CN115080706A - Method and system for constructing enterprise relationship map - Google Patents
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Abstract
The invention provides a method and a system for constructing an enterprise relationship map, which are used for acquiring an enterprise relationship map of an enterprise to be queried, constructing an enterprise relationship matrix according to an enterprise name and an enterprise relationship in the enterprise relationship map, generating a deepened application matrix according to the enterprise relationship matrix, updating the enterprise relationship map according to the deepened application matrix and outputting the enterprise relationship map. The method can improve the accuracy of the enterprise relationship maps, fully reflect the association degree among enterprises, reinforce the weight value of enterprise information change in the construction process, effectively analyze the invisible relationship among the enterprises by coordinating the association of all the enterprises in the maps, correct and optimize the enterprise relationship maps in the database, and effectively help to analyze the enterprise risk propagation paths and the operation activities of the enterprises.
Description
Technical Field
The invention relates to the technical field of knowledge maps, in particular to a construction method of an enterprise relation map.
Background
The enterprise relationship map is helpful for people to examine the composition structure and the associated information among enterprises. At present, the mainstream enterprise relationship spectrogram construction method is mainly to draw an enterprise relationship spectrogram which is convenient and visual to display in a logic association mode by using data analysis methods such as data mining and pattern matching. However, the relationship between enterprises is often complicated, the position information and employee composition of the enterprises can change, new business comes and goes between large and small enterprises, meanwhile, implicit association can exist between different enterprises, and under the change of various information, the enterprise relationship map can have the phenomenon of inaccurate and incomplete information association.
In the invention patent of china with the prior art patent application number of 201810685605.7, an enterprise data knowledge table is constructed, a knowledge template related table is constructed, and a knowledge template ID field is established in the enterprise data knowledge table to realize the one-to-many relationship between the knowledge template and the enterprise data knowledge; constructing a knowledge master tree diagram, and establishing an ID field of the knowledge master tree diagram in a knowledge template table to realize the one-to-many relationship between the master tree diagram and the knowledge template; and constructing a knowledge logic tree diagram, establishing a knowledge logic tree diagram and an enterprise data knowledge relation table in the knowledge logic tree diagram, and storing an ID field of the knowledge logic tree diagram and an ID field of enterprise data knowledge to realize the many-to-many relation between nodes of the knowledge logic tree diagram and the enterprise data knowledge.
Disclosure of Invention
The invention aims to provide a construction method of an enterprise relationship map, which is used for solving one or more technical problems in the prior art and at least providing a beneficial selection or creation condition.
The invention provides a method and a system for constructing an enterprise relation atlas, which are used for acquiring an enterprise relation atlas of an enterprise to be inquired, constructing an enterprise relation matrix according to an enterprise name and an enterprise relation in the enterprise relation atlas, generating a deepened application matrix according to the enterprise relation matrix, updating the enterprise relation atlas according to the deepened application matrix and outputting the enterprise relation atlas. The method can improve the accuracy of the enterprise relation map, fully reflect the association degree among enterprises, reinforce the weight value of enterprise information change in the construction process, effectively analyze the invisible relationship among the enterprises by coordinating the association of all the enterprises in the map, and effectively help to analyze the enterprise risk propagation path and the enterprise operation activities.
In order to achieve the above object, according to an aspect of the present invention, there is provided a method for constructing an enterprise relationship graph, the method including the steps of:
s100, acquiring an enterprise relation map of an enterprise to be queried;
s200, constructing an enterprise relation matrix according to the enterprise names and the enterprise relations in the enterprise relation map;
s300, generating a deepened application matrix according to the enterprise relation matrix;
s400, updating the enterprise relation map according to the deepened application matrix, and outputting the updated enterprise relation map;
the enterprise relationship graph comprises at least two enterprises, each enterprise comprises a plurality of employees, each employee holds a mobile device and is used for obtaining positioning information of the employee, and the positioning information comprises longitude and latitude coordinates.
Preferably, in step S100, the enterprise relationship graph of the enterprise to be queried is obtained, and the specific method is as follows: the enterprise relation map of the enterprise to be inquired is obtained through an enterprise relation map generating method in a patent with the patent number of CN107229756A, or the enterprise relation map of the enterprise to be inquired in a database of an enterprise inquiry website is obtained.
Further, in step S200, an enterprise relationship matrix is constructed according to the enterprise names and the enterprise relationships in the enterprise relationship map, and the specific steps are as follows: screening all enterprises from an enterprise relation map, recording the number of all enterprises as N, numbering all enterprises in sequence by using N numbers 1,2, …, N to obtain enterprise numbering relation, creating an all-zero matrix R with N rows and N columns, setting an integer variable i =1, and recording the value range of i as [1, N ];
and traversing i in sequence, in the enterprise relationship graph, recording the numbers R1, R2, … and rn of all enterprises which have connection relationship with the enterprise with the number i, setting integer variables j, recording the values of j as R1, R2, … and rn in sequence, traversing j in sequence, updating the element of the ith row and the jth column in the matrix R as 1, recording R1 as a transposed matrix of R, updating R as R + R1, and recording the matrix R as an enterprise relationship matrix.
