CN110969486B - Advertisement putting method, user, server, system and storage medium - Google Patents
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Abstract
The embodiment of the specification provides an advertisement putting method, a user side, a server, a system and a storage medium, wherein the method comprises the steps of extracting a first element and corresponding evaluation dimension data from historical service data; the first element comprises a user; clustering the first elements based on the evaluation dimension data to form a plurality of first element subsets; taking the first element subset meeting the preset condition as a target subset, and extracting a second element subset associated with each first element in the target subset from the historical service data; the second element in the second element subset comprises a product; taking the union set of the second element subsets as a second element set, and determining a complement set of each second element subset based on the second element set; and providing advertisement data to the user terminal corresponding to the first element according to the complement. According to the embodiment of the specification, targeted advertising to the user can be achieved.
Description
Technical Field
The present disclosure relates to the field of data mining technologies, and in particular, to an advertisement delivery method, a user side, a server, a system, and a storage medium.
Background
Currently, some financial institutions generally provide business advertisements with fixed content when advertising is performed by using a website display, a mobile terminal, a self-service terminal device and the like. However, this advertisement delivery method does not take into consideration the actual demands and interests of the user, and thus much advertisement information delivered is actually difficult to obtain the attention of the user.
Therefore, how to target advertisement to users has become a technical problem to be solved.
Disclosure of Invention
The embodiment of the specification aims to provide an advertisement putting method, a user side, a server, a system and a storage medium, so as to realize targeted advertisement putting to users.
In order to achieve the above object, in one aspect, an embodiment of the present disclosure provides an advertisement delivery method, including:
extracting a first element from historical service data and corresponding evaluation dimension data thereof; the first element comprises a user;
clustering the first elements based on the evaluation dimension data to form a plurality of first element subsets;
taking the first element subset meeting the preset condition as a target subset, and extracting a second element subset associated with each first element in the target subset from the historical service data; the second element in the second element subset comprises a product;
taking the union set of the second element subsets as a second element set, and determining a complement set of each second element subset based on the second element set;
and providing advertisement data to the user terminal corresponding to the first element according to the complement.
In the advertisement delivery method of the embodiment of the present disclosure, the clustering the first elements based on the evaluation dimension data to form a plurality of first element subsets includes:
determining a distance between the first elements based on the evaluation dimension data;
the first elements are clustered into a plurality of first element subsets according to the distance.
In the advertisement delivery method of the embodiment of the present disclosure, the first element subset satisfying the preset condition includes:
a first subset of elements in which the number value of the first element exceeds a number threshold.
In the advertisement delivery method of the embodiment of the present disclosure, the first element subset satisfying the preset condition includes:
a number of first elements within a specified range, a first subset of elements in the first subset of elements having a duty cycle exceeding a duty cycle threshold; the specified range includes: and a range with the center point of the first element subset as a circle center and the first distance as a radius.
In the advertisement delivery method of the embodiment of the present disclosure, the providing advertisement data to the user terminal corresponding to the first element according to the complement set includes:
selecting a complement;
matching corresponding advertisement data from the advertisement data set according to the element identification of the element in the complement;
and providing the matched advertisement data to the user side corresponding to the first element.
In the advertisement delivery method of the embodiment of the present disclosure, after providing advertisement data to the user terminal corresponding to the first element according to the complement set, the method further includes:
acquiring the interested elements of the user corresponding to the complement; the interested elements are elements of the complement, and the interested elements are elements of the complement, which are queried or transacted by the corresponding user after the advertisement data are put in;
determining the elements of the complement, wherein the distance between the elements and the element of interest is smaller than the second distance;
correspondingly, the providing advertisement data to the user terminal corresponding to the first element according to the complement set further includes:
and selecting one or more elements from the elements with the distance from the interested elements being smaller than the second distance, and providing the advertisement data corresponding to the elements to the user side of the complement corresponding to the user.
