CN112686574B - Method for identifying key structure of attribute facility network - Google Patents
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- CN112686574B CN112686574B CN202110049616.8A CN202110049616A CN112686574B CN 112686574 B CN112686574 B CN 112686574B CN 202110049616 A CN202110049616 A CN 202110049616A CN 112686574 B CN112686574 B CN 112686574B
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Abstract
The invention discloses a method for identifying a key structure of an attribute facility network. In order to find dense and stable attribute facility networks, the invention proposes a new identification attribute facility network model, i.e. the key structure of the attribute facility network, on the attribute facility network. The invention firstly reduces the calculation amount of the facilities needing to be selected finally by reducing the facility selecting space needing to be selected. Meanwhile, considering the unbalanced graphic structure and the attribute of the attribute facility network, the invention provides a new pruning method, and the selected facilities possibly needing to be removed are further examined, so that the facilities which do not meet the requirements are rapidly removed, and the key structure of the attribute facility network can be rapidly found in the large-scale attribute facility network. The application of the method has great benefit for identifying the key structure of the attribute facility network and greatly helps to select the attribute facility network in real life.
Description
Technical Field
The invention belongs to the technical field of facility network data detection, and particularly relates to a method for identifying a key structure of an attribute facility network.
Background
In real life, the facility network is indistinguishable from us, such as the placement of shared bicycle locations, the distribution of electric vehicle charging piles, the distribution of public fire extinguishing facilities, and the like. With the continuous development of society and the continuous expansion of network scale, various facility networks are also growing significantly. In a facility network, each facility has a certain association with other facilities, and some facilities may play a role in promotion, for example, sharing bicycles at different positions on the same platform can help surrounding users to quickly solve the last kilometer problem. However, there are still mutually exclusive effects among some facilities, such as aged facilities, and these facilities may have some conflicts with other facilities, so that people cannot obtain the facilities in time when actually using public facilities. We mark the relationship between facilities with promoting effect as positive side and the relationship between facilities with negative mutual exclusion effect as negative side, thus obtaining the attribute facility network based on the facility network.
Research into facility networks generally defaults to positive relationships between existing facilities, i.e., they are all interactions. In real life, however, mutually exclusive facilities still exist, and if these facilities are considered to have a mutual promoting effect, there may be unstable structures in the resulting facility network, for example, when we need to use a shared bicycle or a charging pile urgently, suitable facilities cannot be found in the nearby area. But if the facilities between the mutexes are removed directly from the facility network, a very small facility network is obtained.
Meanwhile, in order to obtain the attribute facility network really needed by the user, we need to obtain the key structure of the attribute facility network. Many researchers have conducted intensive research into identifying key structures of attribute facility networks, however, many researchers default edges thereof to positive edges when researching attribute facility networks, which cannot truly reflect relationships between facilities, which is out of close connection with the life condition of users, and cannot well find dense and stable attribute facility networks. Meanwhile, in a key structure for identifying the attribute facility network, the existing algorithm has lower efficiency, and the attribute facility network required by the user cannot be identified quickly.
Disclosure of Invention
The invention aims to provide a method for identifying key structures of an attribute facility network, aiming at the defects of the prior art.
The invention aims at realizing the following technical scheme: a method of identifying a critical structure of an attribute facility network, the method comprising the steps of:
step one: given a real attribute facility network G (V, E), where V represents the collection of all facilities in G and E represents the edges between all facilities in G; acquiring all facilities in V and all positive edges in E from the network to form a positive facility network;
an unbalanced graphic structure X (R, S) in an attribute facility network G is defined that satisfies the following conditions: all facilities in some sub-facility sets R, R and all their sides S in V can be enclosed into a polygon, and the number of positive sides in all sides is less than the number of negative sides.
Step two: calculating a critical structure of the positive facility network, the critical structure satisfying two conditions: 1. each facility u in the key structure has at least k positive edges, namely, the facility u has k positive neighbors; 2. the critical structure is very large, i.e. any larger critical structure does not meet at least k positive neighbors per facility.
Step three: the facilities with negative neighbors in the attribute facility network G are put into the candidate deletion facility set C.
Step four: for each candidate deletion facility set C, calculating a key structure group of the facilities in C, the key structure group satisfying the following condition: 1. the number of neighbors of each facility in the key structure group is k;2. in a critical structural group, there must be one facility v+.u for a certain facility u, satisfying that u and v are in the same critical structural group, and v is the positive neighbor of u.
