CN115641191B

CN115641191B - Data pushing method and AI system based on data analysis

Info

Publication number: CN115641191B
Application number: CN202211533839.2A
Authority: CN
Inventors: 秦华辉; 徐荣松
Original assignee: Guangzhou Yuanxiang E Commerce Co ltd; Guangzhou Yuanxiang Information Technology Co ltd
Current assignee: Guangzhou Yuanxiang E Commerce Co ltd; Guangzhou Yuanxiang Information Technology Co ltd
Priority date: 2022-12-02
Filing date: 2022-12-02
Publication date: 2023-09-29
Anticipated expiration: 2042-12-02
Also published as: CN115641191A

Abstract

According to the data pushing method and the AI system based on data analysis, firstly, an online product pushing information set corresponding to a product pushing information set is obtained, then, according to the relevance index between the product pushing information set and each online product pushing information set, at least one undetermined product pushing information set is identified, then, after a target product pushing information set which is consistent with the product pushing information set and is a product pushing information set subclass is identified, a product pushing information set sequence of the associated product pushing information set subclass is established through the product pushing information set and the target product pushing information set. Because the product pushing information sets are corresponding to the product categories with consistency in the established product pushing information set sequence, and the relevance indexes accord with the preset relevance indexes, meanwhile, the product pushing information sets are of the same type, the matching degree among the product pushing information sets is greatly improved, the pertinence of pushing data is enhanced, and the product conversion rate is further improved.

Description

Data pushing method and AI system based on data analysis

Technical Field

The application relates to the field of data processing, in particular to a data pushing method and an AI system based on data analysis.

Background

In the operation of the electronic commerce, when a user clicks a product to browse, in order to increase the conversion rate of the platform of the electronic commerce, the platform often pushes other similar product pushing information related to the product information clicked by the user to increase the products entering the user selection category and promote the conversion. Therefore, how to reasonably and accurately push the product pushing information is an important point to be considered, in the prior art, for the pushed product information, matching elements often considered during early analysis are fewer, for example, the matching elements are the same in price and the same type, however, when a user searches for a product to browse, the considered elements are not limited to the factors, so that a new accurate and reasonable pushing mode needs to be proposed.

Disclosure of Invention

The application aims to provide a data pushing method and an AI system based on data analysis, so as to solve the problem of inaccurate pushing.

In a first aspect, an embodiment of the present application provides a data pushing method based on data analysis, which is characterized in that the method is applied to a server, where the server is communicatively connected to a client, and the method includes:

acquiring at least one online product push information set of a product category to which the product push information set belongs;

Determining relevance indexes of the product pushing information sets and all the online product pushing information sets one by one, and then identifying at least one undetermined product pushing information set with the relevance indexes meeting preset relevance indexes from the at least one online product pushing information set;

acquiring target product pushing information sets of which the number is not less than one and the product pushing information sets are of the same product pushing information set subclass;

establishing a product pushing information set sequence associated with the product pushing information set subclass, wherein the product pushing information set sequence covers the product pushing information set and the target product pushing information set;

and pushing the content associated with the product pushing information set sequence to the client when the pushing event triggering the product indicated by any product pushing information set in the product pushing information set sequence is detected.

As an implementation manner, when the product push information set attribute corresponding to the product push information set sequence is the same-series product push information set, the obtaining at least one online product push information set of a product category to which the product push information set belongs includes:

Acquiring summary information carried by the product pushing information set;

carrying out preset indication information identification on the summary information to obtain preset indication information of the product push information set;

determining the product pushing information set attribute of the product pushing information set based on the preset indication information;

when the product pushing information set attribute indicates that the product pushing information set is a same-series product pushing information set, obtaining at least one online product pushing information set of a product category to which the product pushing information set belongs.

As an implementation manner, when the product push information set attribute corresponding to the product push information set sequence is the same-series product push information set, the one-to-one determining the relevance index of the product push information set and each online product push information set includes:

obtaining summary information carried by each online product pushing information set one by one, and carrying out preset indication information identification on each summary information to obtain preset indication information of each online product pushing information set;

determining the product pushing information set attribute of each online product pushing information set one by one according to the preset indication information;

Identifying that the product pushing information set attribute in the obtained online product pushing information set is an online product pushing information set of the same series of product pushing information sets;

and determining that the product pushing information set and the product pushing information set attribute are relevance indexes of online product pushing information sets of the same series of product pushing information sets one by one.

As an implementation manner, the one-to-one determining the relevance index of the product push information set and each online product push information set includes:

determining first summary information carried by the product push information set and second summary information carried by each online product push information set;

extracting vectors aiming at the first summary information to obtain a first summary information vector related to the product push information set;

extracting the second summary information carried by each online product push information set one by one to obtain second summary information vectors related to each online product push information set;

and determining vector relevance indexes of the first summary information vector and each second summary information vector one by one, and taking the vector relevance indexes of the first summary information vector and each second summary information vector as relevance indexes of the product pushing information set and each online product pushing information set.

acquiring product introduction information of the product pushing information set and product introduction information of each online product pushing information set;

extracting the product introduction information of the product push information set by vector extraction to obtain a first product introduction information vector related to the product push information set;

extracting the product introduction information of each online product pushing information set one by one to obtain a second product introduction information vector related to each online product pushing information set;

the vector relevance indexes of the first product introduction information vector and the second product introduction information vector are determined one by one, and the vector relevance indexes of the first product introduction information vector and the second product introduction information vector are used as relevance indexes of the product pushing information set and the online product pushing information set.

