CN112182098B

CN112182098B - Information push method and information push server based on cloud computing and big data

Info

Publication number: CN112182098B
Application number: CN202010968581.3A
Authority: CN
Inventors: 张明明; 王鹏飞; 陶晔波; 卢霞浩
Original assignee: Information and Telecommunication Branch of State Grid Jiangsu Electric Power Co Ltd
Current assignee: Information and Telecommunication Branch of State Grid Jiangsu Electric Power Co Ltd
Priority date: 2020-09-15
Filing date: 2020-09-15
Publication date: 2021-08-31
Anticipated expiration: 2040-09-15
Also published as: CN113051344A; CN113051345A; CN112182098A

Abstract

The embodiment of the application provides an information pushing method and an information pushing server based on cloud computing and big data, and the method comprises the steps of obtaining business subscription operation information fed back by a plurality of digital financial terminals aiming at information hotspot information, determining a target business subscription tag group corresponding to the information hotspot information according to the business subscription operation information, adjusting a distribution strategy aiming at the information hotspot information according to the target business subscription tag group, and updating the target information hotspot information distributed to the plurality of digital financial terminals according to the adjusted distribution strategy of the information hotspot information, so that the distribution strategy of the information hotspot information is timely and quickly adjusted based on a feedback mechanism of business subscription operation, and the matching degree of subsequent information distribution is improved.

Description

Information push method and information push server based on cloud computing and big data

Technical Field

The application relates to the technical field of cloud computing and big data, in particular to an information pushing method and an information pushing server based on cloud computing and big data.

Background

With the rapid development of cloud computing and big data technology, the application range of the cloud computing and big data technology is wider and wider, and the big data business information can be analyzed by applying the strong cloud computing capability of the cloud computing and big data based information push server, so that the intention development rules of a large number of users are recognized, and the subsequent business service updating and product technology research and development are facilitated.

However, in the related art, in the process of information distribution after acquiring the hotspot information association map including the hotspot information, a feedback mechanism of related service subscription operation is lacked, so that a subsequent cloud-based information push server based on cloud computing and big data cannot quickly adjust a distribution strategy of the information hotspot information in time, and further the matching degree of information distribution is affected.

Disclosure of Invention

In order to overcome at least the above disadvantages in the prior art, an object of the present application is to provide an information push method and an information push server based on cloud computing and big data, by obtaining service subscription operation information fed back by a plurality of digital financial terminals for information hotspot information, according to the service subscription operation information, then determining a target service subscription tag group corresponding to the information hotspot information, adjusting a distribution strategy for the information hotspot information according to the target service subscription tag group, and updating the target information hotspot information distributed to the plurality of digital financial terminals according to the adjusted distribution strategy for the information hotspot information, thereby adjusting the distribution strategy for the information hotspot information in time and quickly based on a feedback mechanism of service subscription operation, and improving the matching degree of subsequent information distribution.

In a first aspect, the present application provides an information push method based on cloud computing and big data, which is applied to an information push server based on cloud computing and big data, where the information push server based on cloud computing and big data is in communication connection with a plurality of digital financial terminals, and the method includes:

acquiring a pre-generated hotspot information association map comprising target hotspot information, and generating corresponding information hotspot information distributed to the plurality of digital financial terminals according to the hotspot information association map comprising the target hotspot information, wherein the pre-generated hotspot information association map comprising the target hotspot information is obtained by processing based on pre-collected service big data record information;

acquiring service subscription operation information fed back by the plurality of digital financial terminals aiming at the information hotspot information;

determining a target service subscription tag group corresponding to the information hotspot information according to the service subscription operation information, and adjusting a distribution strategy aiming at the information hotspot information according to the target service subscription tag group;

and updating target information hotspot information distributed to the plurality of digital financial terminals according to the adjusted distribution strategy of the information hotspot information.

In a possible implementation manner of the first aspect, the step of generating, according to the hotspot information association map including the target hotspot information, information hotspot information distributed to the plurality of digital financial terminals includes:

extracting a hot spot map node unit corresponding to each target hot spot information in the hot spot information association map, and extracting hot spot label feature vectors of the hot spot map node units in parallel while acquiring an original information hot spot service list associated with the hot spot map node units in pushing from a map data source of the hot spot map node units;

determining screening rule information for screening the original information hotspot service list based on the extracted hotspot tag feature vector, extracting rule matching parameters of a plurality of screening rule nodes to be used and service association information among different screening rule nodes from the screening rule information, and screening the plurality of screening rule nodes to be used according to the rule matching parameters and the service association information to obtain at least two target screening rule elements; the coverage characteristic range of the rule matching parameters of the target screening rule elements is located in a set characteristic range, and the difference degree of the service association information between different target screening rule elements is smaller than a set value;

screening the original information hotspot service list through the target screening rule element to obtain an information hotspot service list to be pushed;

determining hotspot tag compatible distribution of the information hotspot service list to be pushed according to a target hotspot tag feature vector determined from a preset subscription hotspot record, and determining hotspot tag expansion distribution of the information hotspot service list to be pushed according to the determined service tags in the information hotspot service list to be pushed;

and extracting key information hotspot information from the information hotspot service list to be pushed based on the hotspot tag compatible distribution and the hotspot tag extended distribution to obtain a key information hotspot information set, and respectively distributing the key information hotspot information set to the plurality of digital financial terminals.