In another aspect, an embodiment of the present disclosure further provides a server, including:
the first extraction module is used for extracting the first element and the corresponding evaluation dimension data thereof from the historical service data; the first element comprises a user;
an element clustering module for clustering the first elements based on the evaluation dimension data to form a plurality of first element subsets;
the second extraction module is used for taking the first element subset meeting the preset condition as a target subset and extracting a second element subset associated with each first element in the target subset from the historical service data; the second element in the second element subset comprises a product;
the complement determining module is used for taking the union set of the second element subsets as a second element set and determining the complement set of each second element subset based on the second element set;
and the advertisement providing module is used for providing advertisement data for the user side corresponding to the first element according to the complement.
In the server of the embodiment of the present disclosure, the clustering the first elements based on the evaluation dimension data to form a plurality of first element subsets includes:
determining a distance between the first elements based on the evaluation dimension data;
the first elements are clustered into a plurality of first element subsets according to the distance.
In the server of the embodiment of the present disclosure, the first element subset that satisfies the preset condition includes:
a first subset of elements in which the number value of the first element exceeds a number threshold.
In the server of the embodiment of the present disclosure, the first element subset that satisfies the preset condition includes:
a number of first elements within a specified range, a first subset of elements in the first subset of elements having a duty cycle exceeding a duty cycle threshold; the specified range includes: and a range with the center point of the first element subset as a circle center and the first distance as a radius.
In the server of the embodiment of the present disclosure, the providing, according to the complement, advertisement data to a user terminal corresponding to the first element includes:
selecting a complement;
matching corresponding advertisement data from the advertisement data set according to the element identification of the element in the complement;
and providing the matched advertisement data to the user side corresponding to the first element.
In the server of the embodiment of the present specification, the complement determining module is further configured to:
after providing advertisement data to a user terminal corresponding to the first element according to the complement, acquiring an element of interest of a user corresponding to the complement; the interested elements are elements of the complement, and the interested elements are elements of the complement, which are queried or transacted by the corresponding user after the advertisement data are put in;
determining the elements of the complement, wherein the distance between the elements and the element of interest is smaller than the second distance;
correspondingly, the advertisement providing module is further configured to:
and selecting one or more elements from the elements with the distance from the interested elements being smaller than the second distance, and providing the advertisement data corresponding to the elements to the user side of the complement corresponding to the user.
On the other hand, the embodiment of the specification also provides a user side, which is used for receiving the advertisement data provided by the server and outputting the advertisement data.
On the other hand, the embodiment of the specification also provides an advertisement delivery system, which comprises the user terminal and the server.
In another aspect, the present description also provides a computer storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:
extracting a first element from historical service data and corresponding evaluation dimension data thereof; the first element comprises a user;
clustering the first elements based on the evaluation dimension data to form a plurality of first element subsets;
taking the first element subset meeting the preset condition as a target subset, and extracting a second element subset associated with each first element in the target subset from the historical service data; the second element in the second element subset comprises a product;
taking the union set of the second element subsets as a second element set, and determining a complement set of each second element subset based on the second element set;
and providing advertisement data to the user terminal corresponding to the first element according to the complement.
The technical scheme provided by the embodiment of the specification can be used for mining and mining the product possibly interested by the user based on the historical service data and the clustering algorithm, so that the product advertisement possibly interested by the user can be personalized pushed to the user, and the targeted advertising to the user is realized.
Drawings
In order to more clearly illustrate the embodiments of the present description or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some of the embodiments described in the present description, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:
FIG. 1 is a block diagram of an advertising system in some embodiments of the present description;
FIG. 2 is a flow chart of a method of advertising in some embodiments of the present description;
FIG. 3 is a schematic diagram of complement acquisition in an embodiment of the present disclosure;
FIG. 4 is a block diagram of a server in some embodiments of the present description;
fig. 5 is a block diagram illustrating a server according to other embodiments of the present disclosure.
Detailed Description
In order to make the technical solutions in the present specification better understood by those skilled in the art, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are intended to be within the scope of the present disclosure.