As an implementation manner, the identifying, from the at least one online product push information set, at least one set of undetermined product push information whose relevance index satisfies a preset relevance index includes:

Determining at least one online product pushing information set according to the product pushing information set and the relevance index of each online product pushing information set, wherein the relevance index accords with the online product pushing information set of the preset relevance index;

and taking the online product pushing information set with the relevance index meeting the preset relevance index as a pending product pushing information set with the relevance index meeting the preset relevance index.

As an implementation manner, the obtaining the target product push information set that is not less than one set of pending product push information and is a subset of a consistent product push information set includes one of the following manners:

acquiring portrait information of a first product pushing information set of the product pushing information sets and portrait information of a second product pushing information set of each undetermined product pushing information set; comparing the first product push information set portrait information with the portrait information of each second product push information set to obtain a comparison value of the portrait information of the first product push information set and the portrait information of each second product push information set; taking a to-be-determined product pushing information set corresponding to the second product pushing information set portrait information with the comparison value meeting the preset comparison value as a target product pushing information set which is a product pushing information set subclass consistent with the product pushing information set;

Or carrying out information mining on the summary information carried by the product push information set to obtain a first summary block cluster related to the product push information set; carrying out information mining on summary information carried by each set of the push information of the undetermined products one by one to obtain second summary block clusters related to each set of the push information of the undetermined products; determining summary block matching results between the first summary block cluster and each second summary block cluster one by one; taking a to-be-determined product pushing information set corresponding to a second summary block cluster with the summary block matching result reaching a preset matching result as a target product pushing information set which is a product pushing information set subclass consistent with the product pushing information set;

or carrying out information mining on the summary information carried by the product push information set to obtain a first summary block cluster related to the product push information set; carrying out information mining on summary information carried by each set of the pending product push information one by one to obtain second summary block clusters related to each set of the pending product push information; determining preset unified summary blocks between the first summary block cluster and each second summary block cluster one by one, and covering the preset unified summary blocks in the second summary block clusters; and taking the undetermined product pushing information set corresponding to the preset unified summary block with the coverage exceeding the preset range as a target product pushing information set which is a product pushing information set subclass consistent with the product pushing information set.

As an embodiment, the establishing a product push information set sequence associated with the product push information set subclass includes one of the following ways:

under the condition that the number of the target product pushing information sets is multiple, the product pushing information sets and the online time of each target product pushing information set are obtained one by one; classifying the product pushing information sets and the target product pushing information sets according to the successive relation of the online time to obtain a first product pushing information set list; establishing a product pushing information set sequence associated with the product pushing information set subclass according to the first product pushing information set list;

or under the condition that the number of the target product pushing information sets is a plurality of, acquiring first summary information carried by the product pushing information sets and second summary information carried by each target product pushing information set; identifying product series identification indication information aiming at the first summary information to obtain a first product series identification of the product pushing information set; identifying product series identification indication information of each piece of second summary information to obtain a second product series identification of a target product pushing information set, wherein the product series identification indication information is configured to represent the online time of the corresponding product pushing information set; classifying the product pushing information set and a plurality of target product pushing information sets through the identification indication rules of the first product series identification and the second product series identification to obtain a second product pushing information set list; and establishing a product pushing information set sequence associated with the product pushing information set subclass according to the second product pushing information set list.

As one embodiment, the pushing the content associated with the product push information set sequence to the client includes: pushing the content associated with the product pushing information set sequence to the client, wherein the associated content comprises a transmission path corresponding to the product pushing information set sequence and summary information of the product pushing information set sequence.

In a second aspect, the present application provides a data push AI system, including a server and a client communicatively connected to each other, where the server includes a processor and a memory, where the memory stores a computer program, and when the processor runs the program, the method as provided in the first aspect of the embodiment of the present application is implemented.

In the embodiment of the application, by acquiring at least one online product pushing information set of a product category to which the product pushing information set belongs, identifying at least one undetermined product pushing information set of which the relevance index meets a preset relevance index from the at least one online product pushing information set according to the relevance index between the product pushing information set and each online product pushing information set, and identifying a target product pushing information set which is consistent with the product pushing information set as a product pushing information set sub-category from the at least one undetermined product pushing information set, so that a product pushing information set sequence of the associated product pushing information set sub-category is established through the product pushing information set and the target product pushing information set. Because the product pushing information sets are corresponding to the product categories with consistency in the established product pushing information set sequence, and the relevance index accords with the preset relevance index, and is a class of consistent product pushing information sets, compared with a simple comparison mode, the matching degree among the obtained product pushing information sets is greatly improved, so that when the pushing event triggering the product indicated by any product pushing information set in the product pushing information set sequence is detected, the content associated with the product pushing information set sequence is pushed, and a user can continuously browse similar product pushing information sets which are highly matched with the product pushing information sets and are class of consistent product pushing information sets through the associated content during browsing the product pushing information sets, thereby enhancing the pushing pertinence and improving the product conversion rate.

In the following description, other features will be partially set forth. Upon review of the ensuing disclosure and the accompanying figures, those skilled in the art will in part discover these features or will be able to ascertain them through production or use thereof. The features of the present application may be implemented and obtained by practicing or using the various aspects of the methods, tools, and combinations that are set forth in the detailed examples described below.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

The methods, AI systems, and/or procedures in the figures will be further described in terms of exemplary embodiments. These exemplary embodiments will be described in detail with reference to the drawings. These exemplary embodiments are non-limiting exemplary embodiments, wherein reference numerals represent similar mechanisms throughout the several views of the drawings.

Fig. 1 is a block diagram of a data push AI system, shown in accordance with some embodiments of the present application.