Step five: the deletion cost for each facility in the candidate deletion set of facilities C is calculated, and for the deletion cost for facility u, it is defined as: in the critical structure of the facility network, the condition of the critical structure of the facility network is not satisfied after the facility u is deleted, so that the number of all facilities removed.
Step six: acquiring a key structure of the attribute facility network G, wherein the key structure of the attribute facility network meets the following conditions: 1. the number of positive neighbors of each facility in the critical structure is at least k;2. the key structure has no unbalanced graphic structure; 3. the critical structure is extremely large, i.e., any larger critical structure does not satisfy both condition 1 and condition 2;
the acquisition process specifically comprises the following steps: selecting a facility u with the minimum deletion cost in the candidate deletion facility set C, deleting all facilities in a key structure group from G if u exists in the key structure group, otherwise deleting u only in G; if the attribute facility network G obtained after the facility deletion meets the condition of the key structure of the attribute facility network, outputting the attribute facility network G as the key structure of the attribute facility network, otherwise, returning to the step four.
Further, in the first step, if there is a positive relationship between the facility u and the facility v, the edges of the two facilities are denoted as positive edges, and the facility v is called as a positive neighbor of the facility u; if there is a negative relationship between facility u and facility v, then the edges of both facilities are noted as negative edges, and facility v is referred to as the negative neighbor of facility u.
Further, the acquiring the network under installation in the step one specifically includes: and accessing a certain facility u in the facility set V in the attribute facility network G, adding the facility u and the positive side of the facility u into a new attribute facility network, and continuing to access other facilities in the V after all sides of the certain facility u are accessed until all facilities are accessed, wherein the obtained new attribute facility network is the positive facility network.
Further, in the second step, the key structure of the computing facility network is specifically: and inquiring a certain facility u in the positive facility network, and if the number of the positive edges of the facility u is smaller than k, iteratively deleting the positive edges of the facilities u and u until no deletable facility exists, wherein the rest of the positive facility network is a key structure.
Further, in the third step, in order to break the unbalanced graph structure in the attribute facility network, the facilities with negative neighbors in the G are put into the candidate deletion facility set C, and the candidate deletion facility set C is no longer all the facilities in the attribute facility network G.
Further, the fourth step comprises the following sub-steps:
(a) Setting i to 0, wherein i is the sequence number of the key structure group currently being constructed;
(b) If there is a facility u in the candidate deletion facility set C that has not been accessed, and the number of positive neighbors of the facility u is k in the critical structure of the positive facility network, performing (C) - (g) in a loop, otherwise performing (h);
(c) Placing the facility u to be queried in a facility queue, circularly executing (d) - (f) if no facility is contained in the facility queue, otherwise executing (g);
(d) Ejecting a facility from the facility queue, and putting the facility into the current key structure group i, namely the constructed ith key structure group;
(e) Acquiring neighbor facilities w of a facility u popped up in a key structure of the positive facility network, if the facility w is not accessed and the positive neighbor number of the facility w in the key structure of the positive facility network is k, performing (f) circularly, otherwise performing (g);
(f) Marking the facility w as a facility that has been accessed and pushing w into a facility queue;
(g) Adding the currently constructed key structure group i into all key structure groups, wherein the sequence number id plus 1 represents that the current key structure group is constructed;
(h) Returning all critical structural groups.
Further, in the fifth step, the calculating of the deletion cost of each facility is specifically: copying the key structure of the positive facility network obtained in the step two to obtain a key structure copy Q of the positive facility network, and calculating the facility quantity Q of the Q; removing a certain facility u in the candidate deleted facility set C from Q, iteratively inquiring the number of positive neighbors of each facility in Q after removing u, deleting the facilities with the number of positive neighbors smaller than k in Q until no facility capable of being deleted exists, calculating the number of the rest facilities in Q, and recording the number of the rest facilities as p, wherein the deleting cost of the facility u is Q-p.
The invention also provides a computer device comprising a memory and a processor, wherein the memory stores computer readable instructions which, when executed by the processor, cause the processor to perform the steps in the method for identifying the key structure of the attribute facility network.
The present invention also provides a storage medium storing computer readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps in the method of identifying a critical structure of an attribute facility network described above.
The beneficial effects of the invention are as follows: the invention provides a method for identifying key structures of attribute facility networks, by which the attribute facility networks really needed by users can be obtained in actual life, and the method can help the users to quickly find appropriate facilities around. Meanwhile, the invention accelerates the acquisition of the attribute facility network really needed by the user through a series of optimization methods, and can reduce the repeated operation process in the facility selection process for the complex attribute facility network, thereby reducing the calculation cost.