The advertisement delivery system of some embodiments of the present description may include a user side and a server. In some embodiments of the present description, the server may be an electronic device having operation and network interaction functions; software running in the electronic device may also be used to provide business logic for data processing and network interactions. The server can perform data interaction with the user side. For example, the server may provide advertisement data to the client so that the client may output and display the advertisement data provided by the server, thereby enabling the user to view advertisement information.
Referring to fig. 1, in some embodiments of the present disclosure, the user terminal may be a self-service terminal device, a mobile terminal (i.e., a smart phone), a display, a desktop computer, a tablet computer, a notebook computer, a digital assistant, or a smart wearable device. Wherein, intelligent wearable equipment can include intelligent bracelet, intelligent wrist-watch, intelligent glasses or intelligent helmet etc.. Of course, the user side is not limited to the electronic device with a certain entity, and may be software running in the electronic device.
As shown in connection with fig. 4, in some embodiments of the present description, the server may include a first extraction module 41, an element clustering module 42, a second extraction module 43, a complement determination module 44, and an advertisement providing module 45. Wherein:
the first extraction module 41 may be configured to extract the first element and the corresponding evaluation dimension data thereof from the historical service data; the first element comprises a user;
element clustering module 42 may be configured to cluster the first elements based on the evaluation dimension data to form a plurality of first element subsets;
the second extraction module 43 may be configured to take a first element subset that meets a preset condition as a target subset, and extract, from the historical service data, a second element subset associated with each first element in the target subset; the second element in the second element subset comprises a product;
the complement determination module 44 may be configured to take the union of the second element subsets as a second element set and determine a complement of each second element subset based on the second element set;
the advertisement providing module 45 may be configured to provide advertisement data to the user terminal corresponding to the first element according to the complement.
Therefore, in the embodiment of the specification, the server can mine and mine out the product possibly interested by the user based on the historical service data and the clustering algorithm, so that the product advertisement possibly interested by the user can be individually pushed to the user, and the targeted advertising to the user is realized.
In some embodiments of the present description, historical business data may include, but is not limited to, transaction data, query data, and the like. In some embodiments of the present description, the historical business data may be historical business data within a specified range. For example, in an exemplary embodiment of the present description, the specified range may be a specified time range, such as transaction data of a certain banking transaction system in the last six months, one year, or three years.
In another exemplary embodiment of the present specification, the specified range may be a specified spatial range, for example, historical transaction data of a certain banking system in Jiangsu province and eastern China. In another exemplary embodiment of the present specification, the specified range may be a combination of the specified spatial range and the specified temporal range described above, which is not a limitation of the present specification.
It should be noted that, in the above embodiment, the user is taken as the first element as an example, but the present disclosure is not limited to this, and in other embodiments of the present disclosure, the first element may be another element in the historical business data such as a product.
In some embodiments of the present description, the evaluation dimension may be a plurality of attribute dimensions selected from a plurality of attribute dimensions of the historical business data. For example, in an exemplary embodiment, with the user as the first element, the evaluation dimension may include, but is not limited to, age, asset, risk preferences, product preferences, etc., such as shown in Table 1 below:
TABLE 1
In some embodiments of the present description, existing data extraction techniques (e.g., ETL (Extract-Transform-Load) tools, etc.) may be utilized to Extract the first element and its corresponding evaluation dimension data from the historic business database. Of course, in other embodiments, in order to ensure data quality and reliability, preprocessing such as data cleansing may be performed on the raw data selected from the historical service database before extracting the data.
In some embodiments of the present disclosure, the first element may be clustered using any suitable clustering algorithm (e.g., a partitioning method, a layering method, a density algorithm, a graph theory clustering method, or a grid algorithm, etc.), which is not limited in this disclosure. For example, in an embodiment of the present disclosure, when an index describing a degree of proximity between a pair of first elements is used, the clustering the first elements based on the evaluation dimension data may include: determining a distance between the first elements based on the evaluation dimension data; the first elements are clustered into a plurality of first element subsets according to the distance.