Fig. 2 is a schematic diagram of hardware and software components in a server according to some embodiments of the application.

Fig. 3 is a flow chart of a data pushing method based on data analysis according to some embodiments of the application.

Fig. 4 is a schematic diagram of an architecture of a data pushing device according to an embodiment of the present application.

Detailed Description

In order to better understand the above technical solutions, the following detailed description of the technical solutions of the present application is made by using the accompanying drawings and specific embodiments, and it should be understood that the specific features of the embodiments and the embodiments of the present application are detailed descriptions of the technical solutions of the present application, and not limiting the technical solutions of the present application, and the technical features of the embodiments and the embodiments of the present application may be combined with each other without conflict.

In the following detailed description, numerous specific details are set forth by way of examples in order to provide a thorough understanding of the relevant teachings. It will be apparent, however, to one skilled in the art that the application can be practiced without these details. In other instances, well known methods, procedures, AI systems, components, and/or circuits have been described at a relatively high-level, without detail, in order to avoid unnecessarily obscuring aspects of the present application.

These and other features, together with the functions, acts, and combinations of parts and economies of manufacture of the related elements of structure, all of which form part of this application, may become more apparent upon consideration of the following description with reference to the accompanying drawings. It is to be expressly understood, however, that the drawings are for the purpose of illustration and description only and are not intended as a definition of the limits of the application. It should be understood that the drawings are not to scale. It is to be expressly understood, however, that the drawings are for the purpose of illustration and description only and are not intended as a definition of the limits of the application. It should be understood that the figures are not to scale.

The present application uses a flowchart to explain an execution process performed by the AI system according to an embodiment of the present application. It should be clearly understood that the execution of the flowcharts may be performed out of order. Rather, these implementations may be performed in reverse order or concurrently. Additionally, at least one other execution may be added to the flowchart. One or more of the executions may be deleted from the flowchart.

Fig. 1 is a block diagram of an AI system architecture of a data push AI system 300, which data push AI system 300 may include a server 100 and a plurality of clients 200 in communication therewith, in accordance with some embodiments of the application. The client 200 is a device used when a target user clicks push information and accepts push information, and may be, for example, a personal computer, a notebook computer, a tablet computer, a smart phone or the like with a network interaction function.

In some embodiments, please refer to fig. 2, which is a schematic architecture diagram of a server 100, wherein the server 100 includes a data pushing device 110, a memory 120, a processor 130 and a communication unit 140. The memory 120, the processor 130, and the communication unit 140 are electrically connected directly or indirectly to each other to realize data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The data pushing device 110 includes at least one software function module that may be stored in the memory 120 in the form of software or firmware (firmware) or solidified in an operating AI system (OS) of the server 100. The processor 130 is configured to execute executable modules stored in the memory 120, such as software functional modules and computer programs included in the data pushing device 110.

The Memory 120 may be, but is not limited to, a random access Memory (Random Access Memory, RAM), a Read Only Memory (ROM), a programmable Read Only Memory (Programmable Read-Only Memory, PROM), an erasable Read Only Memory (Erasable Programmable Read-Only Memory, EPROM), an electrically erasable Read Only Memory (Electric Erasable Programmable Read-Only Memory, EEPROM), etc. The memory 120 is used for storing a program, and the processor 130 executes the program after receiving an execution instruction. The communication unit 140 is used for establishing a communication connection between the server 100 and the client through a network, and for transceiving data through the network.

The processor may be an integrated circuit chip having signal processing capabilities. The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but also Digital Signal Processors (DSPs)), application Specific Integrated Circuits (ASICs), field Programmable Gate Arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

It is to be understood that the structure shown in fig. 2 is merely illustrative, and that the server 100 may also include more or fewer components than shown in fig. 2, or have a different configuration than shown in fig. 2. The components shown in fig. 2 may be implemented in hardware, software, or a combination thereof.

Fig. 3 is a flowchart of a data pushing method based on data analysis according to some embodiments of the present application, which is applied to the server 100 in fig. 1, and may specifically include the following steps S100-S500. Some alternative embodiments will be described on the basis of the following steps S100-S500, which should be understood as examples and should not be interpreted as essential technical features for implementing the present solution.

S100: and acquiring at least one online product pushing information set of the product category to which the product pushing information set belongs.

By establishing a product pushing information set sequence for a product pushing information set (an information set for introducing a pushed product, including multi-part product introduction information), pertinence and accuracy of product pushing of the product pushing information set are improved, and in a process of establishing the product pushing information set sequence for the product pushing information set, a plurality of online product pushing information sets of product categories to which the product pushing information set belongs can be acquired first. The product category is classification information to which the product pushing information set belongs, for example, a product corresponding to the product pushing information set is shower gel, the product category can be a bath product, and it is to be noted that the precision of product classification can be adaptively adjusted according to the requirement of an actual pushing range, for example, the precision is improved for refinement, the product category can be a bath product for men (women and children), and if the precision is reduced, the product category can be a daily product. It should be noted that, the data and information related in the embodiments of the present application are obtained by legal and reasonable means and approaches.

As some possible embodiments, when the product push information set attribute corresponding to the product push information set sequence is the same series (having the same design theme element or the same efficacy or the same manufacturing process, such as the X-series XX product, having multiple versions of V1, V2, etc.) of product push information sets, the following steps may be used to obtain at least one online product push information set of the product category to which the product push information set belongs: obtaining summary information carried by a product pushing information set, carrying out preset indication information identification on the summary information to obtain preset indication information of the product pushing information set, determining product pushing information set attributes of the product pushing information set according to the preset indication information, and obtaining at least one online product pushing information set of a product category to which the product pushing information set belongs under the condition that the product pushing information set is indicated to be the same-series product pushing information set by the product pushing information set attributes.

