CN112395486A - Broadband service recommendation method, system, server and storage medium - Google Patents
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Abstract
The invention discloses a method, a system, a server and a storage medium for recommending broadband services, wherein user data information of a POI (point of interest) label is collected, and the user data information at least comprises user information and longitude and latitude information; cleaning the user data information to obtain potential user data information; carrying out correlation analysis on longitude and latitude information of the potential user data information and broadband service information; and recommending the broadband service to the potential user according to the correlation analysis result. And establishing a geographical position dimension relation between the user and the broadband resource, deeply excavating the target client according to the construction condition of the resource, and reasonably distributing the resource according to the distribution of the user.
Description
Technical Field
The invention relates to the technical field of mobile communication, in particular to a broadband service recommendation method, a system, a server and a storage medium.
Background
With the advent of the 5G era and the continuous popularization of the internet of things technology, the market share of broadband users has become a focus of attention of various operators. In the big data era, with the development of internet technology and the continuous and deep application of machine learning models, operators begin to utilize the technical means to mine potential customers, so as to improve the commodity conversion rate or the success rate of business handling.
Currently, each large operator mainly adopts a big data technology or an artificial intelligence method to recommend broadband services to users, and the prior art mainly has three processes: according to the steps of collection → analysis → recommendation, the collected user information, the information of the communication behavior (such as ARUP value, call attribution, network access time and the like) of the user and other characteristics of the user are classified as system input, a proper recommendation algorithm is utilized to obtain a client suitable for recommendation, and the broadband service is recommended to the user according to the personalization degree and the information sending mode set by the user or the outbound mode.
However, although the broadband service recommendation module of each large operator can recommend services to a certain extent and improve the success rate of service transaction, the following problems still exist:
the valuable POI user data volume obtained by the existing service recommendation module is rare and the classification is incomplete. For example, only dozens of hotel customers are inquired in the Chongqing Yubei district in the BOSS system, but 1000 pieces of data can be obtained through electronic map POI label inquiry, and the user data of the BOSS system of the current operator is not marked strictly according to hospitals, schools, hotels, markets, companies and office buildings, so that a data basis cannot be provided for development business of customized scenes.
The user portrait and the commodity portrait can change along with the development of time, parameters of the established model need to be modified frequently, for example, the distribution of a base station can change along with the distribution of time, the number of ports and the coverage condition can be different every month, and the current service recommendation module does not have data with other dimensions to correct user characteristics.
The method for screening effective customer selections is limited, accurate positioning of user selections cannot be achieved, data cleaning cannot be performed on extracted customers, and real valuable customers can be obtained.
The current service recommendation system can only recommend broadband services, and cannot realize deep mining of users and fine layout of the broadband services according to the distribution conditions of the users.
Disclosure of Invention
In view of the above problems, the present invention has been made to provide a broadband service recommendation system and a corresponding broadband service recommendation method that overcome or at least partially solve the above problems.
According to an aspect of the present invention, there is provided a method for recommending broadband services, comprising the steps of:
collecting user data information of the POI labels, wherein the user data information at least comprises user information and longitude and latitude information;
cleaning the user data information to obtain potential user data information;
carrying out correlation analysis on longitude and latitude information of the potential user data information and broadband service information;
and recommending the broadband service to the potential user according to the correlation analysis result.
Optionally, the step of collecting the user data information of the POI tag further comprises:
selecting a target area and a POI group;
according to the crawler technology, user data information of POI labels in each POI group is sequentially captured through an open interface of an electronic map server;
wherein the user data information further comprises: user evaluation information and user contact information.
Optionally, the step of cleaning the user data information to obtain the potential user data information further includes:
cleaning the user data information according to the background resource table, and removing the user data information of the accepted user;
the step of performing correlation analysis on the longitude and latitude information of the potential user data information and the broadband service information further comprises the following steps:
obtaining a user representation of the potential user according to the potential user data information;
obtaining a broadband service portrait according to the broadband service information; the broadband service information comprises broadband distribution information, and the broadband distribution information is marked according to longitude and latitude information;
and carrying out correlation analysis on the user portrait of the potential user and the broadband service portrait.