The example embodiment shown in table 1 above is exemplified by the closer the age, the closer the corresponding distance; the closer the asset is, the closer the corresponding distance is; the closer the risk preferences are, the closer the corresponding distances are; the closer the product preferences are, the closer the corresponding distances are. Of course, to comprehensively consider these evaluation dimension data, the distance between any two first elements is defined as: cti=αx+βy+γz+λt, wherein x, y, z, t is the age distance, asset distance, risk preference distance, product preference distance between two first elements, respectively. α, β, γ, λ are the weight coefficients of x, y, z, t, respectively, and α+β+γ+λ=1.
In some embodiments of the present disclosure, to improve accuracy, a plurality of first element subsets obtained by clustering may be preferred. For example, in an embodiment of the present specification, the first element subset satisfying the preset condition may be regarded as the target subset; that is, one first element subset may be selected from a plurality of first element subsets by means of a preset condition. The preset conditions can be set according to the needs.
In an exemplary embodiment, the first element subset satisfying the preset condition may be: a first subset of elements in which the number value of the first element exceeds a preset number threshold. For example, taking a user as a first element, assuming that the preset number threshold is 300, when the number of users in a certain first element subset reaches 300, the first element subset may be taken as a target subset.
In another exemplary embodiment, the first element subset that satisfies the preset condition may be: a number of first elements within a specified range, a first subset of elements in the first subset of elements having a duty cycle exceeding a duty cycle threshold; wherein the specified range includes: and a range with the center point of the first element subset as a circle center and the first distance as a radius. For example, taking a preset duty ratio threshold value of 50% as an example, for a certain first element subset including 100 first elements, when the number of first elements in a range of taking the center point of the first element subset as the center and the first distance as the radius is 60, the number of first elements in the specified range, the duty ratio in the first element subset is 60/100=60%, so that the duty ratio threshold value (50%) is reached, and therefore, the first element subset can be taken as the target subset.
In a special case, when more than one first element subset satisfies the preset condition, one may be selected as the target subset, or the first element subsets satisfying the preset condition may be further preferred. In another special case, when none of the plurality of first element subsets satisfies the preset condition, the number of samples of the history service data may be appropriately increased and the processing may be performed again on the basis of this.
In some embodiments of the present disclosure, the extracting, from the historical service data, the second element subset associated with each first element in the target subset refers to: all second elements associated with each first element within the target subset are extracted based on the historical business data. For example, taking a user as a first element and a product as a second element, for each user within the target subset, all products that they transact (queried or focused) can be extracted based on historical business data.
In some embodiments of the present disclosure, taking a user as a first element and a product as a second element, for a target subset, because the users in the target subset have strong similarities with each other, when one of the users is interested in a certain product, it can be presumed that other users in the target subset are also interested in the product. Thus, based on the union of the second element subsets as the second element set, the complement of each second element subset may be determined based on the second element sets. Accordingly, for any user in the target subset, each product in its corresponding complement is a product that has been traded (queried or focused) by other customers in the target subset, but has not yet traded by itself, so that it can be presumed that the products in the complement are all products of interest to that user.
For example, in one exemplary embodiment, as shown in FIG. 3, assume that there are three users within the target subset: user 1, user 2, and user 3, based on historical business data, can be extracted: all products that user 1 has transacted include product 1 and product 2; all products that user 2 has transacted include product 2 and product 3; all products that the user 3 transacts include products 3 and 4. Thus, product 1 and product 2 form a second element subset U1 associated with user 1; product 2 and product 3 form a second element subset U2 associated with user 2; product 3 and product 4 form a second element subset U3 associated with user 3. On this basis, products 1, 2, 3 and 4 form a union of U1, U2 and U3 (i.e., u=u1U 2U 3U 1). Further, products 3 and 4 form complement C of the second element subset U1 U U1; product 1 and product 4 then form complement C of second element subset U2 U U2; product 1 and product 2 then form complement C of second element subset U3 U U3。
In some embodiments of the present disclosure, the providing the advertisement data to the user terminal corresponding to the first element according to the complement set may include: selecting a complement; matching corresponding advertisement data from the advertisement data set according to the element identification of the element in the complement; and providing the matched advertisement data to the user side corresponding to the first element. For example, in the embodiment shown in FIG. 3, when complement C is selected U U2 can be selected according to complement C U Product 1 and product 4 product identifiers in U2 are searched out corresponding advertisement data from an advertisement database, and then complementary set C is used U And the corresponding relation between the U2 and the user 2 pushes the advertisement data to the user side corresponding to the user 2, so that the accurate delivery of the advertisement data is realized.