Specifically, if the product pushing information set attribute corresponding to the established product pushing information set sequence is the same-series product pushing information set, in other words, if the product pushing information set attribute of the product pushing information set in the product pushing information set sequence is the same-series product pushing information set, when the online product pushing information set of the product category to which the product pushing information set belongs is acquired, the product pushing information set attribute of the product pushing information set is screened. For example, the method is realized by the following steps: the method comprises the steps of obtaining summary information carried by a product pushing information set, for example, information which is briefly described in advance for the product pushing information set, for example, information such as a product name, a product efficacy, a product bright spot and the like, and for example, summary information which is obtained by extracting target product introduction information (for example, product introduction information at a preset position) covered by the product pushing information set, then carrying out preset indication information identification on the summary information carried by the product pushing information set to obtain preset indication information of the product pushing information set, determining the attribute of the product pushing information set according to the preset indication information on the basis, for example, if the extracted summary information of the product pushing information set contains preset indication information such as K9s, K9r, K9pro, first generation, second generation, enlarged version, mini version and the like, determining that the attribute of the product pushing information set is the same series, and the above examples are only used for reference, and are not used as bases for limiting other embodiments.

After the product pushing information set attribute of the product pushing information set is obtained, if the product pushing information set attribute indicates that the product pushing information set is a same-series product pushing information set, then the online product pushing information set of the product category to which the product pushing information set belongs can be obtained again, so that a product pushing information set sequence of the same-series product pushing information set is established according to the product pushing information set. In addition, if the product pushing information set attribute indicates that the product pushing information set is not a product pushing information set of the same series, a product pushing information set sequence of the product pushing information set of the same series cannot be established through the product pushing information set, and then an online product pushing information set of a product category to which the product pushing information set belongs is not required to be acquired.

S200: and determining the relevance indexes of the product push information sets and all online product push information sets one by one, and then identifying at least one undetermined product push information set with the relevance index meeting the preset relevance index from at least one online product push information set.

In step S200, after a plurality of online product push information sets of a product category to which the product push information set belongs are obtained, relevance indexes (degree of relevance formation) of the product push information set and each online product push information set are determined one by one, so that a to-be-determined product push information set with relevance indexes meeting preset relevance indexes is identified in the plurality of online product push information sets. As some possible implementations, the preset relevance index may be a preset relevance index range, an online product pushing information set with relevance indexes in the relevance index range is regarded as a to-be-determined product pushing information set, for example, the relevance index range is from a first relevance index S1 to a second relevance index S2, it is easy to understand that S1 < S2, and then an online product pushing information set with relevance indexes greater than S1 and less than S2 is regarded as a to-be-determined product pushing information set.

The online product pushing information set with the relevance index larger than the second relevance index can be regarded as the same product pushing information set as the product pushing information set, and can also be the periphery (small sample and matched product) of the product pushing information set. The online product push information set of the product category may cover local information (such as gift information and associated supporting product information of the product push information set) of the current product push information set, or may be local information of a product push information set of a certain online product push information set. In this case, after the relevance index is obtained, if the relevance index of the current product pushing information set and the online product pushing information set meets the second relevance index, the online product pushing information set which meets the second relevance index with the current product pushing information set is taken as a target online product pushing information set, the information capacity of the current product pushing information set and the information capacity of the target online product pushing information set are obtained, then the capacity difference of the two information capacities is calculated, if the capacity difference reaches a preset condition, for example, more than 20%, the product pushing information set with larger information capacity in the current product pushing information set and the target online product pushing information set is taken as a product pushing information set to be determined, otherwise, if the capacity difference does not reach the preset condition, one product pushing information set in the current product pushing information set and the target online product pushing information set is randomly obtained and taken as the product pushing information set to be determined.

As some possible embodiments, the following manner may be adopted to determine the relevance index of the product push information set and each online product push information set one by one:

the method comprises the steps of obtaining first summary information carried by a product push information set and second summary information carried by each online product push information set, extracting vectors of the first summary information to obtain first summary information vectors related to the product push information set, extracting vectors of the second summary information carried by each online product push information set one by one to obtain second summary information vectors related to each online product push information set, determining vector relevance indexes of the first summary information vectors and the second summary information vectors one by one, and taking vector relevance indexes of the first summary information vectors and the second summary information vectors as relevance indexes of the product push information set and the online product push information sets.

In the above steps, when the relevance index of the product push information set and each online product push information set is obtained, the relevance index may be determined by the product push information set and summary information carried by each online product push information set, where the summary information may be, for example, information that is briefly described for the product push information set in advance, for example, may include information such as a product name, a product efficacy, a product bright point, and the like, and may be, for example, summary information obtained by extracting target product introduction information (for example, product introduction information at a preset position) covered in the product push information set.

For example, first summary information carried by a product push information set and second summary information carried by each online product push information set are obtained, then vector extraction is carried out on the first summary information to obtain first summary information vectors related to the product push information set, and vector extraction is carried out on each second summary information to obtain second summary information vectors related to each online product push information set. The process of vector extraction may operate using existing techniques, such as extraction using a generic vector extraction model. After the first summary information vector related to the product pushing information set and the second summary information vector related to each online product pushing information set are obtained, determining vector relevance indexes (for example, determining by calculating the distance or the included angle between the vectors) of the first summary information vector and each second summary information vector, and taking the vector relevance indexes of the first summary information vector and each second summary information vector as relevance indexes of the product pushing information set and each online product pushing information set.

