CN111985514A - Business circle identification method and device, electronic equipment and storage medium - Google Patents
Business circle identification method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a business circle identification method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining an interest point set corresponding to a target industry in a target area; calculating a distance matrix corresponding to the interest point set, wherein the distance matrix comprises distance information between every two interest points in the interest point set; and carrying out business area clustering identification on the interest point set according to the distance matrix, and outputting business area information. According to the embodiment of the invention, the interest point set is clustered and identified through the distance matrix of the target area and the interest points corresponding to the target industry, so that the quick and efficient identification of the business circles of the target industry is realized, the identification of the area business circles of different scales is supported, and the applicability is strong.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a business district identification method and device, electronic equipment and a storage medium.
Background
The business circle is the momentum range of business enterprises for carrying out business activities, and the emphasis expression of the business circle is the space range of business enterprises for carrying out business activities, which is equal to the concept of a business gathering area. The sales activity of a store is usually geographically bound, i.e., has a relatively stable business circle. Due to the difference of the operation commodity, the traffic factor, the geographic position, the operation scale and the like, the business circle scale and the business circle form of different shops are greatly different. Even the same store can cause the change of the business circle due to the influence of different factors at different times, for example, the original business circle is competitive, and a part of customers are attracted.
When enterprises develop business in cities (regions), the enterprises need to know the distribution of target customers in the cities (regions), namely where the target customers are gathered (the gathering region is defined as a business circle), so that targeted business development and related business strategies are made.
At present, the traditional urban Business District is generally divided by public cognition, such as a Central Business District (CBD), and with the development of big data technology, the method of dividing the urban Business District by population static density or people flow is gradually popularized, but the urban Business District division based on the distribution of the thermal population cannot meet the increasing Business expansion requirement aiming at specific industries, and at present, when an enterprise divides a Business expansion target area, a large amount of off-line investigation cost is needed, for example, manual modes such as small-range off-line stepping and the like are adopted from the cognitive area, and the modes need to consume a large amount of manpower, have low efficiency and have narrow information coverage.
Disclosure of Invention
The embodiment of the invention provides a business circle identification method, a business circle identification device, electronic equipment and a storage medium, wherein the business circle identification method, the business circle identification device, the electronic equipment and the storage medium are used for clustering and identifying an interest point set through a target area and an interest point distance matrix corresponding to a target industry, so that the business circle of the target industry can be quickly and efficiently identified, the identification of the area business circles with different scales is supported, and the applicability is strong.
In a first aspect, the present application provides a business district identification method, including:
acquiring an interest point set corresponding to a target industry in a target area;
calculating a distance matrix corresponding to the interest point set, wherein the distance matrix comprises distance information between every two interest points in the interest point set;
and carrying out business circle clustering identification on the interest point set according to the distance matrix, and outputting business circle information.
In some embodiments of the present application, the obtaining a set of interest points corresponding to a target industry in a target area includes:
acquiring a total interest point set of each industry in the target area, wherein interest points in the total interest point set correspond to interest point classifications;
determining a target interest point classification corresponding to the target industry according to a preset mapping relation between the industry and the interest point classification;
and extracting the interest points corresponding to the target interest point classification from the total interest point set to form an interest point set corresponding to the target industry.
In some embodiments of the present application, before determining a target interest point classification corresponding to the target industry according to a preset mapping relationship between industries and interest point classifications, the method further includes:
And establishing a mapping relation between each industry and the interest point classification in the target area.
In some embodiments of the present application, the calculating a distance matrix corresponding to the set of interest points includes:
respectively taking the interest points in the interest point set as target interest points, and calculating the distance between the target interest points and other interest points in the interest point set;
and obtaining the distance matrix according to the distance between the target interest point and other interest points in the interest point set.
In some embodiments of the present application, the calculating the distance between the target point of interest and the other points of interest in the set of points of interest includes:
calculating spherical distances between the target interest point and other interest points in the interest point set as distances between the target interest point and other interest points in the interest point set,
or, a preset navigation module is called to calculate the distance between the target interest point and other interest points in the interest point set,
or calling a preset navigation module to determine navigation time consumption between the target interest point and other interest points in the interest point set, and calculating the distance between the target interest point and other interest points in the interest point set according to the navigation time consumption.