In a possible implementation manner of the first aspect, the step of extracting the hotspot tag feature vector of the hotspot graph node unit in parallel while acquiring the original information hotspot service list associated with the hotspot graph node unit during pushing from the graph data source of the hotspot graph node unit includes:

generating an index condition corresponding to data index structure information of the map data source, sending the index condition through a software development interface pre-established with the map data source, and detecting whether the index state of the hotspot map node unit is in an activated state or not while sending the index condition;

when the index state is detected to be in the activated state, associating a synchronous extraction tag with an index control corresponding to the hotspot graph node unit so that the index control corresponding to the hotspot graph node unit synchronously feeds back an original information hotspot service list obtained by querying from the graph data source based on the index condition and the hotspot tag feature vector extracted from the running record corresponding to the index state through the synchronous extraction tag;

when the index state is detected to be in an inactivated state, generating a synchronous extraction tag according to the index sequence delay of the index state and issuing the synchronous extraction tag to an index control corresponding to the hotspot graph node unit, so that the index control corresponding to the hotspot graph node unit starts the index state according to the synchronous extraction tag and extracts the hotspot tag feature vector from a running record corresponding to the index state, the index control corresponding to the hotspot graph node unit inquires an original information hotspot service list from the graph data source according to the synchronous extraction tag delay on the basis of the index condition, and synchronously receives the hotspot tag feature vector and the original information hotspot service list fed back by the index control corresponding to the hotspot graph node unit.

In a possible implementation manner of the first aspect, the step of determining, based on the extracted hotspot tag feature vector, screening rule information for screening the original information hotspot service list, and extracting rule matching parameters of a plurality of screening rule nodes to be used and service association information between different screening rule nodes from the screening rule information includes:

determining a plurality of feature vector sets with different theme types from the hotspot tag feature vectors, and constructing a first screening rule set and a second screening rule set according to the feature vector sets, wherein the first screening rule set is a global screening rule set, and the second screening rule set is a specific object screening rule set;

mapping a description vector corresponding to any one first screening rule in the first screening rule set to a second screening rule on a corresponding node in the second screening rule set, and determining description vector mapping element information of the description vector in the second screening rule;

determining a target message queue commonly used by the hotspot tag feature vector in a set service range based on a layering parameter between the description vector mapping element information and target description information in the second screening rule, analyzing message queue content information corresponding to the target message queue, and generating the screening rule information through information features indicated by the message queue content information;

listing the screening rule information in a topological structure to obtain a plurality of initial screening rule nodes, determining the screening hierarchy of each initial screening rule node according to the topological relation hierarchy of the screening rule information, sequencing the initial screening rule nodes according to the descending order of the screening hierarchies, and selecting a target number of initial screening rule nodes with the top sequence as the screening rule nodes to be used;

determining component execution parameters and function calling parameters of a transaction distribution component of each screening rule node to be used, determining a distribution rule use graph-based reference of the screening rule node according to the component execution parameters, and extracting rule matching parameters from the distribution rule use graph-based reference according to the function calling parameters; and

calculating a rule coincidence parameter between every two screening rule nodes aiming at every two screening rule nodes in the plurality of screening rule nodes to be used, determining the image feature information of every two screening rule nodes on the service process based on the rule coincidence parameter, and extracting the service correlation information between every two screening rule nodes from the image feature information.

In a possible implementation manner of the first aspect, the step of screening the original information hotspot service list by using the target screening rule element to obtain an information hotspot service list to be pushed includes:

determining the distribution of the screened message themes of the original information hotspot service list from the target screening rule elements; the screening message topic distribution is used for representing topic distribution information of the original information hotspot service list in the hotspot graph node unit;

determining topic matching parameters of the original information hotspot service list according to topic distribution information in the screened message topic distribution, and acquiring target topic matching parameters with subscribed topic labels in the topic matching parameters;

and screening the original information hot spot service list according to an inverse matrix of a distribution matrix corresponding to the screened message topic distribution, and screening a target data field corresponding to the content corresponding to the subscription topic tag of the target topic matching parameter in the original information hot spot service list by adopting the target topic matching parameter in the screening process to obtain the information hot spot service list to be pushed.

In a possible implementation manner of the first aspect, the step of determining, according to a target hotspot tag feature vector determined from a preset subscription hotspot record, hotspot tag compatible distribution of the information hotspot service list to be pushed, and determining, according to a service tag in the information hotspot service list to be pushed, hotspot tag extended distribution of the information hotspot service list to be pushed includes:

extracting hotspot record information which does not change along with the update of the subscription hotspot record from a preset subscription hotspot record, extracting items to which hotspot tags belong in the hotspot record information, and identifying compatibility parameters generated when the items to which the hotspot tags belong are established from the items to which the hotspot tags belong;

determining the target hotspot tag feature vector from a preset subscription hotspot record according to the compatibility parameter, importing coding information corresponding to the target hotspot tag feature vector into a preset coding information list, and setting a compatible tag for the coding information imported into the coding information list each time;

determining a coding compatibility distribution coefficient between different pieces of coding information according to each piece of coding information in the coding information list and the coding weight of the coding information;

generating hotspot tag compatible distribution of the information hotspot service list to be pushed according to each determined coding compatible distribution coefficient and the position of each coding compatible distribution coefficient in the coding information list;

and determining an extended service tag corresponding to a service tag in the information hotspot service list to be pushed, and combining the service tag with the corresponding extended service tag to generate hotspot tag extended distribution of the information hotspot service list to be pushed.

In a possible implementation manner of the first aspect, the step of determining, according to the service subscription operation information, a target service subscription tag group corresponding to the information hotspot information includes:

acquiring a plurality of subscription label coverage objects corresponding to a service subscription label group based on any service subscription label group in service subscription operation information, wherein the service subscription operation information comprises a plurality of service subscription operation targets and a service relation between the service subscription operation targets, the service subscription label group comprises any service subscription operation target pair in the plurality of service subscription operation targets and a service relation between the service subscription operation targets in the service subscription operation target pair, and the subscription label coverage objects comprise the service subscription operation target pair;

based on the plurality of subscription label coverage objects, performing relationship prediction to obtain probabilities that relationships among service subscription operation targets expressed by the plurality of subscription label coverage objects respectively belong to a plurality of relationship labels, wherein the plurality of relationship labels comprise relationship labels of the service relationships;

determining the probability that the relation between the business subscription operation targets expressed by the plurality of subscription label coverage objects belongs to the relation label of the business relation as the corresponding relation parameter of the plurality of subscription label coverage objects;

determining a confidence level of the service subscription tag group based on the relationship parameter, wherein the confidence level is used for representing the credibility of the service relationship included in the service subscription tag group;

and determining the service subscription tag group with the confidence coefficient meeting the target processing condition as a target service subscription tag group.