As some possible embodiments, the following steps may be used to determine the relevance index of the product push information set and each online product push information set:

The method comprises the steps of obtaining product introduction information of a product pushing information set and product introduction information of each online product pushing information set, extracting vectors of the product introduction information of the product pushing information set to obtain first product introduction information vectors related to the product pushing information set, extracting the product introduction information of each online product pushing information set one by one to obtain second product introduction information vectors related to each online product pushing information set, determining vector relevance indexes of the first product introduction information vectors and each second product introduction information vector one by one, and taking the vector relevance indexes of the first product introduction information vectors and each second product introduction information vector as relevance indexes of the product pushing information set and each online product pushing information set.

In the above steps, in the process of obtaining the relevance index of the product push information set and each online product push information set, the relevance index may be determined according to the product push information set and the product introduction information (including, but not limited to, price, online time, product details, evaluation, detailed display, etc.) covered by each online product push information set, where the product introduction information may be the product push information set or all the product introduction information covered by each online product push information set, or may be the screened product introduction information.

Firstly, acquiring product introduction information of a product pushing information set and product introduction information of each online product pushing information set, wherein the product introduction information can be a plurality of product introduction information, then carrying out vector extraction on the product introduction information of the product pushing information set, namely carrying out vector extraction on each product introduction information to obtain information vectors of each product introduction information, fusing the information vectors of each product introduction information to obtain first product introduction information vectors related to the product pushing information set, carrying out vector extraction on the product introduction information of each online product pushing information set, namely carrying out vector extraction on each product introduction information covered by each online product pushing information set to obtain information vectors of each product introduction information, fusing the information vectors of each product pushing information set to obtain second product introduction information vectors related to each online product pushing information set. After a first product introduction information vector related to a product push information set and a second product introduction information vector related to each online product push information set are obtained, vector relevance indexes between the first product introduction information vector and each second product introduction information vector are determined, and the vector relevance indexes of the first product introduction information vector and each second product introduction information vector are used as relevance indexes of the product push information set and each online product push information set.

As some possible embodiments, if the product push information set attribute corresponding to the product push information set sequence is the same-series product push information set, the following steps may be adopted to determine the relevance index of the product push information set and each online product push information set, as follows:

obtaining summary information carried by each online product push information set one by one, and carrying out preset indication information identification on each summary information to obtain preset indication information of each online product push information set; according to preset indication information, determining the product pushing information set attribute of each online product pushing information set one by one, identifying that the obtained online product pushing information set attribute in the online product pushing information sets is an online product pushing information set of the same series of product pushing information sets, and determining the relevance index of the product pushing information sets and the online product pushing information sets, wherein the product pushing information set attribute is the online product pushing information sets of the same series of product pushing information sets one by one.

In the above step, if the product pushing information set attribute corresponding to the established product pushing information set sequence is the same-series product pushing information set, in other words, the product pushing information set attribute of the product pushing information set in the product pushing information set sequence is the same-series product pushing information set. When the relevance index of the product pushing information set and each online product pushing information set is determined, the same-series product pushing information sets can be selected according to a plurality of online product pushing information sets, and then the relevance index of the product pushing information set and the identified product pushing information set, which is the online product pushing information set of the same-series product pushing information set, is calculated, so that the calculation consumption can be reduced, and the requirement on calculation force is reduced.

The following detailed description is provided, and the product pushing information set attribute of the product pushing information set can be specifically picked up through the following steps:

the method comprises the steps of obtaining summary information carried by a product pushing information set, for example, information which is briefly described for the product pushing information set in advance, such as information including a product name, a product efficacy, a product bright spot and the like, and for example, summary information obtained by extracting target product introduction information (for example, product introduction information at a preset position) covered by the product pushing information set, and then carrying out preset indication information identification on the summary information carried by the product pushing information set to obtain preset indication information of the product pushing information set, so that the attribute of the product pushing information set is determined according to the preset indication information. The foregoing has been exemplified and will not be repeated here.

As some possible embodiments, it may be identified that the association index satisfies not less than one set of pending product push information of the preset association index by:

according to the product pushing information sets and the relevance indexes of all online product pushing information sets, determining at least one online product pushing information set with the relevance index meeting the preset relevance index, and taking the online product pushing information set with the relevance index meeting the preset relevance index as a to-be-determined product pushing information set with the relevance index meeting the preset relevance index.

S300: and acquiring at least one target product pushing information set of which the product pushing information set and the product pushing information set are the same product pushing information set subclass.

After the obtained at least one online product pushing information set is selected through the relevance index, the identified at least one undetermined product pushing information set can be further selected, namely, a target product pushing information set of which the at least one undetermined product pushing information set and the product pushing information set are consistent product pushing information set subclasses is obtained.

As some possible embodiments, the following steps may be taken to obtain not less than one target product push information set of which the pending product push information set and the product push information set are a subset of a consistent product push information set:

the method comprises the steps of obtaining first product pushing information set portrait information of a product pushing information set and second product pushing information set portrait information of each undetermined product pushing information set, comparing the first product pushing information set portrait information with each second product pushing information set portrait information to obtain comparison values of the first product pushing information set portrait information and each second product pushing information set portrait information, and regarding the undetermined product pushing information set corresponding to the second product pushing information set portrait information with the comparison values meeting preset comparison values as a target product pushing information set which is consistent with the product pushing information set in product pushing information set subclass.