In some embodiments of the present application, the performing business district clustering identification on the interest point set according to the distance matrix, and outputting business district information includes:
acquiring preset business circle identification parameters;
and carrying out business circle clustering identification on the interest point set according to the business circle identification parameters and the distance matrix, and outputting business circle information.
In some embodiments of the present application, the obtaining of the preset business turn identification parameter includes:
acquiring a preset quotient ring limit set R, wherein R is [ d1, d2, n1 and n2], d1 is the maximum distance limit of two adjacent interest points in a single quotient ring cluster, d2 is the maximum distance limit of any interest point in the single quotient ring cluster from the center of the quotient ring cluster, n1 is the minimum interest point number limit formed by the single quotient ring cluster, and n2 is the interest point number limit formed by the single quotient ring cluster.
In some embodiments of the present application, the performing business district clustering identification on the interest point set according to the business district identification parameter and the distance matrix, and outputting business district information includes:
randomly selecting k interest points from the interest point set as initial quotient circle cluster centers, wherein k is a positive integer and is more than 1 and less than or equal to n 2;
According to the distance between each interest point in the interest point set and the center of each business circle cluster in the distance matrix, on the premise of meeting the business circle limit set, allocating each interest point in the interest point set to the business circle cluster closest to the current interest point so as to cluster to form a business circle cluster;
when interest points in the target business circle change, recalculating the center of the target business circle cluster until no interest point in the interest point set is reallocated to a different business circle cluster, or no business circle cluster center in the business circle cluster formed by clustering changes again, and outputting business circle information by taking the business circle cluster as a unit.
In a second aspect, the present application provides a business district identification apparatus, including:
the acquisition unit is used for acquiring an interest point set corresponding to a target industry in a target area;
the calculation unit is used for calculating a distance matrix corresponding to the interest point set, and the distance matrix comprises distance information between every two interest points in the interest point set;
and the output unit is used for carrying out business circle clustering identification on the interest point set according to the distance matrix and outputting business circle information.
In some embodiments of the present application, the obtaining unit is specifically configured to:
Acquiring a total interest point set of each industry in the target area, wherein interest points in the total interest point set correspond to interest point classifications;
determining a target interest point classification corresponding to the target industry according to a preset mapping relation between the industry and the interest point classification;
and extracting the interest points corresponding to the target interest point classification from the total interest point set to form an interest point set corresponding to the target industry.
In some embodiments of the present application, the business district identification apparatus further includes:
the establishing unit is used for establishing the mapping relation between each industry and the interest point classification in the target area before determining the target interest point classification corresponding to the target industry according to the preset mapping relation between the industry and the interest point classification.
In some embodiments of the present application, the computing unit is specifically configured to:
respectively taking the interest points in the interest point set as target interest points, and calculating the distance between the target interest points and other interest points in the interest point set;
and obtaining the distance matrix according to the distance between the target interest point and other interest points in the interest point set.
In some embodiments of the present application, the computing unit is specifically configured to:
Calculating spherical distances between the target interest point and other interest points in the interest point set as distances between the target interest point and other interest points in the interest point set,
or calling a preset navigation module to obtain the distance between the target interest point and other interest points in the interest point set,
or calling a preset navigation module to determine navigation time consumption between the target interest point and other interest points in the interest point set, and calculating the distance between the target interest point and other interest points in the interest point set according to the navigation time consumption.
In some embodiments of the present application, the output unit is specifically configured to:
acquiring preset business circle identification parameters;
and carrying out business circle clustering identification on the interest point set according to the business circle identification parameters and the distance matrix, and outputting business circle information.
In some embodiments of the present application, the output unit is specifically configured to:
acquiring a preset quotient ring limit set R, wherein R is [ d1, d2, n1 and n2], d1 is the maximum distance limit of two adjacent interest points in a single quotient ring cluster, d2 is the maximum distance limit of any interest point in the single quotient ring cluster from the center of the quotient ring cluster, n1 is the minimum interest point number limit formed by the single quotient ring cluster, and n2 is the interest point number limit formed by the single quotient ring cluster.