Optionally, the step of cleaning the user data information to obtain the potential user data information further includes:
cleaning the user data information according to the background resource table, and removing the user data information of the accepted user;
the step of performing correlation analysis on the longitude and latitude information of the potential user data information and the broadband service information further comprises the following steps:
obtaining a user representation of the potential user according to the potential user data information;
obtaining a broadband service portrait according to the broadband service information; the broadband service information comprises broadband distribution information, and the broadband distribution information is marked according to longitude and latitude information;
and carrying out correlation analysis on the user portrait of the potential user and the broadband service portrait.
According to another aspect of the present invention, a system for broadband service recommendation includes:
the system comprises a collecting module, a searching module and a searching module, wherein the collecting module is used for collecting user data information of the POI labels, and the user data information at least comprises user information and longitude and latitude information;
the screening module is used for cleaning the user data information to obtain potential user data information;
the correlation module is used for performing correlation analysis on the longitude and latitude information of the potential user data information and the broadband service information;
and the recommending module is used for recommending the broadband service to the potential user according to the correlation analysis result.
Optionally, the collection module is further configured to:
selecting a target area and a POI group;
according to the crawler technology, user data information of POI labels in each POI group is sequentially captured through an open interface of an electronic map server;
wherein the user data information further comprises: user evaluation information and user contact information.
Optionally, the screening module is further configured to:
cleaning the user data information according to the background resource table, and removing the user data information of the accepted user;
the association module is further to:
obtaining a user representation of the potential user according to the potential user data information;
obtaining a broadband service portrait according to the broadband service information; the broadband service information comprises broadband distribution information, and the broadband distribution information is marked according to longitude and latitude information;
and carrying out correlation analysis on the user portrait of the potential user and the broadband service portrait.
Optionally, the recommendation module is further configured to:
establishing a recommendation model according to the correlation analysis result and the collaborative filtering recommendation method; the collaborative filtering recommendation method is characterized in that collaborative filtering is carried out according to the user data information of the accepted historical users and the user data information of the target recommendation user determined according to the correlation analysis result;
and recommending the broadband service according to the recommendation model.
According to yet another aspect of the present invention, a server comprises: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the broadband service recommendation method.
According to still another aspect of the present invention, a computer storage medium has at least one executable instruction stored therein, and the executable instruction causes a processor to perform operations corresponding to the broadband service recommendation method as described above.
The method and the system for recommending the broadband service acquire a large amount of user data based on the POI interface of the electronic map, and perform data cleaning according to the grading, the regional distribution and the distribution condition of broadband service resources of the user to acquire more and more valuable potential customer data; and establishing a geographical position dimension relation between the user and the broadband resource, deeply excavating the target client according to the construction condition of the resource, and reasonably distributing the resource according to the distribution of the user.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a flowchart illustrating a method for recommending broadband services according to an embodiment of the present invention;
fig. 2 illustrates a longitude and latitude model of the earth for a broadband service recommendation method according to an embodiment of the present invention;
fig. 3 shows a flow of implementing collaborative filtering of a broadband service recommendation method according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a broadband service recommendation system according to an embodiment of the present invention;
fig. 5 shows a schematic structural diagram of a server according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
With the interface service opened by the API capability opening platform of each large electronic map, the POI information data specified by the user can be acquired by calling the interface service. POI is an abbreviation for "Point of Interest" and Chinese can be translated into "points of Interest". In the geographic information system, one POI may be a house, a shop, a mailbox, a bus station, etc., and each POI contains four pieces of information, name, category, coordinates, classification.
Example one
Fig. 1 is a method for recommending broadband services according to an exemplary embodiment of the present invention, including the following steps:
s11: and collecting user data information of the POI labels, wherein the user data information at least comprises user information and longitude and latitude information.