Further, in step S300, a deepened application matrix is generated according to the enterprise relationship matrix, and the specific method includes: the enterprise with the most employees is E, and all enterprises in E are recordedThe number of the employees is st, the longitude and latitude coordinates of the mobile equipment of each employee in the step E are obtained, an array lal is built by taking the longitude and latitude coordinates of the mobile equipment of each employee in the step E as a row (the array lal is a two-dimensional array, the st row is 2 columns, the 1 st column is the longitude coordinate of the mobile equipment of each employee, the 2 nd column is the latitude coordinate of the mobile equipment of each employee), and the notation lal is i1j1 The longitude and latitude coordinates of the enterprise position of E are (eg, et) for the elements in line i1 and column j1 in the two-dimensional array lal, and the enterprise pivot value of E is calculated by the following formula
(the enterprise pivot measuring value is used as an index for judging whether the association state of the enterprise is abnormal or not according to the unknown change trend of the employee); i1 is the serial number of the row in the array lal, and j1 is the serial number of the column in the array lal;
acquiring longitude and latitude coordinates of each enterprise, sequentially constructing an array cc (the array cc is a two-dimensional array, and is N rows and 2 columns) by taking the longitude and latitude coordinates of each enterprise as one row according to the ascending sequence of enterprise numbers, sequentially constructing an array mdc (the array mdc is a two-dimensional array, and is N rows and 2 columns) by taking the average value of the longitude and latitude coordinates of the mobile devices of all employees in each enterprise as one row, and recording the cc i2j2 Is the element in the i2 th row and the j2 th column in the array cc, and is denoted mdc i3j3 For the element in row i3, column j3 in the array mdc, i2, j2=1,2, …, N, i3, j3=1,2, …, N, the integer variable p =1, p ∈ [1, N]P is traversed in turn, storing the values of all p that satisfy condition con1 and satisfy condition con2 in array esc,
wherein the condition con1 indicates that the enterprise pivot measurement value of the corresponding enterprise of the pth element in the group cc is less than or equal to cpp, or the condition con1 indicates that the enterprise pivot measurement value of the current enterprise is less than or equal to ccGV, and the condition con2 indicates mdc p1 ∈[cc p1 -K1, cc p1 +K1]And mdc p2 ∈[cc p2 -K2, cc p2 +K2](ii) a ccGV is the average of the enterprise pivot measurements of each enterprise in array cc; k1 is the difference between KT1 and KST 1; k2 is the difference between KT2 and KST 2; KT1 is the average value of each element in the 1 st column in the array lal, and KST1 is the 1 st column of the array mdc corresponding to the current enterpriseAverage value of each element; KT2 is the average value of each element in the 2 nd column of the array lal, and KST2 is the average value of each element in the 2 nd column of the array mdc corresponding to the current enterprise;
alternatively, where condition con1 refers to mdc p1 ∈[int1,int2]Condition con2 refers to mdc p2 ∈[int3,int4]Int1 has a value cc p1 The value of-cpp, int2 is cc p1 The value of + cpp, int3 is cc p2 The value of-cpp, int4 is cc p2 + cpp; note esc i4 Traversing the value range of i4 for the i4 th element in the array esc (the value range of i4 is determined by the number of p meeting the condition), and sequentially adding esc th element in the enterprise relation matrix R i4 All elements of a row and esc th i4 All elements of the column are updated to 0, and the matrix R is taken as the deepening application matrix DA.
The beneficial effect of this step does: the method has the advantages that blank enterprises can exist in the enterprise map, so that the connection relation of the enterprise map is inaccurate, the blank enterprises can be filtered by the method of calculating the center measured value of the enterprise through the coordinates of the mobile equipment, the center measured value of the enterprise is calculated through the number of staff and position information of the enterprise, whether the enterprise normally operates or not is judged, the matrix R is updated according to the judgment result, the connection relation of each enterprise can be better reflected in the construction process of the enterprise relation map, and the accuracy of the enterprise map is improved.
The enterprise pivot measuring value of the current enterprise (the same as the enterprise pivot measuring value E of the enterprise with the most number of staff) is calculated by the following steps:
the number of all employees in the current enterprise EQ is recorded as st1, the longitude and latitude coordinates of the mobile equipment of each employee in the current enterprise EQ are obtained, an array lalC is constructed by taking the longitude and latitude coordinates of the mobile equipment of each employee in the current enterprise EQ as a row (the array lalC is a two-dimensional array, st1 rows and 2 columns are total, the 1 st column is the longitude coordinate of the mobile equipment of each employee, and the 2 nd column is the latitude coordinate of the mobile equipment of each employee), and the lalC is recorded i1j1 Recording longitude and latitude coordinates of the enterprise position of the current enterprise EQ as (EQgC, EQtC) for the elements in the ith 1 th row and the j1 th column in the two-dimensional array lalC, and calculating the enterprise pivot measuring value of the current enterprise EQ according to the following formula:
。
because the association degrees among enterprises are different, some enterprises have invisible cooperative relationships (namely, the enterprises do not have connection relationships in the enterprise graph), the accuracy of the enterprise relationship graph is influenced, and in order to solve the problem and further improve the available reference value of the enterprise relationship graph, the invention provides a method for improving the matrix DA preferentially, which comprises the following steps:
preferably, the deepening application matrix DA further needs to be optimized by the following steps:
s301, recording the regression measure erd = [ ln (| cpp/(1-cpp) |)]Wherein, the]Is expressed as rounding up, [ ln (| cpp/(1-cpp) |)]Represents rounding up ln (| cpp/(1-cpp) |), and | cpp/(1-cpp) | represents the absolute value of cpp/(1-cpp), and sets the integer variable i, i ∈ [1, N |)]Traversing i in the value range of i, and sequentially (cc) in the coordinate system i1 ,cc i2 ) Constructing N circles C by taking erd as radiuses and taking the circle center as the center 1 ,C 2 ,…,C N Recording longitude and latitude coordinates of mobile equipment of all employees in all enterprises as coordinates to be processed, and marking the mobile equipment falling on the circle C 1 ,C 2 ,…,C N The internal coordinate to be processed is a stable coordinate, and C is calculated in sequence 1 , C 2 ,…, C N The average value of all stable coordinates in the load point coordinate system is obtained, and N load point coordinates are obtained and are sequentially (x) 1 , y 1 ),(x 2 , y 2 ),…,(x N , y N ) Connecting all load points according to the connection relation in the matrix DA (the matrix DA is an adjacent matrix, the subscripts of rows and columns are respectively the serial numbers of all enterprises, 0 represents that two enterprises are not connected, 1 represents that two enterprises are connected, the matrix DA stores the connection relation of all enterprises, the enterprise position information represents the enterprises, the array cc stores the enterprise position information, and the circle C 1 , C 2 ,…, C N Taking the elements in the array cc as the circle center, and simultaneously, the load points fall in the circle, so that all load coordinates are connected according to the connection relation among enterprises in the matrix DA, and the connection relation of the enterprises can be reflected); wherein ln refers to the natural logarithm;
s302, set variable j =1, go to S303;
s303, setting a time period [0, t ], creating a sequence of 0,1, …, t at intervals of each second in the time period [0, t ], and turning to S304;
s304, recording (x) j0 , y j0 ), (x j1 , y j1 ),…, (x jt , y jt ) Are respectively a load point (x) j , y j ) The coordinate values at 0,1, …, t, increase j by 1, go to S305;
s305, if j is less than or equal to N, turning to S304, and if j is greater than N, turning to S306;
s306, setting variable p =1, and setting variable q = 0;
s307, the difference value between the longitude of the p-th load point at the q +1 th time and the longitude of the p-th load point at the q-th time is recorded as h pq ，h pq The calculation formula of (2) is as follows: h is pq =x p(q+1) -x pq Increasing the value of q by 1, and going to S308;
s308, if the value of q is less than or equal to t, turning to S307, and if the value of q is greater than t, turning to S309;
s309, making the value of q be 1, and turning to S310;
s310, recording the variable A p0 The value of (a) is 1,
recording variable B p0 Has a value of N (y) p1 - y p0 )/ h p0 ，
Recording variable A pt The value of (a) is 0,
recording variable B pt Has a value of N (y) pt - y p(t-1) )/ h p(t-1) ，
Note A pq Has a value of h p(q-1) /(h p(q-1) +h p )，
Note B pq Has a value of N (1-A) pq )*( y pq - y p(q-1) )/ h p(q-1) + N*A pq *( y p(q+1) -y pq )/ h pq ，
Increment the value of q by 1, and proceed to S311 (set variable A) p0 、B p0 、A pt 、B pt To calculate the subsequent a pq 、b pq ）；
S311, if the value of q is smaller than t, turning to S310, and if the value of q is larger than or equal to t, turning to S312;
s312, setting the value of q to be 0, and turning to S313;
s313, recording the variable a p0 Has a value of (-A) p0 ) /2, recording variable b p0 Has a value of B p0 /2，
Recording variable a pq Has a value of (-A) pq )/((N-1)+(1- A pq )* A p(q-1) )，
Recording variable b pq Has a value of (B) pq -(1- A pq )* B p(q-1) )/((N-1)+(1- A pq )* A p(q-1) )，
Increment the value of q by 1, go to S314 (set variable a) pq 、b pq To calculate the subsequent m pq ）；
S314, if the value of q is less than or equal to t, turning to S313, and if the value of q is greater than t, turning to S315;
s315, making the value of q t-1 and recording m pt Has a value of b pt Recording the variable m pq Has a value of pq *m p(q+1) +b pq Subtracting 1 from the value of q, and going to S316;
s316, if the value of q is more than or equal to 0, turning to S315, and if the value of q is less than 0, turning to S317;
s317, let q be 0 and let x be a function Crf pq (x) The argument of (c), function Crf pq (x) The calculation method is as follows:
Crf pq (x)=(1+N*(x-x p(q+1) )/(x pq -x p(q+1) ))*((x-x pq )/(x p(q+1) -x pq )) 2 *y p(q+1) +(x-x pq )*(x-x p(q+1) )/(x pq - x p(q+1) ) 2 *m pq ，
increase the value of q by 1, go to S318 (calculate function Crf) pq (x) Has the advantage that in the interval 0, t]In each interval, a broken line formed by discrete longitude and latitude coordinates is replaced by a continuous function, so that the accuracy of judging the association degree of the enterprise can be improved);
s318, if the value of q is smaller than t, turning to S317, and if the value of q is larger than or equal to t, turning to S319;
s319, if the value of p is less than or equal to N, increasing the value of p by 1, resetting q =0, proceeding to S307, and if the value of p is greater than N, proceeding to S320;
s320, setting the value of p to be 1, setting the value of q to be 0, and setting a variable k;
s321, let k be p +1
Go to S322;
s322, recording
Keeping an enterprise affinity agreement EISV = | (Crp-sign)/(min { Crp, sign }) |, wherein min { Crp, sign } represents a minimum value between Crp and sign, if the EISV value is less than 1, updating the element in the line p and the element in the line k in the matrix DA to be 1, and going to S323 (setting a variable A) p0 、B p0 、A pt 、B pt 、a pq 、b pq 、m pq Calculating function Crf pq (x) The purpose of the method is to calculate the EISV, judge whether the enterprises are connected or not by calculating the EISV, and update the EISV into a matrix DA so as to correct the enterprise relationship map);
s323, if the value of k is less than N, increasing the value of k by 1, and going to S322, and if the value of k is more than or equal to N, going to S324;
s324, if the value of p is smaller than N, increasing the value of p by 1, and turning to S321, and if the value of p is larger than or equal to N, turning to S325;
s325, if the value of q is less than t, resetting the value of p to be 1, increasing the value of q by 1, and turning to S321, and if the value of q is more than or equal to t, turning to S326;
s326, ending the program;
wherein t is set to [1,2] years, i.e., [31536000, 63072000] seconds.