In some embodiments of the present disclosure, the timing of providing the advertisement data to the user terminal corresponding to the first element according to the complement may be determined according to the need, so as to improve the audience rating of the advertisement data. For example, in an exemplary embodiment, the timing of providing advertisement data may be when a user uses a client.
In other embodiments of the present description, the complement determination module 44 may also be configured to: after advertisement data is provided to the user terminal corresponding to the first element according to the complement, the interested element of the user corresponding to the complement can be obtained; the interested elements are elements of the complement, and the interested elements are elements of the complement, which are queried or transacted by the corresponding user after the advertisement data are put in; and determining the elements of which the distance from the element of interest is smaller than a second distance (the second distance is preset) from the rest elements of the complement. Correspondingly, the advertisement providing module 45 may be further configured to: and selecting one or more elements from the elements with the distance from the interested elements being smaller than the second distance, and providing the advertisement data corresponding to the elements to the user side of the complement corresponding to the user. Therefore, the method and the device can select the put advertisement content according to the advertisement putting effect, so that the put advertisement content meets the personalized requirements of users.
For example, in an exemplary embodiment, assume that the complement for user a obtained includes products P1, P2, P3, and P4. After providing advertising data regarding the product P1 to the user's side of the user a according to the complement, if the user a inquires about or purchased the product P1 during this period, this advertising is indicated to be valid, i.e., there is a certain accuracy in the prediction or the assertion that "the product P1 is a product that the user a may be interested in". To further improve the prediction accuracy, the distances of the products P2, P3, and P4 from the product P1, respectively, may be calculated. According to the calculation result, if the distance between the product P3 and the product P1 is found to be smaller than the preset distance, the product P3 is considered to be more likely to be the user a, so that the advertisement content corresponding to the product P3 can be provided to the user side of the user a during the subsequent advertisement delivery. For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in one or more software and/or hardware elements when implemented in the present specification.
Referring to fig. 5, in other embodiments of the present description, the server may include a memory, a processor, and a computer program stored on the memory, which when executed by the processor performs the steps of:
extracting a first element from historical service data and corresponding evaluation dimension data thereof; the first element comprises a user;
clustering the first elements based on the evaluation dimension data to form a plurality of first element subsets;
taking the first element subset meeting the preset condition as a target subset, and extracting a second element subset associated with each first element in the target subset from the historical service data; the second element in the second element subset comprises a product;
taking the union set of the second element subsets as a second element set, and determining a complement set of each second element subset based on the second element set;
and providing advertisement data to the user terminal corresponding to the first element according to the complement.
While the process flows described above include a plurality of operations occurring in a particular order, it should be apparent that the processes may include more or fewer operations, which may be performed sequentially or in parallel (e.g., using a parallel processor or a multi-threaded environment).
Corresponding to the above server, referring to fig. 2, the advertisement delivery method according to some embodiments of the present disclosure may include:
s21, extracting a first element from historical service data and corresponding evaluation dimension data thereof; the first element includes a user.
S22, clustering the first elements based on the evaluation dimension data to form a plurality of first element subsets.
S23, taking a first element subset meeting preset conditions as a target subset, and extracting a second element subset associated with each first element in the target subset from the historical service data; the second element in the second element subset comprises a product.
S24, taking the union set of the second element subsets as a second element set, and determining the complement set of each second element subset based on the second element set.
And S25, providing advertisement data for the user terminal corresponding to the first element according to the complement.
In the advertisement putting method of the embodiment of the specification, products possibly interested by the user can be mined based on the historical service data and the clustering algorithm, so that the product advertisements possibly interested by the user can be individually pushed to the user, and the advertisement can be put to the user in a targeted manner.