When the product pushing information set is generated, the product pushing information set can be subjected to portrait description, and the representation of what user the product pushing information set is applicable to is characterized, for example, portrait information (such as a description mark) of the corresponding product pushing information set is added. When at least one target product pushing information set of which the product pushing information set is a consistent product pushing information set subclass is obtained, first product pushing information set portrait information of the product pushing information set and second product pushing information set portrait information of each product pushing information set are obtained, then the first product pushing information set portrait information and the second product pushing information set portrait information are respectively compared to obtain comparison values of the first product pushing information set portrait information and the second product pushing information set portrait information, and the target product pushing information set corresponding to the second product pushing information set portrait information of which the comparison value meets the preset comparison value is regarded as the target product pushing information set of the consistent product pushing information set subclass.

As some possible embodiments, the target product push information set of which not less than one set of pending product push information and the product push information set are sub-categories of the consistent product push information set may be obtained by:

Carrying out information mining on summary information carried by a product pushing information set to obtain first summary block clusters related to the product pushing information set, carrying out information mining on the summary information carried by each undetermined product pushing information set one by one to obtain second summary block clusters related to each undetermined product pushing information set, and determining summary block matching results between the first summary block clusters and each second summary block cluster one by one; and taking the undetermined product pushing information set corresponding to the second summary block cluster with the summary block matching result reaching the preset matching result as a target product pushing information set which is the same as the product pushing information set in the product pushing information set subclass.

In addition, the summary information of the product pushing information set and the product pushing information set can be analyzed to obtain target product pushing information sets of which the product pushing information sets are consistent (compared with the above product classification, such as child bath products as the sub-class under bath products) in the product pushing information sets.

Specifically, information mining is performed on summary information carried by a product pushing information set to obtain a first summary block cluster related to the product pushing information set, the first summary block cluster comprises a plurality of summary blocks (a word block after splitting operation is performed on the summary information), then information mining is performed on the summary information carried by each undetermined product pushing information set to obtain a second summary block cluster related to each undetermined product pushing information set, the second summary block cluster also comprises a plurality of summary blocks, summary block matching results of the first summary block cluster and each second summary block cluster, for example, the summary block matching results of the first summary block cluster and the summary block matching results of each second summary block cluster are determined one by one, namely, the percentages of the summary blocks are the same, then the to-be-determined product pushing information set corresponding to the second summary block cluster with the summary block matching result meeting the preset matching result is determined from the plurality of to be regarded as a target product pushing information set of a consistent product pushing information set subclass.

As some possible embodiments, the following steps may be further adopted to obtain not less than one target product push information set of which the pending product push information set and the product push information set are a subset of a consistent product push information set:

the method comprises the steps of carrying out information mining on summary information carried by a product pushing information set to obtain first summary block clusters related to the product pushing information set, carrying out information mining on summary information carried by each undetermined product pushing information set one by one to obtain second summary block clusters related to each undetermined product pushing information set, determining the coverage areas of preset unified summary blocks between the first summary block clusters and each second summary block cluster and the preset unified summary blocks in the second summary block clusters one by one, and regarding the undetermined product pushing information set corresponding to the preset unified summary blocks with the coverage areas exceeding a preset range as a target product pushing information set of a class of consistent product pushing information sets.

In the above step, the target product pushing information sets of which the product pushing information sets are the same product pushing information set subclasses can be obtained by analyzing the summary information of the product pushing information sets to be determined and the product pushing information sets. For example, information mining is performed on summary information carried by a product pushing information set to obtain a first summary block cluster related to the product pushing information set, the first summary block cluster is provided with a plurality of summary blocks, information mining is performed on summary information carried by each undetermined product pushing information set to obtain a second summary block cluster related to each undetermined product pushing information set, the second summary block cluster also comprises a plurality of summary blocks, preset unified summary blocks (summary blocks appearing in the first summary block cluster and each second summary block cluster at the same time) between the first summary block cluster and each second summary block cluster are determined one by one, for example, the summary block with the largest length also obtains coverage (occupied percentage) of each preset unified summary block in the second summary block cluster, and then the undetermined product pushing information set corresponding to the preset unified summary block with the coverage exceeding a preset range is determined from the plurality of undetermined product pushing information sets and is regarded as a target product pushing information set of a consistent product pushing information set class.

S400: and establishing a product push information set sequence of the sub-class of the associated product push information set.

In the application, the product pushing information set sequence covers a product pushing information set and a target product pushing information set.

As some possible embodiments, the following steps may be employed to establish a product push information set sequence of associated product push information set subclasses:

under the condition that the number of the target product pushing information sets is multiple, the product pushing information sets and the online time of each target product pushing information set are obtained one by one, the product pushing information sets and each target product pushing information set are classified (sorted and ordered) according to the successive relation of the online time to obtain a first product pushing information set list, a product pushing information set sequence of the sub-class of the related product pushing information sets is established according to the first product pushing information set list, and when the method is implemented, a certain number of target product pushing information sets with newer online time can be used for establishing the product pushing information set sequence covering the product pushing information sets and the target product pushing information sets.

In the above steps, in the process of establishing the product pushing information set sequence of the sub-class of the related product pushing information set according to the product pushing information set and the target product pushing information set, the product pushing information set and the target product pushing information set can be classified, for example, the same series of product pushing information set sequences can be used for classifying the product pushing information sets in the product pushing information set sequence according to the online sequence, for example, V1 and V2, which is beneficial to user selection. For example, in the process of sorting and ranking the product pushing information sets and the target product pushing information sets, the online time of the product pushing information sets and the online time of each target product pushing information set can be obtained one by one, then the product pushing information sets and each target product pushing information set are classified according to the successive relation of the online time to obtain a first product pushing information set list, and finally a product pushing information set sequence is established through the first product pushing information set list.