As a preferred implementation manner of this embodiment, the step of collecting the user data information of the POI tag further includes:
selecting a target area and a POI group;
according to the crawler technology, user data information of POI labels in each POI group is sequentially captured through an open interface of an electronic map server;
wherein the user data information further comprises: user evaluation information and user contact information.
In this step, the user evaluation information includes a user score and a scoring time. And acquiring user data information by utilizing a crawler technology. At present, each electronic map limits the crawler technology, and generally limits the number of single inquiry, so that to acquire all hotels in Chongqing Yubei areas of a Baidu map, the longitude and latitude parameters of an inquiry interface API are sliced about a longitude and latitude area, so that the slices are small enough, and data of all users in the area are acquired. The data includes information such as the name of the hotel, longitude and latitude information of the hotel, user rating, rating time, contact information, and the like, which is specifically shown in table 1.
Table 1 sample data obtained (part of data has been replaced by;)
S12: and cleaning the user data information to obtain potential user data information.
S13: and performing correlation analysis on the longitude and latitude information of the potential user data information and the broadband service information.
As a preferred implementation manner of this embodiment, the step of cleaning the user data information to obtain the potential user data information further includes:
and cleaning the user data information according to the background resource table, and removing the user data information of the accepted user.
The step of performing correlation analysis on the longitude and latitude information of the potential user data information and the broadband service information further comprises the following steps:
obtaining a user representation of the potential user according to the potential user data information;
obtaining a broadband service portrait according to the broadband service information; the broadband service information comprises broadband distribution information, and the broadband distribution information is marked according to longitude and latitude information;
and carrying out correlation analysis on the user portrait of the potential user and the broadband service portrait.
In the step, after the data of the user is obtained, the data needs to be cleaned according to a certain method to obtain the potential user, the scheme adopts a TOP-K algorithm according to comprehensive scores, the users are sorted according to a time dimension, weights are manually set according to information such as the type and the value of commodities, and the value potential user data is obtained.
Meanwhile, after user data is acquired, certain analysis needs to be carried out on the data, firstly, longitude and latitude marking is carried out on the data of the business, for example, if an operator wants to recommend wide business in Chongqing Yubei district, the longitude and latitude information and the distribution condition of the broadband are required to be correspondingly stored in a database, and the user development record in the district is stored in the database, so that a sales model is established; if a company wants to develop products of hotels in northern Chongqing areas, the product distribution and sales records of the company need to be correspondingly stored in a database, and a certain sales model is established. The technical scheme is discussed by taking the example of developing wide user data analysis in the Yubei district, as shown in Table 1, after potentially valuable user data is obtained, firstly, the user and a background resource table are required to be associated, accepted users are eliminated, secondly, marking is required to be carried out on the wide business according to longitude and latitude information, and the wide business distribution is divided into full coverage, deep coverage and shallow coverage according to the base station construction condition. Thereby creating a broadband resource distribution table, as shown in table 2.
TABLE 2 broadband resource distribution Table
After the wide distribution of the quotient is established, the association between the commodity and the user can be carried out through the longitude and latitude to carry out data analysis and data screening, but the data obtained from the Baidu map cannot be compared with the GIS coordinates in the resource library, and the Mars coordinates of the coordinate data of the Baidu map need to be converted into the GIS coordinates.