In some embodiments of the advertisement delivery method of the present disclosure, the clustering the first elements based on the evaluation dimension data to form a plurality of first element subsets includes:
determining a distance between the first elements based on the evaluation dimension data;
the first elements are clustered into a plurality of first element subsets according to the distance.
In some embodiments of the advertisement delivery method of the present disclosure, the first element subset satisfying the preset condition includes:
a first subset of elements in which the number value of the first element exceeds a number threshold.
In some embodiments of the advertisement delivery method of the present disclosure, the first element subset satisfying the preset condition includes:
a number of first elements within a specified range, a first subset of elements in the first subset of elements having a duty cycle exceeding a duty cycle threshold; the specified range includes: and a range with the center point of the first element subset as a circle center and the first distance as a radius.
In some embodiments of the advertisement delivery method of the present disclosure, the providing advertisement data to the user terminal corresponding to the first element according to the complement set includes:
selecting a complement;
matching corresponding advertisement data from the advertisement data set according to the element identification of the element in the complement;
and providing the matched advertisement data to the user side corresponding to the first element.
In the advertisement delivery method according to some embodiments of the present disclosure, after providing advertisement data to the user terminal corresponding to the first element according to the complement set, the method may further include:
acquiring the interested elements of the user corresponding to the complement; the interested elements are elements of the complement, and the interested elements are elements of the complement, which are queried or transacted by the corresponding user after the advertisement data are put in;
determining the elements of the complement, wherein the distance between the elements and the element of interest is smaller than the second distance;
correspondingly, the providing the advertisement data to the user terminal corresponding to the first element according to the complement set may further include:
and selecting one or more elements from the elements with the distance from the interested elements being smaller than the second distance, and providing the advertisement data corresponding to the elements to the user side of the complement corresponding to the user.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, systems (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method or apparatus comprising such elements.
It will be appreciated by those skilled in the art that embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the present specification may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present description can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
The description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, elements, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.
The foregoing is merely exemplary of the present disclosure and is not intended to limit the disclosure. Various modifications and alterations to this specification will become apparent to those skilled in the art. Any modifications, equivalent substitutions, improvements, or the like, which are within the spirit and principles of the present description, are intended to be included within the scope of the claims of the present description.
Claims (10)
1. An advertising method, comprising:
extracting a first element from historical service data and corresponding evaluation dimension data thereof; the first element includes a user, and the evaluation dimension includes an age, an asset, a risk preference, and a product preference;
determining a distance between the first elements based on the evaluation dimension data, the distance being CTI = αx + βy + γz + λt, wherein x, y, z, t is an age distance, an asset distance, a risk preference distance, and a product preference distance between two first elements, respectively, α, β, γ, λ are weight coefficients of x, y, z, t, respectively, and α + β + γ + λ = 1, clustering the first elements into a plurality of first element subsets according to the distances;
taking the first element subset meeting the preset condition as a target subset, and extracting a second element subset associated with each first element in the target subset from the historical service data; the second element in the second element subset comprises a product;
taking the union set of the second element subsets as a second element set, and determining a complement set of each second element subset based on the second element set; acquiring the interested elements of the user corresponding to the complement; the interested elements are elements of the complement, and the interested elements are elements of the complement, which are queried or transacted by the corresponding user after the advertisement data are put in; determining the elements of the complement, wherein the distance between the elements and the element of interest is smaller than the second distance; and selecting one or more elements from the elements with the distance from the interested elements being smaller than the second distance, and providing the advertisement data corresponding to the elements to the user side of the complement corresponding to the user.
2. The advertising method as recited in claim 1, wherein the first subset of elements satisfying a predetermined condition comprises:
a first subset of elements in which the number value of the first element exceeds a number threshold.
3. The advertising method as recited in claim 1, wherein the first subset of elements satisfying a predetermined condition comprises:
a number of first elements within a specified range, a first subset of elements in the first subset of elements having a duty cycle exceeding a duty cycle threshold; the specified range includes: and a range with the center point of the first element subset as a circle center and the first distance as a radius.