As some possible embodiments, a product push information set sequence of associated product push information set subclasses may be established based on the following steps:

under the condition that the number of the target product pushing information sets is multiple, first summary information carried by the product pushing information sets and second summary information carried by each target product pushing information set are obtained, product series identification indication information identification is carried out on the first summary information to obtain first product series identifications of the product pushing information sets, then product series identification indication information identification is carried out on each second summary information to obtain second product series identifications of corresponding target product pushing information sets, the product pushing information sets and the target product pushing information sets are classified according to identification indication rules (such as sequence indication relation, size relation, containing relation and the like of the identifications) of the first product series identifications and the second product series identifications, a second product pushing information set list is obtained, and a product pushing information set sequence of a sub-class of the associated product pushing information sets is established through the second product pushing information set list. In the application, the product series identification indication information is configured to represent the online time of the corresponding product pushing information set.

Specifically, the steps can be performed by sorting and classifying the summary information of the product pushing information set and the target product pushing information set. For example, first summary information carried by a product pushing information set and second summary information carried by each target product pushing information set are obtained, then product series identification indication information identification is carried out on the first summary information, a first product series identification of the product pushing information set is obtained, then product series identification indication information identification is carried out on each second summary information, a second product series identification of a corresponding target product pushing information set is obtained, and then the product pushing information set and a plurality of target product pushing information sets are sorted according to the first product series identification and identification indication rules of the second product series identification, so that a second product pushing information set list is obtained.

As some possible embodiments, the product push information set sequence of the associated product push information set subclass may be established by:

under the condition that the number of the target product pushing information sets is multiple, obtaining the product pushing information sets and the online time of each target product pushing information set one by one, determining the time interval of any two online time in each online time, if the determined time interval is smaller than the time interval, respectively carrying out product series identification indication information identification on the product pushing information sets and each target product pushing information set to obtain corresponding product series identification, classifying the product pushing information sets and each target product pushing information set according to the identification indication rule to obtain a third product pushing information set list, and establishing a product pushing information set sequence of the related product pushing information set subclass according to the third product pushing information set list. The product line identification indication information is configured to characterize an online time of a corresponding product push information set.

In the embodiment of the application, the product push information set is likely to be online without being online according to the serial order of the product push information set, for example, the second generation of the product push information set is online earlier than the first generation, and then the classification according to the online time is unreasonable. At this time, the online time of the product push information set and the summary information can be integrated to classify. For example, the product pushing information sets and the online time of each target product pushing information set are obtained one by one, the time interval of any two online times in each online time is determined, if the determined time interval is smaller than the time interval of the preset time interval, the product pushing information sets and each target product pushing information set are respectively identified by product series identification indication information, corresponding product series identifications are obtained, the product pushing information sets and each target product pushing information set are classified according to identification indication rules, a third product pushing information set list is obtained, and finally a product pushing information set sequence of the related product pushing information set subclasses is established according to the third product pushing information set list.

As a possible case, if there is no time interval smaller than the predetermined time interval, the product push information set and the target product push information set are directly classified according to the online time, a fourth product push information set list is obtained, and a product push information set sequence of the related product push information set subclass is established.

S500: and pushing the content associated with the product push information set sequence when the push event triggering the product indicated by any product push information set in the product push information set sequence is detected.

As some possible embodiments, the following steps may be understood to push the content associated with the product push information set sequence:

pushing the content associated with the information set sequence to the client by the push product. The associated content includes a transmission path corresponding to the product push information set sequence and summary information of the product push information set sequence.

In the above steps, when the user browses any one of the product pushing information sets in the product pushing information set sequence, the client responds to the request of clicking, searching and the like of the user, displays the content covered by any one of the product pushing information sets in the product pushing information set sequence, such as price, online time, product details, product evaluation, detail display and the like, and sends a pushing trigger instruction to the server, and after the server obtains the pushing trigger instruction, the server pushes the product pushing information set corresponding to the product pushing information set and the content associated with the product pushing information set sequence belonging to the product pushing information set, wherein the associated content is the content pushing the product pushing information set sequence, and may include the introduction information of the product pushing information set sequence and the transmission path (the display form may be a link) corresponding to the product pushing information set sequence.

Further, after the product push information set sequence of the related product push information set subclass is established through the above embodiment, if a newly online product push information set of the same product category is obtained, determining a relevance index of the newly online product push information set and any product push information set in the product push information set sequence, if the relevance index meets a preset relevance index, determining whether the newly online product push information set corresponds to the product push information set subclass of the product push information set sequence, and if so, merging the newly online product push information set into the established product push information set sequence.

The method comprises the steps of obtaining at least one online product pushing information set of a product category to which the product pushing information set belongs, identifying at least one undetermined product pushing information set of which the relevance index meets a preset relevance index from the at least one online product pushing information set according to relevance indexes between the product pushing information set and each online product pushing information set, and identifying a target product pushing information set which is consistent with the product pushing information set and is a product pushing information set sub-category in the at least one undetermined product pushing information set, so that a product pushing information set sequence of the associated product pushing information set sub-category is established through the product pushing information set and the target product pushing information set.

In the embodiment of the application, because the product pushing information sets are corresponding to the product categories with consistency in the established product pushing information set sequence, and the relevance index accords with the preset relevance index, and is a class of the consistent product pushing information sets, compared with a simple comparison mode, the matching degree among the obtained product pushing information sets is greatly improved, so that when the pushing event triggering the product indicated by any product pushing information set in the product pushing information set sequence is detected, the content associated with the product pushing information set sequence is pushed, and a user can continuously browse similar product pushing information sets which are highly matched with the product pushing information sets and are class of the consistent product pushing information sets through the associated content during the period of browsing the product pushing information sets, the pushing pertinence is enhanced, and the product conversion rate is improved.