After the longitude and latitude information of the user and the user under the same coordinate system is obtained, the user can be screened for the service through the longitude and latitude, the service is confirmed to be in an area with full coverage of broadband through a related network department, and under the condition that status is 1 in a table 2, broadband service can be recommended to the user within the range of 5KM around, so that the user can be associated through the table 1(custom) and the table 2(resource), the user with the broadband service selling capacity can be screened out, and the user which can be popularized can be solved through the following SQL according to the longitude and latitude distance formula between the two points:
select a.*from custom a inner join resource b where b.status＝1and a.lat>b.lat.-0.4and a.latitude<b.lat'+0.4and a.lon>b.lon-0.4and a.lon<b.lon+0.4and ACOS(SIN((b.lon*3.1415)/180)*SIN((a.lat*3.1415)/180)+COS((b.lat*3.1415)/180)*COS((a.lat*3.1415)/180)*COS((b.lon*3.1415)/180-(a.lon*3.1415)/180))*6380000<5。
specifically, the derivation method of the longitude and latitude distance formula between the two points is as follows:
as shown in FIG. 2, the shape of the earth is close to a sphere, and the S of the shortest distance of an arc AB between two points A and B can be calculated according to the longitude and latitude of the two points A and BABThe distance of AB is obtained by the distance formula between two points:
AB2＝(Xa-Xb)2+(Ya-Yb)2+(Za-Zb)2；
the point on the recombination sphere is X2+Y2+Z2＝R2；
The incoming data is available: AB2＝2R2(1-cos(wa)cos(wb)cos(jb-ja)+sin(wa)sin(wb))；
Knowing the linear distance AB, we can first use the cosine theorem in Δ AOB:
AB2＝OA2+OB2-2OA*OB*cos(∠AOB)；
after deformation, the following can be obtained: cos (. minus ] AOB) ═1-(AB2/2R2)；
Then the arc length distance of AB can be calculated by calculating the corresponding central angle ═ AOB in Δ AOB, and then using the arc length calculation formula. The arc length formula is reused after the central angle AOB is known:
SAB＝R*∠AOB＝Rarccos(cos(wa)cos(wb)cos(jb-ja)+sin(wa)sin(wb) To obtain the longitude and latitude distance between the two points.
S14: and recommending the broadband service to the potential user according to the correlation analysis result.
As a preferred implementation manner of this embodiment, as shown in fig. 3, the step S14 further includes:
establishing a recommendation model according to the correlation analysis result and the collaborative filtering recommendation method; the collaborative filtering recommendation method is characterized in that collaborative filtering is carried out according to the user data information of the accepted historical users and the user data information of the target recommendation user determined according to the correlation analysis result;
and recommending the broadband service according to the recommendation model.
In this step, after the user data is cleaned, the data of the user and the broadband service resource distribution is put in storage, and a sales model is established to realize service recommendation. In this embodiment, the service recommendation method mainly uses a collaborative filtering recommendation association method to perform collaborative filtering on the target client data and the history acceptance data. Specifically, collaborative filtering is to recommend information of interest to a user by using the preferences of a group with a certain interest and common experience, and individuals give a considerable response (e.g. score) to the information through a collaborative mechanism and record the response to achieve the purpose of filtering, thereby helping others to filter the information.
Most collaborative filtering recommendation systems currently use scoring data as input data for recommendations, which represents the user's preference level, and may be binary 0 or 1, or an integer representation such as 0 to 5. In the collaborative filtering algorithm, user information is represented by a vector formed by items and scores of the items by users, namely a user-item matrix, and data in the matrix is the scores of the items by the users. All possible recommendations to the target customer must be contained in the set of items. The collaborative filtering means how to filter the item set to obtain N recommended items for the target customer, and the N recommended items are compared as a standard data source according to the historical sales records of the goods or services, where it is not considered that the interest of the user changes with time, that is, the user is considered that the item score does not change with time.
For example, as shown in fig. 3, taking the yubei recommender width in step S12 as an example, historical data that has been processed in the system is used as a standard sample a, then unprocessed data is used as a sample B, and then the sample B is scored according to latitude and longitude, a comprehensive score, and a broadband coverage three items, wherein the comprehensive score includes user evaluation information. The method comprises the steps of scaling to be 0-5 according to a certain rule because the longitude and latitude, the comprehensive score and the broadband coverage measurement are different in standard, setting the proportion of the broadband coverage to be 60, the proportion of the longitude and latitude to be 25 and the proportion of the comprehensive score to be 15, searching the minimum value according to the comprehensive of the longitude and latitude, the comprehensive score and the broadband coverage measurement, and sequencing according to a TOP-K algorithm.