The beneficial effect of this step does: because the association degrees among enterprises are different, the invisible cooperative relationship exists in part of enterprises, the accuracy of the enterprise relationship maps is influenced, the enterprise intimacy cooperation quantity is obtained by utilizing the positions of the enterprises and the position information of the mobile equipment of the staff in the enterprises through calculation, and the matrix DA is updated by the enterprise intimacy cooperation quantity EISV.
Further, in step S400, the enterprise relationship map is updated according to the deepened application matrix, and the specific steps are as follows:
s401, recording the row m1 where the element with the value of 0 in the application matrix is located, the column where the element is located is the n1 th row, recording the row m2 where the element with the value of 1 is located, and the column where the element is located is the n2 th row, canceling the connection between the enterprise with the number of m1 and the enterprise with the number of n1 in the enterprise relation map according to the enterprise number relation, and connecting the enterprise with the number of m2 and the enterprise with the number of n 2;
s402, circularly executing S401 until all elements in the deepened application matrix are traversed;
and S403, deleting isolated enterprises in the enterprise relationship graph, wherein the isolated enterprises are the enterprises which do not have connection relationships with other enterprises in the enterprise relationship graph.
Preferably, in step S400, the enterprise relationship map is updated according to the deepened application matrix, and the specific steps are as follows:
traversing each element in the deepened application matrix according to a depth-first search algorithm, disconnecting two enterprises corresponding to the element with the value of 0 and connecting two enterprises corresponding to the element with the value of 1 in the enterprise relationship map (the meaning of the two enterprises corresponding to the element is that in the enterprise relationship map, the row and the column of the element correspond to the two enterprises according to the enterprise numbering relationship); after traversing, deleting isolated enterprises in the enterprise relationship graph, wherein the isolated enterprises are the enterprises which do not have connection relations with other enterprises in the enterprise relationship graph.
The invention also provides a construction system of the enterprise relationship map, which comprises the following steps: the system comprises a processor, a memory and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to implement steps in a method for constructing an enterprise relationship graph, the system for constructing the enterprise relationship graph can run in computing devices such as a desktop computer, a notebook computer, a mobile phone, a portable phone, a tablet computer, a palmtop computer and a cloud data center, and can run in a system including, but not limited to, the processor, the memory and a server cluster, and the processor executes the computer program to run in units of the following systems:
the system comprises an atlas acquisition unit, a mapping unit and a mapping unit, wherein the atlas acquisition unit is used for acquiring an enterprise relation atlas of an enterprise;
the matrix construction unit is used for constructing an enterprise relation matrix according to the enterprise names and the enterprise relations in the enterprise relation map;
the matrix generating unit is used for generating a deepened application matrix according to the enterprise relation matrix;
and the map updating unit is used for updating the enterprise relation map according to the deepened application matrix and outputting the enterprise relation map.
The invention has the beneficial effects that: the method can improve the accuracy of the enterprise relation maps, fully reflect the association degree among enterprises, intensify the weight value of enterprise information change in the construction process, effectively analyze the invisible relationship among the enterprises by coordinating the association of all the enterprises in the maps, correct and optimize the enterprise relation maps in the database, and has instant help for analyzing the enterprise risk propagation paths and the enterprise operation activities.
Drawings
The above and other features of the invention will be more apparent from the detailed description of the embodiments shown in the accompanying drawings in which like reference characters designate the same or similar elements, and it will be apparent that the drawings in the following description are merely exemplary of the invention and that other drawings may be derived by those skilled in the art without inventive effort, wherein:
FIG. 1 is a flow chart of a method for constructing an enterprise relationship graph;
fig. 2 is a system configuration diagram of a system for constructing an enterprise relationship graph.
Detailed Description
The conception, the specific structure and the technical effects of the present invention will be clearly and completely described in conjunction with the embodiments and the accompanying drawings to fully understand the objects, the schemes and the effects of the present invention. It should be noted that, in the present application, the embodiments and features of the embodiments may be combined with each other without conflict.
In the description of the present invention, the meaning of a plurality of means is one or more, the meaning of a plurality of means is two or more, and larger, smaller, larger, etc. are understood as excluding the number, and larger, smaller, inner, etc. are understood as including the number. If there is a description of first and second for the purpose of distinguishing technical features only, this is not to be understood as indicating or implying a relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of technical features indicated.
Referring to fig. 1, a flow chart of a method for constructing an enterprise relationship graph according to the present invention is shown, and a method for constructing an enterprise relationship graph according to an embodiment of the present invention is described below with reference to fig. 1.
The invention provides a construction method of an enterprise relationship map, which comprises the following steps:
s100, acquiring an enterprise relation map of an enterprise to be queried;
s200, constructing an enterprise relation matrix according to the enterprise names and the enterprise relations in the enterprise relation map;
s300, generating a deepened application matrix according to the enterprise relation matrix;
s400, updating the enterprise relation map according to the deepened application matrix, and outputting the updated enterprise relation map;
the enterprise relationship graph comprises at least two enterprises, each enterprise comprises a plurality of employees, each employee holds a mobile device and is used for obtaining positioning information of the employees, and the positioning information comprises longitude and latitude coordinates.