Referring to fig. 4, an architecture diagram of a data pushing device 110 according to an embodiment of the present application is provided, where the data pushing device 110 may be used to perform a data pushing method based on data analysis, and the data pushing device 110 includes:

the product push information set obtaining module 111 is configured to obtain at least one online product push information set of a product category to which the product push information set belongs.

The relevance index determining module 112 is configured to determine relevance indexes of the product push information sets and each online product push information set one by one, and then identify, from at least one online product push information set, at least one pending product push information set whose relevance index satisfies a preset relevance index.

The target determining module 113 obtains at least one target product pushing information set of which the undetermined product pushing information set and the product pushing information set are the same product pushing information set subclass;

the establishing module 114 establishes a product push information set sequence of the related product push information set subclass, wherein the product push information set sequence covers the product push information set and the target product push information set;

the pushing module 115 pushes content associated with the product push information set sequence to the client when a push event triggering a product indicated by any product push information set in the product push information set sequence is detected.

The product push information set acquisition module 111 may be configured to perform step S100; the relevance index determining module 112 may be configured to perform step S200; the targeting module 113 may be operable to perform step S300; the setup module 114 may be used to perform step S400; the push module 115 may be used to perform step S500.

Since in the above embodiments, the data pushing method based on data analysis provided in the embodiments of the present application has been described in detail, the principle of the data pushing device 110 is the same as that of the method, and the execution principle of each module of the data pushing device 110 will not be described in detail here.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The apparatus embodiments described above are merely illustrative, for example, of the flowcharts and block diagrams in the figures that illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based AI systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, functional modules in the embodiments of the present invention may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.

The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, 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, article, 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, article, or apparatus that comprises the element.

It is to be understood that the terminology which does not make a noun interpretation with respect to the above description is not to be interpreted as a noun interpretation, and that the skilled person can unambiguously ascertain the meaning to which it refers from the above disclosure. The foregoing disclosure of embodiments of the present application will be apparent to and complete in light of the foregoing disclosure to those skilled in the art. It should be appreciated that the development and analysis of technical terms not explained based on the above disclosure by those skilled in the art is based on the description of the present application, and thus the above is not an inventive judgment of the overall scheme.

While the basic concepts have been described above, it will be apparent to those skilled in the art that the foregoing detailed disclosure is by way of example only and is not intended to be limiting. Although not explicitly described herein, various modifications, improvements and adaptations of the application may occur to one skilled in the art. Such modifications, improvements, and modifications are intended to be suggested within the present disclosure, and therefore, such modifications, improvements, and adaptations are intended to be within the spirit and scope of the exemplary embodiments of the present disclosure.

It should also be appreciated that in the foregoing description of at least one embodiment of the application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of at least one embodiment of the application. This method of disclosure, however, is not intended to imply that more features than are required by the subject application. Indeed, less than all of the features of a single embodiment disclosed above.

Claims

1. A data pushing method based on data analysis, which is applied to a server, wherein the server is in communication connection with a client, the method comprising:

pushing content associated with the product pushing information set sequence to the client when a pushing event triggering a product indicated by any product pushing information set in the product pushing information set sequence is detected;

The obtaining the target product pushing information set of which the number of the product pushing information sets is not less than one and the product pushing information set is a subclass of the consistent product pushing information set comprises one of the following modes:

Or carrying out information mining on the summary information carried by the product push information set to obtain a first summary block cluster related to the product push information set; carrying out information mining on summary information carried by each set of the pending product push information one by one to obtain second summary block clusters related to each set of the pending product push information; determining preset unified summary blocks between the first summary block cluster and each second summary block cluster one by one, and covering the preset unified summary blocks in the second summary block clusters; taking a to-be-determined product pushing information set corresponding to a preset unified summary block with a coverage exceeding a preset range as a target product pushing information set which is a product pushing information set subclass consistent with the product pushing information set;

the pushing the content associated with the product push information set sequence to the client comprises the following steps:

pushing the content associated with the product pushing information set sequence to the client, wherein the associated content comprises a transmission path corresponding to the product pushing information set sequence and summary information of the product pushing information set sequence.

2. The method of claim 1, wherein when the product push information set attribute corresponding to the product push information set sequence is a same-series product push information set, the obtaining at least one online product push information set of a product category to which the product push information set belongs includes:

Acquiring summary information carried by the product pushing information set;

3. The method of claim 1, wherein when the product push information set attribute corresponding to the product push information set sequence is a same-series product push information set, the one-to-one determining the association index of the product push information set and each of the online product push information sets comprises:

4. The method of claim 1, wherein the one-to-one determination of the association index of the product push information set and each of the online product push information sets comprises:

5. The method of claim 1, wherein the one-to-one determination of the association index of the product push information set and each of the online product push information sets comprises:

6. The method of claim 1, wherein identifying from the set of no less than one online product push information that the relevance index satisfies the set of no less than one pending product push information for which the preset relevance index is a set of relevance indices, comprises:

7. The method of claim 1, wherein the establishing a product push information set sequence associated with the product push information set subclass comprises one of:

8. A data push AI system comprising a server and a client in communication with each other, the server comprising a processor and a memory, the memory storing a computer program, the processor, when running the program, implementing the method of any of claims 1-7.