In some embodiments of the present application, the output unit is specifically configured to:
randomly selecting k interest points from the interest point set as initial quotient circle cluster centers, wherein k is a positive integer and is more than 1 and less than or equal to n 2;
according to the distance between each interest point in the interest point set and the center of each business circle cluster in the distance matrix, on the premise of meeting the business circle limit set, allocating each interest point in the interest point set to the business circle cluster closest to the current interest point so as to cluster to form a business circle cluster;
when interest points in the target business circle change, recalculating the center of the target business circle cluster until no interest point in the interest point set is reallocated to a different business circle cluster, or no business circle cluster center in the business circle cluster formed by clustering changes again, and outputting business circle information by taking the business circle cluster as a unit.
In a third aspect, the present application provides an electronic device, comprising:
one or more processors;
a memory; and
one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the business turn identification method of any of the first aspects.
In a fourth aspect, the present application provides a storage medium storing a plurality of instructions, the instructions being suitable for being loaded by a processor to execute the steps in the business turn identification method according to any one of the first aspect.
The method comprises the steps of obtaining an interest point set corresponding to a target industry in a target area; calculating a distance matrix corresponding to the interest point set, wherein the distance matrix comprises distance information between every two interest points in the interest point set; and carrying out business area clustering identification on the interest point set according to the distance matrix, and outputting business area information. According to the embodiment of the invention, the interest point set is clustered and identified through the distance matrix of the target area and the interest points corresponding to the target industry, so that the quick and efficient identification of the business circles of the target industry is realized, the identification of the area business circles of different scales is supported, and the applicability is strong.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flow chart of an embodiment of a business circle identification method according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of an embodiment of step 101 in a business turn identification method according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating an embodiment of step 102 in a business turn identification method according to an embodiment of the present invention;
fig. 4 is a flowchart illustrating an embodiment of step 103 in the business turn identification method according to the embodiment of the present invention;
fig. 5 is a schematic structural diagram of an embodiment of a business circle identification device provided in an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an embodiment of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention. Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
In this application, the word "exemplary" is used to mean "serving as an example, instance, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to make and use the invention. In the following description, details are set forth for the purpose of explanation. It will be apparent to one of ordinary skill in the art that the present invention may be practiced without these specific details. In other instances, well-known structures and processes are not shown in detail to avoid obscuring the description of the invention with unnecessary detail. Thus, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.
Embodiments of the present invention provide a business turn identification method, a business turn identification device, an electronic device, and a storage medium, which are described in detail below.
First, an embodiment of the present invention provides a business circle identification method, where the business circle identification method includes: acquiring an interest point set corresponding to a target industry in a target area; calculating a distance matrix corresponding to the interest point set, wherein the distance matrix comprises distance information between every two interest points in the interest point set; and carrying out business circle clustering identification on the interest point set according to the distance matrix, and outputting business circle information.
As shown in fig. 1, which is a schematic flow chart of an embodiment of a business circle identification method in an embodiment of the present invention, the business circle identification method is applied to a business circle identification device, the business circle identification device may be located in an electronic device, and the business circle identification method may include:
s101, acquiring an interest point set corresponding to a target industry in a target area.
The target region is a geographic region, for example, a certain urban region, specifically, shenzhen city, or a certain region of a certain city, for example, shenzhen futian region, and it can be understood that, in the process of practical application, the target region may also be a region larger than the city, for example, province, country, etc., or a region smaller than the urban region, for example, county, street, etc., and is not limited herein specifically.
The industry refers to the detailed division of the operation units or the individual organization structure systems of the same-property production in national economy or other economic societies, such as restaurants, real estate, clothing industry and the like. The target industry may refer to a predetermined industry of business circles to be analyzed.
A Point of interest (POI) refers to a building with a geographic marking meaning in a local area, and is subdivided into organizations, shops, units, and the like. The interest points in the geographic information system are independent geographic marker points, which are usually organized according to interest point types, the interest points are independent from each other, and each interest point mainly includes information such as type, name, address, geographic position coordinates, and the like, so as to provide Location Based Service (LBS) such as positioning, navigation, query, and the like.
S102, calculating a distance matrix corresponding to the interest point set, wherein the distance matrix comprises distance information between every two interest points in the interest point set.