Preferably, in step S100, an enterprise relationship map of an enterprise to be queried is obtained, and the specific method includes: acquiring an enterprise relationship map of an enterprise to be inquired by an enterprise relationship map generation method in a patent with the patent number of CN107229756A, or acquiring the enterprise relationship map of the enterprise to be inquired by an enterprise inquiry website (an enterprise information inquiry tool);
further, in step S200, an enterprise relationship matrix is constructed according to the enterprise name and the enterprise relationship in the enterprise relationship map, and the specific steps are as follows: screening all enterprises from an enterprise relation map, recording the number of all enterprises as N, numbering all enterprises in sequence by using N numbers 1,2, …, N to obtain enterprise numbering relations (each enterprise in the map corresponds to a number, and can be positioned to the corresponding enterprise according to the number), creating an all-zero matrix R with N rows and N columns, setting an integer variable i =1, and recording the value range of i as [1, N ];
and traversing i in sequence, in the enterprise relationship graph, setting the numbers R1, R2, … and rn of all enterprises which have connection relations with the enterprise with the number i, setting integer variables j, setting the values of j to R1, R2, … and rn in sequence, traversing j in sequence, updating the element of the ith row and the jth column in the matrix R to be 1 (namely marking the relation among all enterprises in the enterprise relationship graph by 0 or 1), setting R1 to be a transposed matrix of R, updating R to be R + R1, and setting the matrix R to be an enterprise relationship matrix (also called an adjacent matrix to represent the connection relations of the elements in the graph).
Further, in step S300, a deepened application matrix is generated according to the enterprise relationship matrix, and the specific method includes: recording the number of the enterprises with the largest number of employees as E, recording the number of all the employees as st, acquiring the longitude and latitude coordinates of the mobile equipment of each employee in the E, sequentially constructing an array lal (the array lal is a two-dimensional array, the st row is 2 columns, the 1 st column is the longitude coordinate of the mobile equipment of each employee, and the 2 nd column is the latitude coordinate of the mobile equipment of each employee) by taking the longitude and latitude coordinates of the mobile equipment of each employee as one row in the E, and recording lal i1j1 The longitude and latitude coordinates of the enterprise position recorded as E are (eg, et) for the elements in the i1 th row and the j1 th column in the two-dimensional array lal, and the enterprise pivot value is calculated by the following formula
The enterprise central pivot measuring value is used as an index for judging whether the association state of the enterprise is abnormal or not according to the unknown change trend of the employee;
acquiring longitude and latitude coordinates of each enterprise, sequentially constructing an array cc (the array cc is a two-dimensional array, and is N rows and 2 columns) by taking the longitude and latitude coordinates of each enterprise as one row according to the ascending order of enterprise numbers, sequentially constructing an array mdc (the array mdc is a two-dimensional array, and is N rows and 2 columns) by taking the average value of the longitude and latitude coordinates of mobile devices of all employees in each enterprise as one row, and recording the cc i2j2 Is the element in the i2 th row and the j2 th column in the array cc, and is denoted mdc i3j3 For the element in row i3, column j3 in the array mdc, i2, j2=1,2, …, N, i3, j3=1,2, …, N, the integer variable p =1, p ∈ [1, N]P is traversed in turn, storing the values of all p that satisfy condition con1 and satisfy condition con2 in array esc,
wherein the condition con1 indicates that the business pivot measurement value of the enterprise corresponding to the pth element in the array cc is less than or equal to cpp, or the condition con1 indicates that the business pivot measurement value of the current enterprise (i.e. the enterprise corresponding to the pth element in the array cc) is less than or equal to ccGV, and the condition con2 indicates mdc p1 ∈[cc p1 -K1, cc p1 +K1]And mdc p2 ∈[cc p2 -K2, cc p2 +K2](ii) a ccGV is the average of the enterprise pivot measurements of each enterprise in the array cc; k1 is the difference between KT1 and KST 1; k2 is the difference between KT2 and KST 2; KT1 is the average value of each element in the 1 st column of the array lal, and KST1 is the average value of each element in the 1 st column of the array mdc corresponding to the current enterprise; KT2 is the average value of each element in the 2 nd column of the array lal, and KST2 is the average value of each element in the 2 nd column of the array mdc corresponding to the current enterprise;
alternatively, where condition con1 refers to mdc p1 ∈[int1,int2]Condition con2 refers to mdc p2 ∈[int3,int4]Int1 has a value cc p1 The value of-cpp, int2 is cc p1 The value of + cpp, int3 is cc p2 The value of-cpp, int4 is cc p2 + cpp; note esc i4 Traversing the value range of i4 for the i4 th element in the array esc (the value range of i4 is determined by the number of p meeting the condition), and sequentially adding esc th element in the enterprise relation matrix R i4 All elements of a linePlain No. esc i4 All elements of the column are updated to 0, and the matrix R is taken as the deepening application matrix DA.