In a possible implementation manner of the first aspect, the obtaining, based on any service subscription tag group in the service subscription operation information, a plurality of subscription tag coverage objects corresponding to the service subscription tag group includes:

the service subscription operation target pair included in the service subscription tag group is used as an index target to be indexed, and a plurality of initial subscription tag covering objects corresponding to the service subscription tag group are obtained;

extracting the service subscription operation targets of the initial subscription label covered objects to obtain the service subscription operation target in each initial subscription label covered object;

determining an initial subscription label covered object meeting a first target condition as the subscription label covered object, wherein the first target condition is that service subscription operation targets which are respectively the same as two service subscription operation targets in the service subscription operation target pair exist in the extracted service subscription operation targets;

the service subscription tag group further includes a service subscription operation target type of a service subscription operation target in the service subscription operation target pair, and the subscription tag overlay object further satisfies a second target condition, where the second target condition is that the service subscription operation target type corresponding to the extracted service subscription operation target is the same as the service subscription operation target type corresponding to the service subscription operation target included in the service subscription tag group.

In a possible implementation manner of the first aspect, the step of acquiring, based on any service subscription tag group in the service subscription operation information, a plurality of subscription tag overlay objects corresponding to the service subscription tag group includes:

based on any service subscription operation target in the service subscription operation target pair, acquiring a similar service subscription operation target corresponding to the service subscription operation target, wherein the relation between the similar service subscription operation target and the other service subscription operation target in the service subscription operation target pair is equal to the service relation;

replacing the service subscription operation target with a corresponding similar service subscription operation target to obtain an extended service subscription tag group corresponding to the service subscription tag group;

and determining a subscription tag coverage object corresponding to the extended service subscription tag group as the subscription tag coverage object, wherein the subscription tag coverage object corresponding to the extended service subscription tag group comprises a service subscription operation target pair in the extended service subscription tag group.

For example, in a possible implementation manner of the first aspect, the performing relationship prediction based on the plurality of subscription tag overlay objects to obtain probabilities that relationships between service subscription operation targets expressed by the plurality of subscription tag overlay objects respectively belong to a plurality of relationship tags includes:

inputting each subscription label coverage object into a first relation prediction network to obtain the probability that the relation between the service subscription operation targets expressed by each subscription label coverage object belongs to the plurality of relation labels respectively, wherein the first relation prediction network is used for classifying the relation of the service subscription operation target pairs in the subscription label coverage objects;

the determining, as the relationship parameter corresponding to the plurality of subscription label overlay objects, the probability that the relationship between the service subscription operation targets expressed by the plurality of subscription label overlay objects belongs to the relationship label of the service relationship includes:

and determining the probability that the relation between the business subscription operation targets expressed by each subscription label covering object belongs to the relation label of the business relation as a first relation parameter corresponding to the plurality of subscription label covering objects.

inputting a data set formed by the plurality of subscription label coverage objects into a second relation prediction network to obtain the probability that the relations expressed by the data set belong to the plurality of relation labels respectively, wherein the second relation prediction network is used for classifying the relations expressed by the data set, and the relations expressed by the data set are the relations of the service subscription operation target pairs;

and determining the probability that the relation expressed by the data set belongs to the relation label of the business relation as a second relation parameter corresponding to the plurality of subscription label coverage objects.

In a second aspect, an embodiment of the present application further provides an information push apparatus based on cloud computing and big data, which is applied to an information push server based on cloud computing and big data, where the information push server based on cloud computing and big data is in communication connection with a plurality of digital financial terminals, and the apparatus includes:

the generating module is used for acquiring a pre-generated hotspot information association map comprising target hotspot information and generating corresponding information hotspot information distributed to the plurality of digital financial terminals according to the hotspot information association map comprising the target hotspot information, wherein the pre-generated hotspot information association map comprising the target hotspot information is obtained by processing based on pre-collected service big data record information;

the acquisition module is used for acquiring the service subscription operation information fed back by the plurality of digital financial terminals aiming at the information hotspot information;

the adjusting module is used for determining a target service subscription tag group corresponding to the information hotspot information according to the service subscription operation information and adjusting a distribution strategy aiming at the information hotspot information according to the target service subscription tag group;

and the updating module is used for updating the target information hotspot information distributed to the plurality of digital financial terminals according to the adjusted distribution strategy of the information hotspot information.

In a third aspect, an embodiment of the present application further provides an information push system based on cloud computing and big data, where the information push system based on cloud computing and big data includes an information push server based on cloud computing and big data and a plurality of digital financial terminals in communication connection with the information push server based on cloud computing and big data;

the cloud computing and big data based information push server is used for acquiring a pre-generated hot spot information association map comprising target hot spot information, and generating and distributing corresponding information hot spot information to the plurality of digital financial terminals according to the hot spot information association map comprising the target hot spot information, wherein the pre-generated hot spot information association map comprising the target hot spot information is obtained by processing based on pre-collected service big data record information;

the information push server based on cloud computing and big data is used for acquiring service subscription operation information fed back by the plurality of digital financial terminals aiming at the information hotspot information;

the information push server based on cloud computing and big data is used for determining a target service subscription tag group corresponding to the information hotspot information according to the service subscription operation information and adjusting a distribution strategy aiming at the information hotspot information according to the target service subscription tag group;

the information push server based on cloud computing and big data is used for updating target information hotspot information distributed to the plurality of digital financial terminals according to the adjusted distribution strategy of the information hotspot information.

In a fourth aspect, an embodiment of the present application further provides an information push server based on cloud computing and big data, where the information push server based on cloud computing and big data includes a processor, a machine-readable storage medium, and a network interface, where the machine-readable storage medium, the network interface, and the processor are connected through a bus system, the network interface is used for being in communication connection with at least one digital financial terminal, the machine-readable storage medium is used for storing a program, an instruction, or a code, and the processor is used for executing the program, the instruction, or the code in the machine-readable storage medium to perform the information push method based on cloud computing and big data in the first aspect or any one of possible implementation manners in the first aspect.