In summary, by adopting the method of the present embodiment, through the three steps, the geographical position dimension relationship between the user and the service distribution can be established. The closed-loop marketing mode can be realized according to the longitude and latitude information of the user and the commodity or the service, the target user can be deeply mined according to the construction condition of the resources, and the resources can be reasonably distributed according to the distribution of the users.
Example two
Fig. 4 is a diagram illustrating a broadband service recommendation system according to an exemplary embodiment of the present invention, as shown in fig. 4, including:
the collecting module 41 is configured to collect user data information of the POI tag, where the user data information at least includes user information and longitude and latitude information;
the screening module 42 is configured to clean the user data information to obtain potential user data information;
an association module 43, configured to perform association analysis on the longitude and latitude information of the potential user data information and the broadband service information
And the recommending module 44 is used for recommending the broadband service to the potential user according to the correlation analysis result.
As a preferred implementation manner of this embodiment, the collecting module 41 is further configured to:
selecting a target area and a POI group;
according to the crawler technology, user data information of POI labels in each POI group is sequentially captured through an open interface of an electronic map server;
wherein the user data information further comprises: user evaluation information and user contact information.
As a preferred implementation manner of this embodiment, the screening module 42 is further configured to:
cleaning the user data information according to the background resource table, and removing the user data information of the accepted user;
the association module 43 is further configured to:
obtaining a user representation of the potential user according to the potential user data information;
obtaining a broadband service portrait according to the broadband service information; the broadband service information comprises broadband distribution information, and the broadband distribution information is marked according to longitude and latitude information;
and carrying out correlation analysis on the user portrait of the potential user and the broadband service portrait.
As a preferred implementation manner of this embodiment, the recommending module 44 is further configured to:
establishing a recommendation model according to the correlation analysis result and the collaborative filtering recommendation method; the collaborative filtering recommendation method is characterized in that collaborative filtering is carried out according to the user data information of the accepted historical users and the user data information of the target recommendation user determined according to the correlation analysis result;
and recommending the broadband service according to the recommendation model.
By adopting the system provided by the embodiment, the target client can be selected according to the POI label through a big data technology, more user data can be obtained compared with the method in the prior art, and the data is provided with the user labels such as hospitals, schools, shopping malls, hotels and the like, so that effective data guarantee can be provided for the customized development business of the user; the users can be selected according to the commodities, so that bidirectional and closed-loop mutual selection is realized, and valuable customers can be deeply mined.
EXAMPLE III
The third embodiment of the present application provides a non-volatile computer storage medium, where the computer storage medium stores at least one executable instruction, and the computer executable instruction may execute the broadband service recommendation method in any of the above method embodiments.
Example four
Fig. 5 is a schematic structural diagram of a server according to a sixth embodiment of the present invention, and the specific embodiment of the present invention does not limit the specific implementation of the server.
As shown in fig. 5, the server may include: a processor (processor), a Communications Interface (Communications Interface), a memory (memory), and a Communications bus.
Wherein:
the processor, the communication interface, and the memory communicate with each other via a communication bus.
A communication interface for communicating with network elements of other devices, such as clients or other servers.
And the processor is used for executing a program, and specifically can execute relevant steps in the broadband service recommendation method embodiment.
In particular, the program may include program code comprising computer operating instructions.
The processor may be a central processing unit CPU or an application Specific Integrated circuit asic or one or more Integrated circuits configured to implement embodiments of the present invention. The server comprises one or more processors, which can be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.