The method for calculating the enterprise pivot measuring value of the current enterprise (the same as the method for calculating the enterprise pivot measuring value of the enterprise with the most number of staff) comprises the following steps:
the number of all employees in the current enterprise EQ is recorded as st1, the longitude and latitude coordinates of the mobile equipment of each employee in the current enterprise EQ are obtained, an array lalC is constructed by taking the longitude and latitude coordinates of the mobile equipment of each employee in the current enterprise EQ as a row (the array lalC is a two-dimensional array, st1 rows and 2 columns are total, the 1 st column is the longitude coordinate of the mobile equipment of each employee, and the 2 nd column is the latitude coordinate of the mobile equipment of each employee), and the lalC is recorded i1j1 Recording longitude and latitude coordinates of the enterprise position of the current enterprise EQ as (EQgC, EQtC) for the elements in the i1 th line and the j1 th column in the two-dimensional array lalC, and calculating the enterprise pivot measuring value of the current enterprise EQ according to the following formula:
。
because the association degrees among enterprises are different, the invisible relationship exists in part of enterprises, the accuracy of the enterprise relationship maps is influenced, and in order to solve the problem and further improve the available reference value of the enterprise relationship maps, the invention provides a method for improving the application matrix DA more preferentially, which comprises the following steps:
preferably, the deepening application matrix DA further needs to be optimized by the following steps:
s301, recording the regression measure erd = [ ln (| cpp/(1-cpp) |)]Wherein, the]Is expressed as rounding up, [ ln (| cpp/(1-cpp) |)]Represents rounding up ln (| cpp/(1-cpp) |), and | cpp/(1-cpp) | represents the absolute value of cpp/(1-cpp), and sets the integer variable i, i ∈ [1, N |)]Traversing i in the value range of i, and sequentially (cc) in the coordinate system i1 ,cc i2 ) Constructing N circles C by taking erd as radiuses and taking the circle center as the center 1 ,C 2 ,…,C N Recording longitude and latitude coordinates of mobile equipment of all employees in all enterprises as coordinates to be processed, and marking the mobile equipment falling on the circle C 1 ,C 2 ,…,C N The internal coordinates to be processed being stableCoordinates, calculating C in turn 1 , C 2 ,…, C N The average value of all stable coordinates in the load point coordinate system is obtained, and N load point coordinates are obtained and are sequentially (x) 1 , y 1 ),(x 2 , y 2 ),…,(x N , y N ) Connecting all load points according to the connection relation in a matrix DA (the matrix DA is a 01 matrix, the subscripts of rows and columns are respectively the numbers of all enterprises, 0 represents that two enterprises are not connected, 1 represents that two enterprises are connected, the matrix DA stores the connection relation of all enterprises, the enterprise position information represents the enterprises, the array cc stores the enterprise position information, and a circle C 1 , C 2 ,…, C N Taking the elements in the array cc as the circle center, and simultaneously, the load points fall in the circle, so that all load coordinates are connected according to the connection relation among enterprises in the matrix DA, and the connection relation of the enterprises can be reflected);
s302, set variable j =1, go to S303;
s303, setting a time period [0, t ], creating a sequence of 0,1, …, t at intervals of every second in the time period [0, t ], and turning to S304;
s304, recording (x) j0 , y j0 ), (x j1 , y j1 ),…, (x jt , y jt ) Are respectively a load point (x) j , y j ) The coordinate values at 0,1, …, t, increase j by 1, go to S305;
s305, if j is less than or equal to N, turning to S304, and if j is greater than N, turning to S306;
s306, setting variable p =1, and setting variable q = 0;
s307, the difference value between the longitude of the p-th load point at the q +1 th time and the longitude of the p-th load point at the q-th time is recorded as h pq ，h pq The calculation formula of (2) is as follows: h is pq =x p(q+1) -x pq Increasing the value of q by 1, and going to S308;
s308, if the value of q is less than or equal to t, going to S307, and if the value of q is greater than t, going to S309;
s309, setting the value of q as 1, and turning to S310;
s310, recording the variable A p0 Has a value of 1, and records the variable B p0 Has a value of N (y) p1 - y p0 )/ h p0 Recording the variable A pt Is 0, and the variable B is recorded pt Has a value of N (y) pt - y p(t-1) )/ h p(t-1) Recording the variable A pq Has a value of h p(q-1) /(h p(q-1) +h p ) Record the variable B pq Has a value of N (1-A) pq )*( y pq - y p(q-1) )/ h p(q-1) + N*A pq *( y p(q+1) -y pq )/ h pq ，
Increasing the value of q by 1, and going to S311;
s311, if the value of q is smaller than t, turning to S310, and if the value of q is larger than or equal to t, turning to S312;
s312, setting the value of q to be 0, and turning to S313;
s313, recording the variable a p0 Has a value of (-A) p0 ) /2, recording variable b p0 Has a value of B p0 /2，
Recording variable a pq Has a value of (-A) pq )/((N-1)+(1- A pq )* A p(q-1) )，
Recording variable b pq Has a value of (B) pq -(1- A pq )* B p(q-1) )/((N-1)+(1- A pq )* A p(q-1) )，
Increasing the value of q by 1, and going to S314;
s314, if the value of q is less than or equal to t, turning to S313, and if the value of q is greater than t, turning to S315;
s315, making the value of q t-1 and recording m pt Has a value of b pt Remember m pq Has a value of pq *m p(q+1) +b pq Subtracting 1 from the value of q, and going to S316;
s316, if the value of q is more than or equal to 0, turning to S315, and if the value of q is less than 0, turning to S317;
s317, let q be 0 and let x be a function Crf pq (x) The argument of (c), function Crf pq (x) The calculation method is as follows: crf pq (x)=
(1+N*(x-x p(q+1) )/(x pq - x p(q+1) ))*((x-x pq )/(x p(q+1) - x pq )) 2 *y p(q+1) +(x-x pq )*(x-x p(q+1) )/(x pq - x p(q+1) ) 2 *m pq ，
Increasing the value of q by 1, and going to S318;
s318, if the value of q is smaller than t, going to S317, and if the value of q is larger than or equal to t, going to S319;
s319, if the value of p is less than or equal to N, increasing the value of p by 1, resetting q =0, and going to S307, if the value of p is greater than N, going to S320;
s320, setting the value of p to be 1, setting the value of q to be 0, and setting a variable k;
s321, let k be p +1
Go to S322;
s322, recording
Keeping the enterprise affinity synergy EISV = | (Crp-sign)/(min { Crp, sign }) |, wherein min { Crp, sign } represents the minimum value between Crp and sign, and if the value of EISV is less than 1, updating the element in the line p of the kth row and the element in the line k of the pth row in the matrix DA to be 1, and turning to S323; judging whether the enterprises are connected or not by calculating EISV, and updating the EISV into a matrix DA so as to correct the enterprise relationship map;
s323, if the value of k is less than N, increasing the value of k by 1, and going to S322, and if the value of k is more than or equal to N, going to S324;
s324, if the value of p is smaller than N, increasing the value of p by 1, and turning to S321, and if the value of p is larger than or equal to N, turning to S325;
s325, if the value of q is less than t, resetting the value of p to be 1, increasing the value of q by 1, and turning to S321, and if the value of q is more than or equal to t, turning to S326;
s326, ending the program;
wherein t is set to [1,2] years, i.e., [31536000, 63072000] seconds.