In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, and when the instructions are executed, the computer executes the cloud computing and big data based information pushing method in the first aspect or any one of the possible implementation manners of the first aspect.

Based on any one of the above aspects, the method and the system for providing the information hotspot information acquire the service subscription operation information fed back by the plurality of digital financial terminals aiming at the information hotspot information, then determine the target service subscription tag group corresponding to the information hotspot information according to the service subscription operation information, adjust the distribution strategy aiming at the information hotspot information according to the target service subscription tag group, and update the target information hotspot information distributed to the plurality of digital financial terminals according to the adjusted distribution strategy of the information hotspot information, so that the distribution strategy of the information hotspot information is rapidly adjusted in time based on a feedback mechanism of the service subscription operation, and the matching degree of subsequent information distribution is improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that need to be called in the embodiments are briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.

Fig. 1 is a schematic view of an application scenario of an information push system based on cloud computing and big data according to an embodiment of the present application;

fig. 2 is a schematic flowchart of an information pushing method based on cloud computing and big data according to an embodiment of the present application;

fig. 3 is a schematic functional module diagram of an information pushing device based on cloud computing and big data according to an embodiment of the present application;

fig. 4 is a schematic block diagram of structural components of an information push server based on cloud computing and big data for implementing the above-mentioned information push method based on cloud computing and big data according to an embodiment of the present application.

Detailed Description

The present application will now be described in detail with reference to the drawings, and the specific operations in the method embodiments may also be applied to the apparatus embodiments or the system embodiments.

Fig. 1 is an interaction diagram of an information push system 10 based on cloud computing and big data according to an embodiment of the present application. The cloud computing and big data based information push system 10 may include a cloud computing and big data based information push server 100 and a digital financial terminal 200 communicatively connected to the cloud computing and big data based information push server 100. The cloud computing and big data based information push system 10 shown in fig. 1 is only one possible example, and in other possible embodiments, the cloud computing and big data based information push system 10 may also include only a part of the components shown in fig. 1 or may also include other components.

In this embodiment, the digital financial terminal 200 may comprise a mobile device, a tablet computer, a laptop computer, etc., or any combination thereof. In some embodiments, the mobile device may include an internet of things device, a wearable device, a smart mobile device, a virtual reality device, an augmented reality device, or the like, or any combination thereof. In some embodiments, the internet of things device may include a control device of a smart appliance device, a smart monitoring device, a smart television, a smart camera, and the like, or any combination thereof. In some embodiments, the wearable device may include a smart bracelet, a smart lace, smart glass, a smart helmet, a smart watch, a smart garment, a smart backpack, a smart accessory, or the like, or any combination thereof. In some embodiments, the smart mobile device may include a smartphone, a personal digital assistant, a gaming device, and the like, or any combination thereof. In some embodiments, the virtual reality device and the augmented reality device may include a virtual reality helmet, virtual reality glass, a virtual reality patch, an augmented reality helmet, augmented reality glass, an augmented reality patch, or the like, or any combination thereof. For example, virtual reality devices and augmented reality devices may include various virtual reality products and the like.

In this embodiment, the cloud computing and big data based information push server 100 and the digital financial terminal 200 in the cloud computing and big data based information push system 10 may cooperatively perform the cloud computing and big data based information push method described in the following method embodiment, and specifically, the performing steps of the cloud computing and big data based information push server 100 and the digital financial terminal 200 may refer to the detailed description of the following method embodiment.

Based on the inventive concept of the technical scheme provided by the application, the cloud computing and big data based information push server 100 provided by the application can be applied to scenes such as smart medical treatment, smart city management, smart industrial internet, general service monitoring management and the like, in which big data technology or cloud computing technology can be applied, and for example, the application can also be applied to new energy automobile system management, smart cloud office, cloud platform data processing, cloud game data processing, cloud live broadcast processing, cloud automobile management platform, block chain financial data service platform and the like, but is not limited thereto.

In order to solve the technical problem in the foregoing background, fig. 2 is a schematic flowchart of an information pushing method based on cloud computing and big data according to an embodiment of the present application, where the information pushing method based on cloud computing and big data according to the present embodiment may be executed by the information pushing server 100 based on cloud computing and big data shown in fig. 1, and the information pushing method based on cloud computing and big data is described in detail below.

Step S110, acquiring a pre-generated hotspot information association map comprising target hotspot information, and generating and distributing corresponding information hotspot information to a plurality of digital financial terminals according to the hotspot information association map comprising the target hotspot information.

Step S120, service subscription operation information fed back by the plurality of digital financial terminals aiming at the information hotspot information is obtained.

Step S130, according to the service subscription operation information, determining a target service subscription tag group corresponding to the information hotspot information, and adjusting a distribution strategy aiming at the information hotspot information according to the target service subscription tag group.

Step S140, updating the target information hotspot information distributed to the plurality of digital financial terminals according to the adjusted distribution strategy of the information hotspot information.

In this embodiment, the pre-generated hotspot information associated map including the target hotspot information is obtained by processing based on the service big data record information collected in advance. For example, the service big data record information can be obtained by processing according to the information distribution rule and the distributed cloud computing task. In this embodiment, the information distribution rule may include an information distribution collection item subscribed by the service provider in advance, where the information distribution collection item may refer to a service type tag referred to when performing subsequent information distribution, and thus, the corresponding service big data record information may be collected based on the service type tag. The cloud computing task may include a task node for performing classification processing on the service big data record information, such as a trigger time node, or a trigger service node, and is not limited in particular herein. Therefore, the service big data record information can be classified to obtain classified service big data record information, and the specific classification processing mode can be used for classifying and analyzing the service big data record information based on a pre-configured classification principle.