And the memory is used for storing programs. The memory may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
The program may specifically be adapted to cause a processor to perform the following operations:
collecting user data information of the POI labels, wherein the user data information at least comprises user information and longitude and latitude information;
cleaning the user data information to obtain potential user data information;
carrying out correlation analysis on longitude and latitude information of the potential user data information and broadband service information;
and recommending the broadband service to the potential user according to the correlation analysis result.
The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. Moreover, the present invention is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components in a broadband service recommendation system according to embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
Claims (10)
1. A method for recommending broadband services is characterized by comprising the following steps:
collecting user data information of the POI labels, wherein the user data information at least comprises user information and longitude and latitude information;
cleaning the user data information to obtain potential user data information;
carrying out correlation analysis on longitude and latitude information of the potential user data information and broadband service information;
and recommending the broadband service to the potential user according to the correlation analysis result.
2. The method of claim 1, wherein the step of collecting user data information of POI tags further comprises:
selecting a target area and a POI group;
according to the crawler technology, user data information of POI labels in each POI group is sequentially captured through an open interface of an electronic map server;
wherein the user data information further comprises: user evaluation information and user contact information.
3. The method of claim 1 or 2, wherein the step of cleansing the user data information to obtain the potential user data information further comprises:
cleaning the user data information according to the background resource table, and removing the user data information of the accepted user;
the step of performing correlation analysis on the longitude and latitude information of the potential user data information and the broadband service information further comprises the following steps:
obtaining a user representation of the potential user according to the potential user data information;
obtaining a broadband service portrait according to the broadband service information; the broadband service information comprises broadband distribution information, and the broadband distribution information is marked according to longitude and latitude information;
and carrying out correlation analysis on the user portrait of the potential user and the broadband service portrait.
4. The method of claim 3, wherein the step of recommending broadband services to the potential user according to the correlation analysis further comprises:
establishing a recommendation model according to the correlation analysis result and the collaborative filtering recommendation method; the collaborative filtering recommendation method is characterized in that collaborative filtering is carried out according to the user data information of the accepted historical users and the user data information of the target recommendation user determined according to the correlation analysis result;
and recommending the broadband service according to the recommendation model.
5. A system for broadband service recommendation, comprising:
the system comprises a collecting module, a searching module and a searching module, wherein the collecting module is used for collecting user data information of the POI labels, and the user data information at least comprises user information and longitude and latitude information;
the screening module is used for cleaning the user data information to obtain potential user data information;
the correlation module is used for performing correlation analysis on the longitude and latitude information of the potential user data information and the broadband service information;
and the recommending module is used for recommending the broadband service to the potential user according to the correlation analysis result.
6. The system of claim 5, wherein the collection module is further configured to:
selecting a target area and a POI group;
according to the crawler technology, user data information of POI labels in each POI group is sequentially captured through an open interface of an electronic map server;
wherein the user data information further comprises: user evaluation information and user contact information.
7. The system of claim 5 or 6, wherein the screening module is further configured to:
cleaning the user data information according to the background resource table, and removing the user data information of the accepted user;
the association module is further to:
obtaining a user representation of the potential user according to the potential user data information;
obtaining a broadband service portrait according to the broadband service information; the broadband service information comprises broadband distribution information, and the broadband distribution information is marked according to longitude and latitude information;
and carrying out correlation analysis on the user portrait of the potential user and the broadband service portrait.
8. The system of claim 7, wherein the recommendation module is further configured to:
establishing a recommendation model according to the correlation analysis result and the collaborative filtering recommendation method; the collaborative filtering recommendation method is characterized in that collaborative filtering is carried out according to the user data information of the accepted historical users and the user data information of the target recommendation user determined according to the correlation analysis result;
and recommending the broadband service according to the recommendation model.
9. A server, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction causes the processor to execute the operation corresponding to the broadband service recommendation method according to any one of claims 1-4.
10. A computer storage medium having at least one executable instruction stored therein, the executable instruction causing a processor to perform operations corresponding to the broadband service recommendation method according to any one of claims 1-4.
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