In mathematics, a distance matrix is a matrix (i.e., a two-dimensional array) that contains a set of distances between points. Thus, given N points in euclidean space, the distance matrix is an N × N symmetric matrix with non-negative real numbers as elements. The number of pairs between two of these points, N (N-1)/2, is the number of independent elements in the distance matrix. In the embodiment of the present invention, the point in the distance matrix refers to an interest point, and the distance matrix includes distance information between every two interest points in the interest point set.
S103, carrying out business circle clustering identification on the interest point set according to the distance matrix, and outputting business circle information.
The method comprises the steps of obtaining an interest point set corresponding to a target industry in a target area; calculating a distance matrix corresponding to the interest point set, wherein the distance matrix comprises distance information between every two interest points in the interest point set; and carrying out business area clustering identification on the interest point set according to the distance matrix, and outputting business area information. According to the embodiment of the invention, the interest point set is clustered and identified through the distance matrix of the target area and the interest points corresponding to the target industry, so that the quick and efficient identification of the business circles of the target industry is realized, the identification of the area business circles of different scales is supported, and the applicability is strong.
In some embodiments of the present invention, there are multiple ways to obtain the interest point set corresponding to the target industry in the target area, and one way is to obtain all the interest points in the target area, and obtain the interest point set corresponding to the target industry in the target area by obtaining the interest points of the user marked target industry. Another way is that as shown in fig. 2, the acquiring of the interest point set corresponding to the target industry in the target area in step S101 may specifically include:
s201, acquiring a total set of interest points of each industry in the target area.
And each interest point in the total interest point set corresponds to an interest point classification. For example, the point of interest corresponding to point of interest a is classified as a restaurant. In the embodiment of the present invention, a point of interest itself may include the information in the following table 1:
TABLE 1
| POI classification | POI name | Address | Longitude (G) | Latitude |
I.e. a point of interest inclusion may include a corresponding point of interest classification (POI classification), point of interest name (POI name), address, longitude and latitude information.
Specifically, a preset Geographic Information System (GIS) Application Programming Interface (API) may be called in the electronic device to obtain a total set of points of interest of each industry in the target area.
S202, determining a target interest point classification corresponding to the target industry according to a preset mapping relation between the industry and the interest point classification.
Since one industry may correspond to a plurality of interest point classifications, in the embodiment of the present invention, before determining the target interest point classification corresponding to the target industry according to the preset mapping relationship between the industry and the interest point classification, the mapping relationship between each industry and the interest point classification in the target area may be pre-established. For example, if a pharmaceutical enterprise needs to rapidly popularize a newly marketed drug in a city, it needs to know the distribution of POIs in the city of its dealers, such as hospitals, community health stations, pharmacies, etc., and provide a reference for its rapid development of business negotiation and subsequent operation planning related to logistics (e.g., where a drug warehouse is located, which can meet downstream requirements as much as possible with low cost and high efficiency), so that a mapping relationship between industries and interest point classifications in a target area can be established in advance, that is, the method further includes: and establishing a mapping relation between each industry and the interest point classification in the target area. This forms the mapping as shown in table 2 below:
TABLE 2
| Industry | POI classification | POI name | Address | Longitude (G) | Latitude |
In table 2, the interest point classification and the industry establish a corresponding mapping relationship. According to the pre-established mapping relation between industries and interest points, the interest point classification corresponding to the target industry can be determined.
S203, extracting the interest points corresponding to the target interest point classification from the interest point total set to form an interest point set corresponding to the target industry.
Since the interest point classification corresponding to the target industry is determined in step S202, and the interest points have corresponding interest point classifications, the interest points corresponding to the target interest point classification may be extracted from the total interest point set to form the interest point set corresponding to the target industry. For example, assuming that the target industry is the pharmaceutical industry, the corresponding interest points are classified as "medical", and the primary interest point classification number is 10, the interest points corresponding to the "medical" interest point classification are extracted from the total interest point set to form an interest point set corresponding to the "pharmaceutical" industry.
In some embodiments of the present invention, as shown in fig. 3, the calculating a distance matrix corresponding to the interest point set in step S102 may specifically include:
s301, respectively taking the interest points in the interest point set as target interest points, and calculating the distance between the target interest points and other interest points in the interest point set.