Further, in step S400, the enterprise relationship map is updated according to the deepened application matrix, and the specific steps are as follows:
s401, recording the row m1 where the element with the value of 0 in the application matrix is located, the column where the element is located is the n1 th row, recording the row m2 where the element with the value of 1 is located, and the column where the element is located is the n2 th row, canceling the connection between the enterprise with the number of m1 and the enterprise with the number of n1 in the enterprise relation map according to the enterprise number relation, and connecting the enterprise with the number of m2 and the enterprise with the number of n 2;
s402, circularly executing S401 until all elements in the deepened application matrix are traversed;
and S403, deleting isolated enterprises in the enterprise relationship graph, wherein the isolated enterprises are the enterprises which do not have connection relationships with other enterprises in the enterprise relationship graph.
Preferably, in step S400, the enterprise relationship map is updated according to the deepened application matrix, and the specific steps are as follows:
traversing each element in the deepened application matrix according to a depth-first search algorithm, disconnecting two enterprises corresponding to the element with the value of 0 in the enterprise relationship graph, and connecting two enterprises corresponding to the element with the value of 1 (the meaning of the two enterprises corresponding to the element is that in the enterprise relationship graph, the row and the column of the element correspond to the two enterprises according to the enterprise numbering relationship); after traversing, deleting isolated enterprises in the enterprise relationship graph, wherein the isolated enterprises are the enterprises which do not have connection relations with other enterprises in the enterprise relationship graph.
As shown in fig. 2, the system for constructing an enterprise relationship graph according to an embodiment of the present invention includes: a processor, a memory and a computer program stored in the memory and executable on the processor, the processor implementing the steps in the above embodiment of the method for building an enterprise relationship graph when executing the computer program, the processor executing the computer program to run in the units of the following system:
the system comprises an atlas acquisition unit, a mapping unit and a mapping unit, wherein the atlas acquisition unit is used for acquiring an enterprise relation atlas of an enterprise;
the matrix construction unit is used for constructing an enterprise relation matrix according to the enterprise names and the enterprise relations in the enterprise relation map;
the matrix generating unit is used for generating a deepened application matrix according to the enterprise relation matrix;
and the map updating unit is used for updating the enterprise relation map according to the deepened application matrix and outputting the enterprise relation map.
The construction system of the enterprise relationship graph can be operated in computing equipment such as a desktop computer, a notebook computer, a palm computer and a cloud data center. The system for constructing the enterprise relationship graph comprises, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the example is only an example of the method and system for constructing the enterprise relationship graph, and does not constitute a limitation to the method and system for constructing the enterprise relationship graph, and may include more or less components than the other, or combine some components, or different components, for example, the system for constructing the enterprise relationship graph may further include input and output devices, network access devices, buses, and the like.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete component Gate or transistor logic, discrete hardware components, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor, etc., and the processor is a control center of the building system of the enterprise relationship map and connects the sub-areas of the building system of the whole enterprise relationship map by using various interfaces and lines.
The memory can be used for storing the computer programs and/or modules, and the processor implements various functions of the method and system for constructing the enterprise relationship graph by running or executing the computer programs and/or modules stored in the memory and calling the data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, etc. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The invention provides a method and a system for constructing an enterprise relationship map, which are used for acquiring the enterprise relationship map of an enterprise to be inquired, constructing an enterprise relationship matrix according to an enterprise name and an enterprise relationship in the enterprise relationship map, generating a deepened application matrix according to the enterprise relationship matrix, updating the enterprise relationship map according to the deepened application matrix and outputting the enterprise relationship map. Although the present invention has been described in considerable detail and with reference to certain illustrated embodiments, it is not intended to be limited to any such details or embodiments or any particular embodiment, so as to effectively encompass the intended scope of the invention. Furthermore, the foregoing describes the invention in terms of embodiments foreseen by the inventor for which an enabling description was available, notwithstanding that insubstantial modifications of the invention, not presently foreseen, may nonetheless represent equivalent modifications thereto.
Claims (6)
1. A method for constructing an enterprise relationship graph is characterized by comprising the following steps:
s100, acquiring an enterprise relation map of an enterprise to be queried;
s200, constructing an enterprise relation matrix according to the enterprise names and the enterprise relations in the enterprise relation map;
s300, generating a deepened application matrix according to the enterprise relation matrix;
and S400, updating the enterprise relation map according to the deepening application matrix, and outputting the updated enterprise relation map.
2. The method as claimed in claim 1, wherein the enterprise relationship graph includes at least two enterprises, each enterprise includes a plurality of employees, each employee holds a mobile device for obtaining location information of the employee, and the location information includes longitude and latitude coordinates.