In this embodiment, the service subscription operation information may be used to represent service subscription operations executed by users of each digital financial terminal in the use process of the distributed information hotspot information, such as service collection, service click, service access, service denial, and the like.

In this embodiment, after the target service subscription tag group is determined, the distribution policy for the information hotspot information may be adjusted according to the target service subscription tag group, for example, the target information hotspot information may be matched from the original information hotspot information according to each target service subscription tag in the target service subscription tag group, and then a distribution policy that takes the target information hotspot information as a distribution object is generated. Therefore, the adjusted distribution strategy of the information hotspot information can update the target information hotspot information distributed to the plurality of digital financial terminals, and then the next information distribution operation is carried out.

Based on the steps, by acquiring the service subscription operation information fed back by the plurality of digital financial terminals aiming at the information hotspot information, according to the service subscription operation information, determining a target service subscription tag group corresponding to the information hotspot information, adjusting the distribution strategy aiming at the information hotspot information according to the target service subscription tag group, and updating the target information hotspot information distributed to the plurality of digital financial terminals according to the adjusted distribution strategy of the information hotspot information, the distribution strategy of the information hotspot information is timely and quickly adjusted based on a feedback mechanism of the service subscription operation, and the matching degree of subsequent information distribution is improved.

In one possible implementation, step S110 may be implemented by the following exemplary sub-steps, which are described in detail below.

And the substep S111 is to extract a hot spot map node unit corresponding to each target hot spot information in the hot spot information association map, and extract hot spot label feature vectors of the hot spot map node units in parallel while acquiring an original information hot spot service list associated with the hot spot map node units in pushing from a map data source of the hot spot map node units.

And a substep S112, determining screening rule information for screening an original information hotspot service list based on the extracted hotspot tag feature vector, extracting rule matching parameters of a plurality of screening rule nodes to be used and service association information among different screening rule nodes from the screening rule information, and screening the plurality of screening rule nodes to be used according to the rule matching parameters and the service association information to obtain at least two target screening rule elements.

The coverage characteristic range of the rule matching parameters of the target screening rule elements is located in the set characteristic range, and the difference degree of the service association information between different target screening rule elements is smaller than a set value.

And a substep S113, screening the original information hotspot service list through the target screening rule element to obtain an information hotspot service list to be pushed.

And a substep S114, determining the hotspot tag compatible distribution of the information hotspot service list to be pushed according to the target hotspot tag feature vector determined from the preset subscription hotspot record, and determining the hotspot tag extended distribution of the information hotspot service list to be pushed according to the service tags in the determined information hotspot service list to be pushed.

And a substep S115, extracting key information hotspot information from the information hotspot service list to be pushed based on hotspot tag compatible distribution and hotspot tag extended distribution to obtain a key information hotspot information set, and respectively distributing the key information hotspot information set to a plurality of digital financial terminals.

In one possible implementation, to improve the information indexing efficiency, the sub-step S111 may be implemented by the following exemplary embodiments.

(1) And generating an index condition corresponding to the data index structure information of the map data source, sending the index condition through a software development interface which is pre-established with the map data source, and detecting whether the index state of the hotspot map node unit is in an activated state or not while sending the index condition.

(2) And when the index state is detected to be in the activated state, associating the synchronous extraction labels with the index controls corresponding to the hotspot spectrum node units so that the index controls corresponding to the hotspot spectrum node units synchronously feed back original information hotspot service lists obtained by inquiring from the spectrum data source based on the index conditions and hotspot label feature vectors extracted from the running records corresponding to the index state through the synchronous extraction labels.

(3) When the index state is detected to be in an inactivated state, generating synchronous extraction labels according to the index sequence delay of the index state and issuing the synchronous extraction labels to the index controls corresponding to the hotspot graph node units, so that the index controls corresponding to the hotspot graph node units start the index state according to the synchronous extraction labels and extract hotspot label feature vectors from the running records corresponding to the index state, the index controls corresponding to the hotspot graph node units inquire and obtain an original information hotspot service list from a graph data source according to the synchronous extraction labels delay and on the basis of the index condition, and the hotspot label feature vectors and the original information hotspot service list fed back by the index controls corresponding to the hotspot graph node units are synchronously received.

In one possible implementation, the sub-step S112 may be implemented by the following exemplary embodiments.

(1) Determining a plurality of feature vector sets with different theme types from the hotspot tag feature vectors, and constructing a first screening rule set and a second screening rule set according to the feature vector sets.

It should be noted that the first filtering rule set is a global filtering rule set, and the second filtering rule set is a specific object filtering rule set.

(2) And mapping the description vector corresponding to any one first screening rule in the first screening rule set to a second screening rule on a corresponding node in the second screening rule set, and determining the description vector mapping element information of the description vector in the second screening rule.

(3) And determining a target message queue commonly used by the hotspot tag feature vector in a set service range based on the hierarchical parameter between the description vector mapping element information and the target description information in the second screening rule, analyzing message queue content information corresponding to the target message queue, and generating screening rule information according to the information features indicated by the message queue content information.

(4) The screening rule information is listed in a topological structure to obtain a plurality of initial screening rule nodes, the screening hierarchy of each initial screening rule node is determined according to the topological relation hierarchy of the screening rule information, the initial screening rule nodes are sequenced according to the sequence of the screening hierarchies from large to small, and the initial screening rule nodes with the target number in the front of the sequence are selected as the screening rule nodes to be used.

(5) And aiming at each screening rule node to be used, determining component execution parameters and function calling parameters of a transaction distribution component of the screening rule node, determining a distribution rule use graph certificate of the screening rule node according to the component execution parameters, and extracting rule matching parameters from the distribution rule use graph certificate according to the function calling parameters.

(6) Calculating a rule coincidence parameter between every two screening rule nodes aiming at every two screening rule nodes in the plurality of screening rule nodes to be used, determining the image identification characteristic information of every two screening rule nodes on the service process based on the rule coincidence parameter, and extracting the service correlation information between every two screening rule nodes from the image identification characteristic information.

In one possible implementation, the sub-step S113 may be implemented by the following exemplary embodiments.