There are multiple calculation methods for calculating the distance between the target interest point and other interest points in the interest point set, specifically as follows:
(1) and calculating the spherical distance between the target interest point and other interest points in the interest point set as the distance between the target interest point and other interest points in the interest point set.
The position of a certain point on the earth surface is determined by latitude and longitude, and the spherical distance of the two points can be obtained by knowing the latitude and longitude of the two points. Assuming a target interest point A, a latitude angle beta 1 and a longitude angle alpha 1; the other interest points B in the set of interest points, the latitude angle β 2, the longitude angle α 2. The spherical distance S between a and B is r · arc cos [ cos β 1cos β 2cos (α 1- α 2) + sin β 1sin β 2], where r is the sphere radius, i.e., the earth radius.
(2) And calling a preset navigation module to calculate the distance between the target interest point and other interest points in the interest point set.
Specifically, the navigation distance may be called by calling a preset GIS API to obtain the navigation distance between the target interest point and the other interest points in the interest point set as the distance between the target interest point and the other interest points in the interest point set.
(3) And calling a preset navigation module to determine the navigation consumed time between the target interest point and other interest points in the interest point set, and calculating the distance between the target interest point and other interest points in the interest point set according to the navigation consumed time.
Specifically, the navigation time consumption between the target interest point and other interest points in the interest point set can be obtained by calling a preset GIS API, and the distance between the target interest point and other interest points in the interest point set is calculated according to the navigation time consumption. The way of calculating the distance specifically according to the time consumed by navigation may refer to the existing way, which is not specifically illustrated here.
The modes (2) and (3) aim at scenes with high precision and high requirements, such as scenes which need to strictly limit the range of business circles by actual traffic distance or time consumption.
S302, obtaining the distance matrix according to the distance between the target interest point and other interest points in the interest point set.
Since the distances between the target interest point and other interest points in the other interest point sets have already been calculated in step S202. And each interest point is taken as a target interest point to perform the calculation. Therefore, the distance between each two interest points in the interest point set is calculated in step S202, and the distance matrix can be obtained by matrix representation.
As shown in fig. 4, in some embodiments of the present invention, the performing, in step S103, quotient-circle cluster recognition on the interest point set according to the distance matrix, and outputting quotient-circle information may specifically include:
s401, acquiring preset business circle identification parameters.
Specifically, the acquiring of the preset business circle identification parameter includes:
acquiring a preset quotient ring limit set R, wherein R is [ d1, d2, n1 and n2], d1 is the maximum distance limit of two adjacent interest points in a single quotient ring cluster, d2 is the maximum distance limit of any interest point in the single quotient ring cluster from the center of the quotient ring cluster, n1 is the minimum interest point number limit formed by the single quotient ring cluster, and n2 is the interest point number limit formed by the single quotient ring cluster.
S402, carrying out business circle clustering identification on the interest point set according to the business circle identification parameters and the distance matrix, and outputting business circle information.
Specifically, the performing business circle cluster recognition on the interest point set according to the business circle recognition parameter and the distance matrix, outputting business circle information, performing clustering by using an improved k-means algorithm, that is, clustering under a condition of adding business attention (i.e., the business circle limit set R in step S401), obtaining cluster members and cluster performance when 1< k < ═ n2, selecting an optimal k value under a specified sample by using an inflection point method, specifically, performing business circle cluster recognition on the interest point set according to the business circle recognition parameter and the distance matrix, and outputting business circle information may include:
Randomly selecting k interest points from the interest point set as initial quotient circle cluster centers, wherein k is a positive integer and is not less than 1 and not more than n2, and k can be preset;
according to the distance between each interest point in the interest point set and the center of each business circle cluster in the distance matrix, on the premise of meeting the business circle limit set, allocating each interest point in the interest point set to the business circle cluster closest to the current interest point so as to cluster to form a business circle cluster;
when interest points in the target business circle change, recalculating the center of the target business circle cluster until no interest point in the interest point set is reallocated to a different business circle cluster, or no business circle cluster center in the business circle cluster formed by clustering changes again, and outputting business circle information by taking the business circle cluster as a unit. The longitude and the latitude of the center of the target business circle cluster are respectively equal to the average latitude of each interest point in the target business circle and the average longitude of each interest point in the target business circle.
