding of the present invention, the present invention is further described below in conjunction with embodiment, the present embodiment
For explaining only the invention, it is not intended to limit the scope of the present invention..
The present embodiment is related to 800 films of 2014-2016, passes through the processing to film, director, cast's data
It gets between director and performer, cooperative relationship and cooperation number, the cooperative relationship got share 91976 between performer and performer
Item, and the cinematographic work quantity information, winning information, the quantity information for shooting all types of films of director are related to according to above-mentioned film
The similarity between each director is calculated.
The A of performer's set described in the present embodiment is defined as { a1,a2,...,ai,...,an, aiI-th bit in set is represented to drill
Member, n represent the number of performer in set, and director set D is defined as { d1,d2,d3...,dj,...dm, djRepresent director's set
In j-th of director, m represents the number directed in set.Film types set T is defined as { t1,t2,t3,...,tk,...,tu,
tkKth seed type in film types set is represented, u represents the kind number of film types in set.Performer aiWith ajBetween weight use
w(ai,aj) indicate, performer aiWith director djBetween weight w (ai,dj) indicate, director-Actor Collaboration Network network is established accordingly,
As shown in Figure 1.
Present embodiment discloses the method for cooperating possibility with performer is directed the present invention provides a kind of measurement, feature exists
In, comprising the following steps:
Step 1: according to cooperative relationship between director and performer, performer and performer and cooperation number, building director performer is closed
Make network, as shown in Figure 3,4, this patent method calculating process explanation is carried out by taking Fig. 3 as an example;
Step 2: similarity matrix formula between director is establishedAcquire the phase between each director
Like degree, and similarity matrix is established, similarity is as shown in Figure 5 between each director;
Step 3: it determines and whether there is optimal path between director and performer
To direct d1With performer a20For, search out performer a20With director d1Between All Paths, then select this
Set of minimal paths in a little paths is { a20< a20,a11> a11< a11,a4> a41< a4,d1> d1}.In shortest path collection
It is a that weight and maximum path on path are selected in conjunction20< a20,a11> a11< a11,a4> a41< a4,d1> d1, as most
Good path.A plurality of optimal path if it exists, then optional one is as optimal path.It is gone to determine that other are led with same method
It drills between performer with the presence or absence of optimal path;
Step 4: the cooperation degree between director and performer is calculated
The cooperation degree between director and performer is calculated according to the judgement result of step 3.To direct d1、 d2With performer a20Between
For cooperation degree calculates.A as can be seen from Figure 420To d1Between optimal path pqFor a20< a20,a11> a11< a11,a4> a4
< a4,d1> d1, respective paths length l is 3,Performer a20With director d1Cooperation degreePerformer a13With director d2Between existing path all have passed through
Except d2Outer other nodes, therefore a13With director d2Between there is no only comprising director node d2Optimal path, such as a13< a13,d1
> d1< d1,a5> a5< a5,d2> d2In addition to d in path2It is outer that there are also director node d1。a13With d1Between there are optimal path a13
< a13,d1> d1And with a13Have in director's node of optimal path, d1With d2Similarity it is maximum, therefore can use d1
And a13Between cooperation degree and d1And d2Between pixel i.e. spread out of a13And d2Between cooperation degree, specific formula be condeg
(d2,a13)=sim (d1,d2).condeg(a13,d1)=1*0.78=0.78.All directors and performer are acquired with same method
Between cooperation degree, as shown in Figure 6.
The principle of the invention be director with the cooperation number of certain performer illustrate direct this performer is more approved;Director
It is shorter that the path contacted is generated between performer, director and performer are more easy to produce cooperation;Therefore, internuncial pathway between director and performer
It is higher to cooperate number on shorter, path between each node, then it is bigger to cooperate possibility between director and performer.Two director's similarities are got over
Greatly, then they to cooperate possibility for same performer more similar.
Measurement director of the invention cooperates possibility method with performer, from network structure and director, performer's oneself factor two
Aspect is set out, and the limitation that conventional method passes through merely cooperation possibility between the box office measurement director performer for cooperating film is breached;
For cooperating the measurement of possibility between the director performer that had not cooperated, this patent method is equally applicable;Algorithm in this patent
Simplicity is calculated, the time complexity of algorithm close to that linearly, can excavate the big director performer combination of cooperation possibility quickly, originally
Invention can be applied to movie director performer Team, film investment decision, the control of film investment risk, products propaganda popularization etc.
Aspect.
Claims (2)
1. a kind of method that measurement director cooperates possibility with performer, which comprises the following steps:
Step 1: according to cooperative relationship between director and performer, performer and performer and cooperation number, building director's Actor Collaboration Network
Network figure;
Step 2: similarity matrix between director is established
Use formulaThe similarity between each director is acquired, and establishes similarity matrix.
Step 3: it determines and whether there is optimal path between director and performer
The process for finding optimal path is: searching out performer aiWith director djBetween All Paths, then select these paths
In shortest path, weight and maximum path, as optimal path on path are selected in set of minimal paths, it is more if it exists
Optimal path, then optional one is as optimal path;
Step 4: the cooperation degree between director and performer is calculated
The cooperation degree between director and performer is calculated according to the judgement result of step 3, if actor node aiWith director node djBetween
There are optimal paths, and direct node on the path and there was only dj, then a is first acquirediAnd djBetween optimal path length l=len
(pk), then utilize formulaCalculate performer aiWith director dj's
Cooperation degree index Condeg (ai,dj).If performer aiWith director djBetween there is no deposit on optimal path or optimal path
In director node djDirector's node in addition is then successively traversed according to similarity size and director djSimilar director, until traversal
To director's node dm, with performer aiThere are only include director node d on optimal path and respective pathsm, then utilize
FormulaDirector d is calculatedmWith performer aiCooperation degree
condeg(ai,dm), finally utilize condeg (ai,dj)=sim (dj,dm)*condeg(ai,dm) acquire aiAnd djCooperation degree.