(1) And determining the distribution of the screened message topics of the original information hotspot service list from the target screening rule elements.

The screening message topic distribution is used for representing topic distribution information of an original information hotspot service list in a hotspot graph node unit.

(2) And determining the topic matching parameters of the original information hotspot service list according to the topic distribution information in the screened message topic distribution, and acquiring the target topic matching parameters of the subscribed topic labels in the topic matching parameters.

(3) And screening the original information hot spot service list according to an inverse matrix of a distribution matrix corresponding to the screened message topic distribution, and screening a target data field corresponding to the content corresponding to the subscription topic tag of the target topic matching parameter in the original information hot spot service list by adopting the target topic matching parameter in the screening process to obtain the information hot spot service list to be pushed.

In one possible implementation, the substep S114 may be implemented by the following exemplary embodiments.

(1) And extracting hotspot record information which does not change along with the update of the subscription hotspot record from a preset subscription hotspot record, extracting items to which the hotspot tags belong in the hotspot record information, and identifying the compatibility parameters generated when the items to which the hotspot tags belong are established from the items to which the hotspot tags belong.

(2) And determining a target hotspot tag feature vector from a preset subscription hotspot record according to the compatibility parameter, importing coding information corresponding to the target hotspot tag feature vector into a preset coding information list, and setting a compatible tag for the coding information imported into the coding information list each time.

(3) And determining the coding compatibility distribution coefficient between different pieces of coding information according to each piece of coding information in the coding information list and the coding weight of the coding information.

(4) And generating the hotspot tag compatible distribution of the information hotspot service list to be pushed according to each determined coding compatible distribution coefficient and the position of each coding compatible distribution coefficient in the coding information list.

(5) And determining an extended service tag corresponding to a service tag in the information hotspot service list to be pushed, and combining the service tag with the corresponding extended service tag to generate hotspot tag extended distribution of the information hotspot service list to be pushed.

In one possible implementation, for example, the substep S115 may be implemented by the following exemplary embodiments.

(1) The method comprises the following steps of extracting key information hotspot information of an information hotspot service list to be pushed based on hotspot tag compatible distribution and hotspot tag extended distribution to obtain a key information hotspot information set, wherein the steps comprise:

(2) and carrying out service distribution on the information hotspot service list to be pushed based on hotspot tag expansion distribution to obtain a plurality of distribution service objects, and calculating the distribution service influence of each distribution service object according to the incidence relation between each distribution service object and other distribution service objects.

(3) And sequencing the shunting service objects according to the descending order of the influence of the shunting service to obtain a shunting service object sequencing set.

(4) And sequentially extracting key information hot spot information of each shunting service object in the sequencing set of the shunting service objects based on the compatibility distribution of the hot spot labels, and calculating the current hot spot influence parameters and the current compatibility distribution parameters of a group of key information hot spot information when each group of key information hot spot information is extracted.

(5) And when the current hotspot influence parameters and the current compatible distribution parameters meet set conditions, continuously extracting the key information hotspot information according to the sorting set of the shunting service objects.

(6) Judging whether the current hotspot influence parameter and the current compatible distribution parameter meet set conditions, deleting the current set of key information hotspot information and returning to traverse when the current hotspot influence parameter and the current compatible distribution parameter do not meet the set conditions, and extracting the key information hotspot information of the distribution service objects of the next sequencing sequence corresponding to the current set of key information hotspot information until the extraction of the key information hotspot information of all the distribution service objects in the distribution service object sequencing set is completed.

When judging whether the current hotspot influence parameter and the current compatible distribution parameter meet the set conditions, determining a first subscription frequency of the current hotspot influence parameter and a second subscription frequency of the current compatible distribution parameter according to the distribution coverage service of the shunting service object sorting set, and then comparing the first subscription frequency with the second subscription frequency.

For example, when the first subscription frequency is greater than the second subscription frequency, it is determined whether the current hotspot influence parameter exceeds a first preset value. And when the current hotspot influence parameter does not exceed the first preset value, judging whether the current compatible distribution parameter is lower than a second preset value, and when the current compatible distribution parameter is lower than the second preset value, judging that the current hotspot influence parameter and the current compatible distribution parameter meet the set conditions. And when the current compatible distribution parameter is larger than or equal to a second preset value, judging that the current hotspot influence parameter and the current compatible distribution parameter do not meet the set condition. And when the current hotspot influence parameter exceeds a first preset value, judging that the current hotspot influence parameter and the current compatible distribution parameter do not meet the set condition. The first preset value and the second preset value are determined according to a first mapping value of a difference value of the first subscription frequency and the second subscription frequency in the first preset mapping list.

For another example, when the first subscription frequency is less than or equal to the second subscription frequency, it is determined whether the current hotspot influence parameter exceeds a third preset value. And when the current hotspot influence parameter does not exceed the third preset value, judging whether the current compatible distribution parameter is lower than a fourth preset value, and when the current compatible distribution parameter is lower than the fourth preset value, judging that the current hotspot influence parameter and the current compatible distribution parameter meet set conditions. And when the current compatible distribution parameter is greater than or equal to the fourth preset value, judging that the current hotspot influence parameter and the current compatible distribution parameter do not meet the set condition. And when the current hotspot influence parameter exceeds a third preset value, judging that the current hotspot influence parameter and the current compatible distribution parameter do not meet the set condition. The third preset value and the fourth preset value are determined according to second mapping values of the first subscription frequency and the second subscription frequency in a second preset mapping list respectively, and the first preset mapping list and the second preset mapping list are complementary lists.

In a possible implementation manner, for step S130, the inventor researches and discovers that if subsequent processing is performed only based on the existing service subscription operation content in the service subscription operation information, under the condition that the noise is large, that is, the error service subscription operation content is more, the error service subscription operation content cannot be accurately checked, and further cannot be corrected, so that after the processing of the above technical scheme, the accuracy of the service subscription operation information is still low.

Based on this, step S130 may be further realized by the following exemplary sub-steps, which are described in detail below.