The clustering process is described by taking a specific example as follows;
a) let k be i, i be 1, … …, n 2;
b) and randomly selecting k POIs from the POI set P (interest point set) as initial quotient circle cluster centers.
c) Then, according to the distance D between each POI in the P and the center of each business district cluster, each POI is allocated to the business district cluster closest to the POI on the premise of meeting the business district limit set R;
d) when the members of the business circle cluster change, the center of the business circle cluster is recalculated, the new center of the business circle cluster is (the average latitude in the new business circle cluster, the average longitude in the new business circle cluster), and the process is repeated continuously until any of the following termination conditions is met:
(1) no (or minimum number of) objects (points of interest) are reassigned to different quotient circle clusters;
(2) no (or a minimum number) business circle cluster centers change again.
The business circle is clustered and identified through the improved k-means algorithm, so that the business circle is identified more accurately and more efficiently.
In some embodiments of the present invention, the result of the business circle cluster identification is recombined based on actual business requirements, and if it is considered that the calculated area of the business circle is too small, two or more adjacent business circles need to be merged or split, and the business circle processing may be performed again, taking merging as an example, specifically: and receiving a user business circle merging instruction, and merging the first business circle and the second business circle which are formed by clustering.
It should be noted that, after the business circles are formed in the clusters, the business circle information that is output may be output as a business circle identifier (e.g., 1, 2, 3, 4), and then the information of each corresponding interest point in each business circle, such as the content recorded in table 2, which is not limited herein.
In order to better implement the business district identification method in the embodiment of the present invention, on the basis of the business district identification method, the embodiment of the present invention further provides a business district identification apparatus, the business district identification apparatus is located in an electronic device, as shown in fig. 5, the business district identification apparatus 500 may include:
an obtaining unit 501, configured to obtain a set of interest points corresponding to a target industry in a target area;
a calculating unit 502, configured to calculate a distance matrix corresponding to the interest point set, where the distance matrix includes distance information between every two interest points in the interest point set;
and the output unit 503 is configured to perform business area clustering identification on the interest point set according to the distance matrix, and output business area information.
In some embodiments of the present application, the obtaining unit 501 is specifically configured to:
acquiring a total interest point set of each industry in the target area, wherein interest points in the total interest point set correspond to interest point classifications;
Determining a target interest point classification corresponding to the target industry according to a preset mapping relation between the industry and the interest point classification;
and extracting the interest points corresponding to the target interest point classification from the total interest point set to form an interest point set corresponding to the target industry.
In some embodiments of the present application, the business district identification apparatus 500 further includes:
the establishing unit is used for establishing the mapping relation between each industry and the interest point classification in the target area before determining the target interest point classification corresponding to the target industry according to the preset mapping relation between the industry and the interest point classification.
In some embodiments of the present application, the calculating unit 502 is specifically configured to:
respectively taking the interest points in the interest point set as target interest points, and calculating the distance between the target interest points and other interest points in the interest point set;
and obtaining the distance matrix according to the distance between the target interest point and other interest points in the interest point set.
In some embodiments of the present application, the calculating unit 502 is specifically configured to:
calculating spherical distances between the target interest point and other interest points in the interest point set as distances between the target interest point and other interest points in the interest point set,
Or calling a preset navigation module to obtain the distance between the target interest point and other interest points in the interest point set,
or calling a preset navigation module to determine navigation time consumption between the target interest point and other interest points in the interest point set, and calculating the distance between the target interest point and other interest points in the interest point set according to the navigation time consumption.
In some embodiments of the present application, the output unit 503 is specifically configured to:
acquiring preset business circle identification parameters;
and carrying out business circle clustering identification on the interest point set according to the business circle identification parameters and the distance matrix, and outputting business circle information.
In some embodiments of the present application, the output unit 503 is specifically configured to:
acquiring a preset quotient ring limit set R, wherein R is [ d1, d2, n1 and n2], d1 is the maximum distance limit of two adjacent interest points in a single quotient ring cluster, d2 is the maximum distance limit of any interest point in the single quotient ring cluster from the center of the quotient ring cluster, n1 is the minimum interest point number limit formed by the single quotient ring cluster, and n2 is the interest point number limit formed by the single quotient ring cluster.