Drawings
FIG. 1 is a flow chart of a method for identifying key structures of an attribute facility network provided by an embodiment of the present invention;
FIG. 2 is a schematic diagram of an attribute facility network provided by an embodiment of the present invention;
fig. 3 is a schematic diagram of a key structure of a fast-generating attribute facility network provided by an embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the invention will be readily understood, a more particular description of the invention will be rendered by reference to the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
As shown in fig. 1, a method for identifying a key structure of an attribute facility network according to an embodiment of the present invention includes:
step one: given a real attribute facility network G (V, E), where V represents a collection of all facilities in the attribute facility network, while the connection of the related facility u and the facility V is denoted as an edge, the facility V is called a neighbor of the facility u. If there is a positive relationship (cooperative relationship, complementary relationship, etc.) between the facility u and the facility v, the sides of the two facilities are denoted as positive sides, and the facility v is called a positive neighbor of the facility u. If there is a negative relationship (competing relationship, mutually exclusive relationship, etc.) between facility u and facility v, then the edges of both facilities are noted as negative edges, and facility v is referred to as the negative neighbor of facility u. E represents the edges between all facilities in the attribute facility network G. From which all facilities in V and all positive edges in E are obtained, constituting a positive facility network.
The specific method comprises the following steps: according to the attribute facility network G, accessing a certain facility u in the facility set V in the G, adding the positive sides of the facility u and the facility u into a new attribute facility network, and continuing to access other facilities in the V after all sides of the certain facility u are accessed until all facilities are accessed, wherein the obtained new attribute facility network is the positive facility network.
Meanwhile, an unbalanced graphic structure X (R, S) in the attribute facility network G is defined, which satisfies the following condition: all facilities in the facility set V and all their sides S can be enclosed into a polygon for some of the sub-facility sets R, and the number of positive sides is smaller than the number of negative sides.
Step two: according to the positive facility network obtained in the step one, calculating a key structure of the positive facility network, wherein the key structure is required to meet two conditions: 1. each facility u in the key structure has at least k positive edges, namely, the facility u has k positive neighbors; 2. the critical structure is extremely large, and any larger critical structure does not satisfy at least k positive neighbors per facility.
Typically, the k value is set according to the density of the facility network (e.g., the density of the shared bicycle impression), typically taking 5-10.
The specific method comprises the following steps: and inquiring a certain facility u in the positive facility network, and if the number of the positive edges of the facility u is smaller than k, iteratively deleting the positive edges of the facilities u and u until no deletable facility exists, wherein the rest of the positive facility network is a key structure.
Step three: a candidate deletion facility set C in the attribute facility network G is obtained.
To break the unbalanced graph structure in the attribute facility network, we need only put the facilities with negative neighbors in G into the candidate deletion facility set C. Thereby reducing the number of facilities in the candidate deletion facility set C that need to be selected, which is no longer all the facilities in the attribute facility network G.
Step four: for each candidate deletion facility set C, calculating a key structure group of the facilities in C, the key structure group g satisfying the following condition: 1. the number of neighbors of each facility in the key structure group is k;2. in a critical structural group, there must be one facility v+.u for a certain facility u, satisfying that u and v are in the same critical structural group, and v is the positive neighbor of u.
By constructing a key structure group, we can accelerate the key structure of the attribute utility network that gets the desired output. And when the deleted facility u is selected in the step six, simultaneously obtaining the key structure group where the facility u is located, and removing all facilities of the key structure group from the key structure of the attribute facility network.
In one embodiment, the calculation of the critical structure group specifically includes the sub-steps of:
(a) Setting i to 0, wherein i is the sequence number of the key structure group currently being constructed;
(b) If there is a facility u in the candidate deletion facility set C that has not been accessed, and the number of positive neighbors of the facility u is k in the critical structure of the positive facility network, performing (C) - (g) in a loop, otherwise performing (h);
(c) Placing the facility u to be queried in a facility queue, circularly executing (d) - (f) if no facility is contained in the facility queue, otherwise executing (g);
(d) Ejecting a facility from the facility queue, and putting the facility into the current key structure group i, namely the constructed ith key structure group;
(e) Acquiring neighbor facilities w of a facility u popped up in a key structure of the positive facility network, if the facility w is not accessed and the positive neighbor number of the facility w in the key structure of the positive facility network is k, performing (f) circularly, otherwise performing (g);
(f) Marking the facility w as a facility that has been accessed and pushing w into a facility queue;
(g) Adding the currently constructed key structure group i into all key structure groups, wherein the sequence number id plus 1 represents that the current key structure group is constructed;
(h) Returning all critical structural groups.