And a substep S131, acquiring a plurality of subscription tag coverage objects corresponding to the service subscription tag group based on any service subscription tag group in the service subscription operation information.

In this embodiment, the service subscription operation information includes a plurality of service subscription operation targets and a service relationship between the service subscription operation targets, the service subscription tag group includes any service subscription operation target pair of the plurality of service subscription operation targets and a service relationship between the service subscription operation targets in the service subscription operation target pair, and the subscription tag overlay object includes the service subscription operation target pair.

And a substep S132, performing relationship prediction based on the plurality of subscription label coverage objects, to obtain probabilities that relationships between service subscription operation targets expressed by the plurality of subscription label coverage objects respectively belong to the plurality of relationship labels, where the plurality of relationship labels include relationship labels of service relationships.

In the substep S133, the probability that the relationship between the service subscription operation targets expressed by the plurality of subscription label overlay objects belongs to the relationship label of the service relationship is determined as the relationship parameter corresponding to the plurality of subscription label overlay objects.

And a substep S134, determining a confidence level of the service subscription tag group based on the relationship parameter, where the confidence level is used to indicate a credibility of the service relationship included in the service subscription tag group.

And a substep S135, determining the business subscription label group with the confidence coefficient meeting the target processing condition as the target business subscription label group.

Based on the above design, for any service subscription tag group in the service subscription operation information, obtaining a plurality of subscription tag covering objects including a service subscription operation target pair in the service subscription tag group, using the plurality of subscription tag covering objects as a reference corpus for judging the credibility of the service subscription tag group, enriching the sources of the reference subscription tag covering objects for judging the credibility of the service subscription tag group, further obtaining the probability that the relation expressed by the plurality of subscription tag covering objects is the service relation through relation prediction, judging the credibility of the service subscription tag group, reducing the interference of wrong service subscription operation content on the credibility judgment of the service subscription tag group, improving the accuracy of judging the credibility of the service subscription tag group, and further processing the service subscription operation information based on the credibility of the service subscription tag group, the accuracy of the service subscription operation information can be improved.

In a possible implementation manner, for substep S131, a service subscription operation target pair included in the service subscription tag group may be used as an index target to index, so as to obtain a plurality of initial subscription tag coverage objects corresponding to the service subscription tag group. And then, extracting the service subscription operation targets of the plurality of initial subscription label covered objects to obtain the service subscription operation target in each initial subscription label covered object.

Therefore, the initial subscription label covered object meeting the first target condition can be determined as the subscription label covered object, and the first target condition is that the extracted service subscription operation objects have service subscription operation objects which are respectively the same as the two service subscription operation objects in the service subscription operation object pair.

It should be noted that the service subscription tag group further includes a service subscription operation target type of the service subscription operation target in the service subscription operation target pair, and the subscription tag overlay object further satisfies a second target condition, where the second target condition is that the extracted service subscription operation target type corresponding to the service subscription operation target is the same as the service subscription operation target type corresponding to the service subscription operation target included in the service subscription tag group.

In a possible implementation manner, still for sub-step S131, a similar service subscription operation target corresponding to the service subscription operation target may be obtained based on any service subscription operation target in the service subscription operation target pair. And the relation between the similar service subscription operation target and the other service subscription operation target in the service subscription operation target pair is equal to the service relation.

In this way, the service subscription operation target can be replaced by the corresponding similar service subscription operation target to obtain the extended service subscription tag group corresponding to the service subscription tag group, so that the subscription tag coverage object corresponding to the extended service subscription tag group is determined as the subscription tag coverage object, and the subscription tag coverage object corresponding to the extended service subscription tag group includes the service subscription operation target pair in the extended service subscription tag group.

Further, for example, in a possible implementation manner, in the process of performing relationship prediction based on the plurality of subscription label overlay objects to obtain probabilities that relationships between service subscription operation targets expressed by the plurality of subscription label overlay objects belong to the plurality of relationship labels, each subscription label overlay object may be input into a first relationship prediction network to obtain probabilities that relationships between service subscription operation targets expressed by each subscription label overlay object belong to the plurality of relationship labels, and the first relationship prediction network is configured to classify relationships of pairs of service subscription operation targets in the subscription label overlay objects.

In the process of determining the probability that the relationship between the service subscription operation targets expressed by the plurality of subscription label overlay objects belongs to the relationship label of the service relationship as the relationship parameter corresponding to the plurality of subscription label overlay objects, the probability that the relationship between the service subscription operation targets expressed by each subscription label overlay object belongs to the relationship label of the service relationship may be determined as the first relationship parameter corresponding to the plurality of subscription label overlay objects.

For another example, in a possible implementation manner, in the process of performing relationship prediction based on the plurality of subscription label overlay objects to obtain probabilities that relationships between service subscription operation targets expressed by the plurality of subscription label overlay objects belong to the plurality of relationship labels, a data set composed of the plurality of subscription label overlay objects may be input to a second relationship prediction network to obtain probabilities that the relationships expressed by the data set belong to the plurality of relationship labels, respectively, and the second relationship prediction network is configured to classify the relationships expressed by the data set, where the relationships expressed by the data set are relationships of the service subscription operation target pairs.

In addition, in the process of determining the probability that the relationship between the service subscription operation targets expressed by the plurality of subscription label overlay objects belongs to the relationship label of the service relationship as the relationship parameter corresponding to the plurality of subscription label overlay objects, the probability that the relationship expressed by the data set belongs to the relationship label of the service relationship may be determined as the second relationship parameter corresponding to the plurality of subscription label overlay objects.

Further, for example, in one possible implementation manner, for step S110, in the process of acquiring the pre-generated hotspot information association map including the target hotspot information, the following exemplary sub-steps may be implemented.

And step S101, classifying the service big data record information according to the information distribution rule and the distributed cloud computing task to obtain classified service big data record information, and performing keyword clustering on the classified service big data record information to obtain keyword clustering information of the service big data record information.