In some embodiments of the present application, the output unit 503 is specifically configured to:
Randomly selecting k interest points from the interest point set as initial quotient circle cluster centers, wherein k is a positive integer and is more than 1 and less than or equal to n 2;
according to the distance between each interest point in the interest point set and the center of each business circle cluster in the distance matrix, on the premise of meeting the business circle limit set, allocating each interest point in the interest point set to the business circle cluster closest to the current interest point so as to cluster to form a business circle cluster;
when interest points in the target business circle change, recalculating the center of the target business circle cluster until no interest point in the interest point set is reallocated to a different business circle cluster, or no business circle cluster center in the business circle cluster formed by clustering changes again, and outputting business circle information by taking the business circle cluster as a unit.
The embodiment of the present invention further provides an electronic device, which integrates any one of the business district identification apparatuses provided by the embodiments of the present invention, and the electronic device includes:
one or more processors;
a memory; and
one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the processor for performing the steps of the business turn identification method in any of the above embodiments of the log collection method.
The embodiment of the invention also provides electronic equipment which integrates any business district identification device provided by the embodiment of the invention. As shown in fig. 6, it shows a schematic structural diagram of an electronic device according to an embodiment of the present invention, specifically:
the electronic device may include components such as a processor 601 of one or more processing cores, memory 602 of one or more computer-readable storage media, a power supply 603, and an input unit 604. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 6 does not constitute a limitation of the electronic device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components. Wherein:
the processor 601 is a control center of the electronic device, connects various parts of the whole electronic device by using various interfaces and lines, and performs various functions of the electronic device and processes data by operating or executing software programs and/or modules stored in the memory 602 and calling data stored in the memory 602, thereby performing overall monitoring of the electronic device. Optionally, processor 601 may include one or more processing cores; preferably, the processor 601 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 601.
The memory 602 may be used to store software programs and modules, and the processor 601 executes various functional applications and data processing by operating the software programs and modules stored in the memory 602. The memory 602 may mainly include a program storage area and a data storage area, wherein the program storage 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 created according to use of the electronic device, and the like. Further, the memory 602 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 602 may also include a memory controller to provide the processor 601 with access to the memory 602.
The electronic device further comprises a power supply 603 for supplying power to the various components, and preferably, the power supply 603 is logically connected to the processor 601 through a power management system, so that functions of managing charging, discharging, power consumption, and the like are realized through the power management system. The power supply 603 may also include any component of one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and the like.
The electronic device may further include an input unit 604, and the input unit 604 may be used to receive input numeric or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.
Although not shown, the electronic device may further include a display unit and the like, which are not described in detail herein. Specifically, in this embodiment, the processor 601 in the electronic device loads the executable file corresponding to the process of one or more application programs into the memory 602 according to the following instructions, and the processor 601 runs the application program stored in the memory 602, thereby implementing various functions as follows:
acquiring an interest point set corresponding to a target industry in a target area;
calculating a distance matrix corresponding to the interest point set, wherein the distance matrix comprises distance information between every two interest points in the interest point set;
and carrying out business circle clustering identification on the interest point set according to the distance matrix, and outputting business circle information.
It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions or by associated hardware controlled by the instructions, which may be stored in a computer readable storage medium and loaded and executed by a processor.
To this end, an embodiment of the present invention provides a storage medium, which may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like. The storage medium has stored therein a plurality of instructions that can be loaded by the processor to perform the steps of any of the business district identification methods provided by the embodiments of the present invention. For example, the instructions may perform the steps of:
acquiring an interest point set corresponding to a target industry in a target area;
calculating a distance matrix corresponding to the interest point set, wherein the distance matrix comprises distance information between every two interest points in the interest point set;
and carrying out business circle clustering identification on the interest point set according to the distance matrix, and outputting business circle information.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and parts that are not described in detail in a certain embodiment may refer to the above detailed descriptions of other embodiments, and are not described herein again.
In a specific implementation, each unit or structure may be implemented as an independent entity, or may be combined arbitrarily to be implemented as one or several entities, and the specific implementation of each unit or structure may refer to the foregoing method embodiment, which is not described herein again.