Step five: the deletion cost for each facility in the candidate deletion set of facilities C is calculated, and for the deletion cost for facility u, it is defined as: in the critical structure of the facility network, the condition of the critical structure of the facility network is not satisfied after the facility u is deleted, so that the number of all facilities removed.
The specific method comprises the following steps: copying the key structure of the positive facility network obtained in the step two to obtain a key structure copy Q of the positive facility network, and calculating the facility quantity Q of the Q; removing a certain facility u in the candidate deleted facility set C from Q, iteratively inquiring the number of positive neighbors of each facility in Q after removing u, deleting the facilities with the number of positive neighbors smaller than k in Q until no facility capable of being deleted exists, calculating the number of the rest facilities in Q, and recording the number of the rest facilities as p, wherein the deleting cost of the facility u is Q-p.
Step six: acquiring a key structure of the attribute facility network G, wherein the key structure of the attribute facility network meets the following conditions: 1. in a critical structure of the attribute facility network, the number of positive neighbors of each facility is at least k;2. in the key structure of the attribute facility network, an unbalanced graphic structure does not exist; 3. the critical structure is extremely large, i.e., neither of the larger critical structures satisfies condition 1 nor condition 2.
The specific method comprises the following steps: selecting a facility u with the minimum deletion cost in the candidate deletion facility set C, acquiring a key structure group G of the facility u, deleting all facilities in the key structure group G from the attribute facility network G if the key structure group G exists, and deleting the facility u only in the attribute facility network G if the key structure group G of the facility u does not exist. If the attribute facility network G obtained after the facility deletion meets the condition of the key structure of the attribute facility network, outputting the attribute facility network G as the key structure of the attribute facility network, otherwise, returning to the step four.
As shown in fig. 2, for a group of facilities, two facilities having positive relationships are connected by positive edges, and two facilities having negative relationships are connected by negative edges, thus obtaining an attribute facility network. In this attribute facility network we need to obtain the key structure of the attribute facility network, we find that there is an unbalanced graph structure in fig. 2, and we can quickly obtain the key structure of the attribute facility network as shown in fig. 3 according to the method of the present invention, where each facility has at least 2 positive neighbors and there is no unbalanced graph structure.
In one embodiment, a computer device is provided that includes a memory and a processor, where the memory stores computer readable instructions that, when executed by the processor, cause the processor to perform the steps in the method for identifying a critical structure of an attribute facility network in each of the embodiments described above.
In one embodiment, a storage medium storing computer readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps in the method of identifying a critical structure of an attribute facility network in the above embodiments is presented. Wherein the storage medium may be a non-volatile storage medium.
Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be implemented by a program to instruct related hardware, the program may be stored in a computer readable storage medium, and the storage medium may include: read Only Memory (ROM), random access Memory (RAM, random Access Memory), magnetic or optical disk, and the like.
The foregoing is merely a preferred embodiment of the present invention, and the present invention has been disclosed in the above description of the preferred embodiment, but is not limited thereto. Any person skilled in the art can make many possible variations and modifications to the technical solution of the present invention or modifications to equivalent embodiments using the methods and technical contents disclosed above, without departing from the scope of the technical solution of the present invention. Therefore, any simple modification, equivalent variation and modification of the above embodiments according to the technical substance of the present invention still fall within the scope of the technical solution of the present invention.
Claims (9)
1. A method of identifying a critical structure of an attribute facility network, the method comprising the steps of:
step one: given a real attribute facility network G (V, E), where V represents the collection of all facilities in G and E represents the edges between all facilities in G; acquiring all facilities in V and all positive edges in E from the network to form a positive facility network;
an unbalanced graphic structure X (R, S) in an attribute facility network G is defined that satisfies the following conditions: all facilities in the sub-facility sets R, R and all sides S of the facilities can be enclosed into a polygon, and the number of positive sides in all sides is smaller than the number of negative sides;
step two: calculating a critical structure of the positive facility network, the critical structure satisfying two conditions: 1. each facility u in the key structure has at least k positive edges, namely, the facility u has k positive neighbors; 2. the critical structure is extremely large, i.e., any larger critical structure does not meet at least k positive neighbors per facility;
step three: putting the facilities with negative neighbors in the attribute facility network G into a candidate deletion facility set C;
step four: for each candidate deletion facility set C, calculating a key structure group of the facilities in C, the key structure group satisfying the following condition: 1. the number of neighbors of each facility in the key structure group is k;2. in the key structure group, for a certain facility u, there must be a facility v not equal to u, satisfying that u and v are in the same key structure group, and v is the positive neighbor of u;
step five: the deletion cost for each facility in the candidate deletion set of facilities C is calculated, and for the deletion cost for facility u, it is defined as: in the critical structure of the facility network, the condition of the critical structure of the facility network is not satisfied after the facility u is deleted, so that the number of all facilities removed;
step six: acquiring a key structure of the attribute facility network G, wherein the key structure of the attribute facility network meets the following conditions: 1. the number of positive neighbors of each facility in the critical structure is at least k;2. the key structure has no unbalanced graphic structure; 3. the critical structure is extremely large, i.e., any larger critical structure does not satisfy both condition 1 and condition 2;
the acquisition process specifically comprises the following steps: selecting a facility u with the minimum deletion cost in the candidate deletion facility set C, deleting all facilities in a key structure group from G if u exists in the key structure group, otherwise deleting u only in G; if the attribute facility network G obtained after the facility deletion meets the condition of the key structure of the attribute facility network, outputting the attribute facility network G as the key structure of the attribute facility network, otherwise, returning to the step four.