3. The method for constructing an enterprise relationship graph according to claim 1, wherein in step S200, an enterprise relationship matrix is constructed according to the enterprise names and the enterprise relationships in the enterprise relationship graph, and the specific steps are as follows: screening all enterprises from an enterprise relation map, recording the number of all enterprises as N, numbering all enterprises in sequence by using N numbers 1,2, …, N to obtain enterprise numbering relation, creating an all-zero matrix R with N rows and N columns, setting an integer variable i =1, and recording the value range of i as [1, N ];
sequentially traversing i, in the enterprise relationship graph, recording the numbers R1, R2, … and rn of all enterprises which have connection relationship with the enterprise with the number i, setting integer variables j, recording the values of j as R1, R2, … and rn, sequentially traversing j, updating the element of the jth row and the jth column in the matrix R as 1, recording R1 as a transposed matrix of R, updating R as R + R1, and recording the matrix R as an enterprise relationship matrix.
4. The method for constructing an enterprise relationship graph according to claim 1, wherein in step S300, a deepened application matrix is generated according to the enterprise relationship matrix, and the specific method is as follows: recording the number of the enterprises with the most employees as E, recording the number of all the employees as st, acquiring the longitude and latitude coordinates of the mobile equipment of each employee in the E, sequentially constructing an array lal by taking the longitude and latitude coordinates of the mobile equipment of each employee in the E as a row, and recording lal i1j1 For the element in row i1 and column j1 in the two-dimensional array lal, the longitude and latitude coordinates of the enterprise location with the notation E are (eg, et), and the enterprise pivot value cpp is calculated by the following formula:
obtainingSequentially constructing an array cc by taking the longitude and latitude coordinates of each enterprise as a line according to the ascending order of the enterprise numbers, sequentially constructing an array mdc by taking the average value of the longitude and latitude coordinates of the mobile devices of all the employees in each enterprise as a line, and recording the array cc i2j2 Is the element in the i2 th row and the j2 th column in the array cc, and is written mdc i3j3 For the element in row i3, column j3 in the array mdc, i2, j2=1,2, …, N, i3, j3=1,2, …, N, the integer variable p =1, p ∈ [1, N]Sequentially traversing p, storing all values of p that satisfy condition con1 and satisfy condition con2 in array esc,
wherein the condition con1 indicates that the enterprise pivot measurement value of the corresponding enterprise of the pth element in the group cc is less than or equal to cpp, or the condition con1 indicates that the enterprise pivot measurement value of the current enterprise is less than or equal to ccGV, and the condition con2 indicates mdc p1 ∈[cc p1 -K1, cc p1 +K1]And mdc p2 ∈[cc p2 -K2, cc p2 +K2](ii) a ccGV is the average of the enterprise pivot measurements of each enterprise in the array cc; k1 is the difference between KT1 and KST 1; k2 is the difference between KT2 and KST 2; KT1 is the average value of each element in the 1 st column of the array lal, and KST1 is the average value of each element in the 1 st column of the array mdc corresponding to the current enterprise; KT2 is the average value of each element in the 2 nd column of the array lal, and KST2 is the average value of each element in the 2 nd column of the array mdc corresponding to the current enterprise;
alternatively, condition con1 refers to mdc p1 ∈[int1,int2]Condition con2 refers to mdc p2 ∈[int3,int4]Int1 has a value cc p1 The value of-cpp, int2 is cc p1 The value of + cpp, int3 is cc p2 The value of-cpp, int4 is cc p2 +cpp；
Note esc i4 For the i4 th element in the array esc, traverse i4 and sequentially select the esc th element in the enterprise relationship matrix R i4 All elements of a row and esc th i4 And updating all elements of the columns to be 0, and recording the enterprise relation matrix R as a deepened application matrix DA.
5. The method for constructing the enterprise relationship graph according to claim 1, wherein in step S400, the enterprise relationship graph is updated according to the deepening application matrix, and the specific steps are as follows:
s401, recording the row m1 where the element with the value of 0 in the application matrix is located, the column where the element is located is the n1 th row, recording the row m2 where the element with the value of 1 is located, and the column where the element is located is the n2 th row, canceling the connection between the enterprise with the number of m1 and the enterprise with the number of n1 in the enterprise relation map according to the enterprise number relation, and connecting the enterprise with the number of m2 and the enterprise with the number of n 2;
s402, circularly executing S401 until all elements in the deepened application matrix are traversed;
and S403, deleting isolated enterprises in the enterprise relationship graph, wherein the isolated enterprises are the enterprises which do not have connection relationships with other enterprises in the enterprise relationship graph.
6. The method for constructing the enterprise relationship graph according to claim 1, wherein in step S400, the enterprise relationship graph is updated according to the deepening application matrix, and the specific steps are as follows: traversing each element in the deepened application matrix according to a depth-first search algorithm, disconnecting two enterprises corresponding to the element with the value of 0 and connecting two enterprises corresponding to the element with the value of 1 in the enterprise relationship map; after traversing, deleting isolated enterprises in the enterprise relationship graph, wherein the isolated enterprises are the enterprises which do not have connection relations with other enterprises in the enterprise relationship graph.
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| US20190370296A1 (en) * | 2018-05-30 | 2019-12-05 | Beijing Baidu Netcom Science And Technology Co., Ltd. | Method and device for mining an enterprise relationship |
| CN110968701A (en) * | 2019-11-05 | 2020-04-07 | 量子数聚（北京）科技有限公司 | Relationship map establishing method, device and equipment for graph neural network |
| WO2021213448A1 (en) * | 2020-04-24 | 2021-10-28 | 支付宝(杭州)信息技术有限公司 | Determination of map for information recommendation |
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