2. the method that a kind of measurement director as described in claim 1 cooperates possibility with performer, it is characterised in that: the performer
Set A is defined as { a1,a2,...,ai,...,an, aiI-th bit performer in set is represented, n represents the number of performer in set, leads
It drills set D and is defined as { d1,d2,d3...,dj,...dm, djJ-th of director in director's set is represented, is directed in m representative set
Number.Film types set T is defined as { t1,t2,t3,...,tk,...,tu, tkKth seed type in film types set is represented,
U represents the kind number of film types in set.Performer aiWith ajBetween weight w (ai,aj) indicate, performer aiWith director djBetween
Weight w (ai,dj) indicate, director-Actor Collaboration Network network is established accordingly.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810835050.XA CN109102111A (en) | 2018-07-26 | 2018-07-26 | A method of measurement director cooperates possibility with performer |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810835050.XA CN109102111A (en) | 2018-07-26 | 2018-07-26 | A method of measurement director cooperates possibility with performer |
Publications (1)
Publication Number | Publication Date |
---|---|
CN109102111A true CN109102111A (en) | 2018-12-28 |
Family
ID=64847755
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201810835050.XA Pending CN109102111A (en) | 2018-07-26 | 2018-07-26 | A method of measurement director cooperates possibility with performer |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109102111A (en) |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101930462A (en) * | 2010-08-20 | 2010-12-29 | 华中科技大学 | Comprehensive body similarity detection method |
CN102195899A (en) * | 2011-05-30 | 2011-09-21 | 中国人民解放军总参谋部第五十四研究所 | Method and system for information mining of communication network |
CN104102745A (en) * | 2014-07-31 | 2014-10-15 | 上海交通大学 | Complex network community mining method based on local minimum edges |
US8988611B1 (en) * | 2012-12-20 | 2015-03-24 | Kevin Terry | Private movie production system and method |
CN106354862A (en) * | 2016-09-06 | 2017-01-25 | 山东大学 | Multidimensional individualized recommendation method in heterogeneous network |
-
2018
- 2018-07-26 CN CN201810835050.XA patent/CN109102111A/en active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101930462A (en) * | 2010-08-20 | 2010-12-29 | 华中科技大学 | Comprehensive body similarity detection method |
CN102195899A (en) * | 2011-05-30 | 2011-09-21 | 中国人民解放军总参谋部第五十四研究所 | Method and system for information mining of communication network |
US8988611B1 (en) * | 2012-12-20 | 2015-03-24 | Kevin Terry | Private movie production system and method |
CN104102745A (en) * | 2014-07-31 | 2014-10-15 | 上海交通大学 | Complex network community mining method based on local minimum edges |
CN106354862A (en) * | 2016-09-06 | 2017-01-25 | 山东大学 | Multidimensional individualized recommendation method in heterogeneous network |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Zhou et al. | Semantic understanding of scenes through the ade20k dataset | |
Li et al. | Estimating building age from Google street view images using deep learning (short paper) | |
CN109685121A (en) | Training method, image search method, the computer equipment of image encrypting algorithm | |
CN103955535A (en) | Individualized recommending method and system based on element path | |
CN113255895B (en) | Structure diagram alignment method and multi-diagram joint data mining method based on diagram neural network representation learning | |
CN103064903A (en) | Method and device for searching images | |
Zhang et al. | Hybrid federated learning: Algorithms and implementation | |
CN103399900B (en) | Picture recommendation method based on location-based service | |
CN105184321B (en) | Data processing method and device for ftrl model | |
CN110209858A (en) | Exhibiting pictures determination, object search, methods of exhibiting, device, equipment and medium | |
CN105787464A (en) | A viewpoint calibration method of a large number of pictures in a three-dimensional scene | |
CN105138636B (en) | Graph construction method and device for entity relationship | |
CN105069003B (en) | A kind of user's perpetual object based on forwarding chain similarity recommends computational methods | |
CN109102111A (en) | A method of measurement director cooperates possibility with performer | |
CN108304588A (en) | A kind of image search method and system based on k neighbours and Fuzzy Pattern Recognition | |
CN104866818B (en) | A kind of method and apparatus for searching for the picture comprising face | |
Farhat et al. | Intelligent portrait composition assistance: Integrating deep-learned models and photography idea retrieval | |
Seo et al. | A photomosaic image generation method using photo annotation in a social network environment | |
Guo et al. | Conditional feature coupling network for multi-persons clothing parsing | |
CN104796478B (en) | A kind of resource recommendation method and device | |
CN112612965A (en) | Material recommendation method and system based on map label noise reduction | |
Nathan et al. | LightNet: deep learning based illumination estimation from virtual images | |
Mohamed et al. | Geolocation of cultural heritage using multi-view knowledge graph embedding | |
Bres et al. | Localisation and augmented reality for mobile applications in culture heritage | |
Wang et al. | [Retracted] Aided Evaluation of Motion Action Based on Attitude Recognition |
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 | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181228 |