The above operations can be implemented in the foregoing embodiments, and are not described in detail herein.
The business turn identification method, the business turn identification device, the electronic device and the storage medium provided by the embodiment of the invention are described in detail, a specific example is applied in the text to explain the principle and the implementation of the invention, and the description of the embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, for those skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A business circle identification method is characterized by comprising the following steps:
acquiring an interest point set corresponding to a target industry in a target area;
calculating a distance matrix corresponding to the interest point set, wherein the distance matrix comprises distance information between every two interest points in the interest point set;
and carrying out business circle clustering identification on the interest point set according to the distance matrix, and outputting business circle information.
2. The business circle identification method according to claim 1, wherein the obtaining of the interest point set corresponding to the target industry in the target area comprises:
Acquiring a total interest point set of each industry in the target area, wherein interest points in the total interest point set correspond to interest point classifications;
determining a target interest point classification corresponding to the target industry according to a preset mapping relation between the industry and the interest point classification;
and extracting the interest points corresponding to the target interest point classification from the total interest point set to form an interest point set corresponding to the target industry.
3. The business turn identification method according to claim 1, wherein the calculating of the distance matrix corresponding to the interest point set comprises:
respectively taking the interest points in the interest point set as target interest points, and calculating the distance between the target interest points and other interest points in the interest point set;
and obtaining the distance matrix according to the distance between the target interest point and other interest points in the interest point set.
4. The business turn identification method of claim 3, wherein said calculating distances between the target point of interest and other points of interest in the set of points of interest comprises:
calculating spherical distances between the target interest point and other interest points in the interest point set as distances between the target interest point and other interest points in the interest point set,
Or, a preset navigation module is called to calculate the distance between the target interest point and other interest points in the interest point set,
or calling a preset navigation module to determine navigation time consumption between the target interest point and other interest points in the interest point set, and calculating the distance between the target interest point and other interest points in the interest point set according to the navigation time consumption.
5. The business circle identification method of claim 1, wherein the business circle clustering identification of the interest point set according to the distance matrix and outputting business circle information comprises:
acquiring preset business circle identification parameters;
and carrying out business circle clustering identification on the interest point set according to the business circle identification parameters and the distance matrix, and outputting business circle information.
6. The business district identification method according to claim 5, wherein the obtaining of the preset business district identification parameters comprises:
acquiring a preset quotient ring limit set R, wherein R is [ d1, d2, n1 and n2], d1 is the maximum distance limit of two adjacent interest points in a single quotient ring cluster, d2 is the maximum distance limit of any interest point in the single quotient ring cluster from the center of the quotient ring cluster, n1 is the minimum interest point number limit formed by the single quotient ring cluster, and n2 is the interest point number limit formed by the single quotient ring cluster.
7. The business circle identification method of claim 6, wherein the business circle cluster identification of the interest point set according to the business circle identification parameters and the distance matrix and the output of business circle information comprise:
randomly selecting k interest points from the interest point set as initial quotient circle cluster centers, wherein k is a positive integer and is more than 1 and less than or equal to n 2;
according to the distance between each interest point in the interest point set and the center of each business circle cluster in the distance matrix, on the premise of meeting the business circle limit set, allocating each interest point in the interest point set to the business circle cluster closest to the current interest point so as to cluster to form a business circle cluster;
when interest points in the target business circle change, recalculating the center of the target business circle cluster until no interest point in the interest point set is reallocated to a different business circle cluster, or no business circle cluster center in the business circle cluster formed by clustering changes again, and outputting business circle information by taking the business circle cluster as a unit.
8. A business turn identifying device, characterized in that it comprises:
the acquisition unit is used for acquiring an interest point set corresponding to a target industry in a target area;
The calculation unit is used for calculating a distance matrix corresponding to the interest point set, and the distance matrix comprises distance information between every two interest points in the interest point set;
and the output unit is used for carrying out business circle clustering identification on the interest point set according to the distance matrix and outputting business circle information.
9. An electronic device, characterized in that the electronic device comprises:
one or more processors;
a memory; and
one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the business turn identification method of any one of claims 1 to 7.
10. A storage medium storing a plurality of instructions adapted to be loaded by a processor to perform the steps of the business turn identification method of any one of claims 1 to 7.
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