4. The advertising method as claimed in claim 1, wherein said providing advertisement data to the user terminal corresponding to the first element according to the complement set includes:
selecting a complement;
matching corresponding advertisement data from the advertisement data set according to the element identification of the element in the complement;
and providing the matched advertisement data to the user side corresponding to the first element.
5. A server, comprising:
the first extraction module is used for extracting the first element and the corresponding evaluation dimension data thereof from the historical service data; the first element includes a user, and the evaluation dimension includes an age, an asset, a risk preference, and a product preference;
an element clustering module for determining a distance between the first elements based on the evaluation dimension data, the distance being cti=αx+βy+γz+λt, wherein x, y, z, t is an age distance, an asset distance, a risk preference distance, and a product preference distance between two first elements, α, β, γ, λ are weight coefficients of x, y, z, t, respectively, and α+β+γ+λ=1, clustering the first elements into a plurality of first element subsets according to the distances;
the second extraction module is used for taking the first element subset meeting the preset condition as a target subset and extracting a second element subset associated with each first element in the target subset from the historical service data; the second element in the second element subset comprises a product;
the complement determining module is used for taking the union set of the second element subsets as a second element set and determining the complement set of each second element subset based on the second element set; after providing advertisement data to a user terminal corresponding to the first element according to the complement, acquiring an element of interest of a user corresponding to the complement; the interested elements are elements of the complement, and the interested elements are elements of the complement, which are queried or transacted by the corresponding user after the advertisement data are put in; determining the elements of the complement, wherein the distance between the elements and the element of interest is smaller than the second distance;
and the advertisement providing module is used for selecting one or more elements from the elements with the distance from the interested elements being smaller than the second distance, and providing advertisement data corresponding to the elements to the user side of the complement corresponding user.
6. The server according to claim 5, wherein the first subset of elements satisfying a preset condition comprises:
a first subset of elements in which the number value of the first element exceeds a number threshold.
7. The server according to claim 5, wherein the first subset of elements satisfying a preset condition comprises:
a number of first elements within a specified range, a first subset of elements in the first subset of elements having a duty cycle exceeding a duty cycle threshold; the specified range includes: and a range with the center point of the first element subset as a circle center and the first distance as a radius.
8. The server according to claim 5, wherein the providing advertisement data to the user side corresponding to the first element according to the complement includes:
selecting a complement;
matching corresponding advertisement data from the advertisement data set according to the element identification of the element in the complement;
and providing the matched advertisement data to the user side corresponding to the first element.
9. An advertising system comprising a user side and a server as claimed in any one of claims 5 to 8.
10. A computer storage medium having a computer program stored thereon, the computer program, when executed by a processor, performing the steps of:
extracting a first element from historical service data and corresponding evaluation dimension data thereof; the first element includes a user, and the evaluation dimension includes an age, an asset, a risk preference, and a product preference;
determining a distance between the first elements based on the evaluation dimension data, the distance being CTI = αx + βy + γz + λt, wherein x, y, z, t is an age distance, an asset distance, a risk preference distance, and a product preference distance between two first elements, respectively, α, β, γ, λ are weight coefficients of x, y, z, t, respectively, and α + β + γ + λ = 1, clustering the first elements into a plurality of first element subsets according to the distances;
taking the first element subset meeting the preset condition as a target subset, and extracting a second element subset associated with each first element in the target subset from the historical service data; the second element in the second element subset comprises a product;
taking the union set of the second element subsets as a second element set, and determining a complement set of each second element subset based on the second element set; after providing advertisement data to a user terminal corresponding to the first element according to the complement, acquiring an element of interest of a user corresponding to the complement; the interested elements are elements of the complement, and the interested elements are elements of the complement, which are queried or transacted by the corresponding user after the advertisement data are put in; determining the elements of the complement, wherein the distance between the elements and the element of interest is smaller than the second distance;
and selecting one or more elements from the elements with the distance from the interested elements being smaller than the second distance, and providing the advertisement data corresponding to the elements to the user side of the complement corresponding to the user.
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