2. The method for identifying key structure of attribute facility network according to claim 1, wherein in the first step, if there is a positive relationship between the facility u and the facility v, the edges of the two facilities are marked as positive edges, and the facility v is called as the positive neighbor of the facility u; if there is a negative relationship between facility u and facility v, then the edges of both facilities are noted as negative edges, and facility v is referred to as the negative neighbor of facility u.
3. The method for identifying key structures of a facility network according to claim 1, wherein the acquiring the facility network in the step one specifically comprises: and accessing a certain facility u in the facility set V in the attribute facility network G, adding the facility u and the positive side of the facility u into a new attribute facility network, and continuing to access other facilities in the V after all sides of the certain facility u are accessed until all facilities are accessed, wherein the obtained new attribute facility network is the positive facility network.
4. The method for identifying key structures of a facility network according to claim 1, wherein in the second step, the key structures of the facility network are calculated specifically as follows: and inquiring a certain facility u in the positive facility network, and if the number of the positive edges of the facility u is smaller than k, iteratively deleting the positive edges of the facilities u and u until no deletable facility exists, wherein the rest of the positive facility network is a key structure.
5. A method for identifying key structures of an attribute facility network according to claim 1, wherein in the third step, in order to break an unbalanced graphic structure in the attribute facility network, facilities with negative neighbors in G are put into a candidate deletion facility set C, which is no longer all facilities in the attribute facility network G.
6. A method of identifying a critical structure of an attribute facility network according to claim 1, wherein said step four comprises the sub-steps of:
(a) Setting i to 0, wherein i is the sequence number of the key structure group currently being constructed;
(b) If there is a facility u in the candidate deletion facility set C that has not been accessed, and the number of positive neighbors of the facility u is k in the critical structure of the positive facility network, performing (C) - (g) in a loop, otherwise performing (h);
(c) Placing the facility u to be queried in a facility queue, circularly executing (d) - (f) if no facility is contained in the facility queue, otherwise executing (g);
(d) Ejecting a facility from the facility queue, and putting the facility into the current key structure group i, namely the constructed ith key structure group;
(e) Acquiring neighbor facilities w of a facility u popped up in a key structure of the positive facility network, if the facility w is not accessed and the positive neighbor number of the facility w in the key structure of the positive facility network is k, performing (f) circularly, otherwise performing (g);
(f) Marking the facility w as a facility that has been accessed and pushing w into a facility queue;
(g) Adding the currently constructed key structure group i into all key structure groups, wherein the sequence number id plus 1 represents that the current key structure group is constructed;
(h) Returning all critical structural groups.
7. The method for identifying key structures of attribute facility network according to claim 1, wherein in the fifth step, the calculation of each facility deletion cost is specifically: copying the key structure of the positive facility network obtained in the step two to obtain a key structure copy Q of the positive facility network, and calculating the facility quantity Q of the Q; removing a certain facility u in the candidate deleted facility set C from Q, iteratively inquiring the number of positive neighbors of each facility in Q after removing u, deleting the facilities with the number of positive neighbors smaller than k in Q until no facility capable of being deleted exists, calculating the number of the rest facilities in Q, and recording the number of the rest facilities as p, wherein the deleting cost of the facility u is Q-p.
8. A computer device comprising a memory and a processor, the memory having stored therein computer readable instructions that, when executed by the processor, cause the processor to perform the steps in the method of identifying a critical structure of an attribute facility network as claimed in any of claims 1-7.
9. A storage medium storing computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps in the method of identifying an attribute facility network critical structure of any of claims 1-7.
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