Step S102, carrying out hotspot information tracking processing on the keyword clustering information of the service big data record information to obtain a target hotspot information set corresponding to the service big data record information, and carrying out feature tag tracking processing on the keyword clustering information of the service big data record information to obtain a hotspot information feature tag set corresponding to the service big data record information.

And step S103, according to the hot spot information feature tag set, performing fusion processing on the classified service big data record information and the target hot spot information set to obtain a hot spot information association map comprising target hot spot information.

Step S104, generating and distributing corresponding information hotspot information to a plurality of digital financial terminals 200 according to the hotspot information association map comprising the target hotspot information.

Based on the design, in the embodiment, the hot spot information tracking is performed on the keyword clustering information of the service big data record information to obtain the target hot spot information set corresponding to the service big data record information, so that the target hot spot information can be adaptive to the service big data record information, that is, the target hot spot information fits the service big data record information better, and further, according to the hot spot information feature tag set, the classified service big data record information and the target hot spot information set are fused to obtain the hot spot information association map including the target hot spot information, so that the generated hot spot information association map better conforms to the actual hot spot distribution condition, and corresponding information hot spot information distributed to a plurality of digital financial terminals is generated, and the matching degree of information distribution is improved.

In a possible implementation manner, in the process of analyzing the hotspot information, a hotspot information analysis script for hotspot information analysis may be configured in advance, and specifically, the hotspot information analysis script may include a keyword clustering program and a tracking program.

Based on this, for example, in step S101, in the process of performing keyword clustering on the classified service big data record information to obtain keyword clustering information of the service big data record information, the keyword clustering program may perform keyword-based clustering on the classified service big data record information to obtain keyword clustering information of the service big data record information.

Further, for example, in step S102, in the process of performing hot spot information tracking processing on the keyword cluster information of the service big data record information to obtain the target hot spot information set corresponding to the service big data record information, the tracking program may perform hot spot information tag-based tracking processing on the keyword cluster information of the service big data record information to obtain the target hot spot information set corresponding to the service big data record information. And in the process of tracking the characteristic tag of the keyword cluster information of the service big data record information to obtain the hotspot information characteristic tag set corresponding to the service big data record information, tracking the keyword cluster information of the service big data record information based on the characteristic tag space through a tracking program to obtain the hotspot information characteristic tag set corresponding to the service big data record information.

Further, for example, in a possible implementation manner, for step S103, in order to accurately fuse the hot title feature and the hot content feature to improve the matching degree and the experience degree of the subsequent information distribution, the following exemplary sub-steps may be implemented, which are described in detail below.

And step S1031, for each hot spot information feature tag in the hot spot information feature tag set, fusing the tag feature value of the corresponding hot spot information feature tag in the classified service big data record information with the tag feature value of the hot spot information feature tag in the hot spot information feature tag set to obtain a first tag feature value of the hot spot information feature tag.

And a substep S1032 of weighting the tag characteristic values of the hot spot information characteristic tags in the hot spot information characteristic tag set, and fusing the weighted processing result with the tag characteristic values of the corresponding hot spot information characteristic tags in the target hot spot information set to obtain a second tag characteristic value of the hot spot information characteristic tags.

And a substep S1033, performing weighting processing on the first tag characteristic value and the second tag characteristic value to obtain the characteristic of the hotspot information characteristic tag.

And a substep S1034, according to the characteristics of the hot spot information characteristic tag, matching corresponding hot spot title characteristics from the classified service big data record information and matching corresponding hot spot content characteristics from the target hot spot information set.

And in the substep S1035, performing fusion processing on the matched hot spot title characteristics and hot spot content characteristics to obtain a hot spot map node.

And the substep S1036 is to splice all the hot spot map nodes according to the hot spot service relationship to obtain a hot spot information association map comprising target hot spot information.

Fig. 3 is a schematic diagram of functional modules of an information push device 300 based on cloud computing and big data according to an embodiment of the present disclosure, in this embodiment, the information push device 300 based on cloud computing and big data may be divided into the functional modules according to the method embodiment executed by the information push server 100 based on cloud computing and big data, that is, the following functional modules corresponding to the information push device 300 based on cloud computing and big data may be used to execute the method embodiments executed by the information push server 100 based on cloud computing and big data. The cloud computing and big data based information pushing apparatus 300 may include a generating module 310, an obtaining module 320, an adjusting module 330, and an updating module 340, and the functions of the functional modules of the cloud computing and big data based information pushing apparatus 300 are described in detail below.

The generating module 310 is configured to acquire a pre-generated hotspot information association map including target hotspot information, and generate, according to the hotspot information association map including the target hotspot information, information hotspot information distributed to the plurality of digital financial terminals correspondingly, where the pre-generated hotspot information association map including the target hotspot information is obtained by processing based on pre-collected service big data record information. The generating module 310 may be configured to execute the step S110, and the detailed implementation of the generating module 310 may refer to the detailed description of the step S110.

The obtaining module 320 is configured to obtain service subscription operation information fed back by the plurality of digital financial terminals according to the information hotspot information. The obtaining module 320 may be configured to perform the step S120, and the detailed implementation of the obtaining module 320 may refer to the detailed description of the step S120.

The adjusting module 330 is configured to determine, according to the service subscription operation information, a target service subscription tag group corresponding to the information hotspot information, and adjust a distribution policy for the information hotspot information according to the target service subscription tag group. The adjusting module 330 may be configured to perform the step S130, and the detailed implementation of the adjusting module 330 may refer to the detailed description of the step S130.

And the updating module 340 is configured to update the target information hotspot information distributed to the plurality of digital financial terminals according to the adjusted distribution policy of the information hotspot information. The updating module 340 may be configured to perform the step S140, and the detailed implementation of the updating module 340 may refer to the detailed description of the step S140.

It should be noted that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical service subscription operation target, or may be physically separated. And these modules may all be implemented in software invoked by a processing element. Or may be implemented entirely in hardware. And part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the generating module 310 may be a processing element separately set up, or may be implemented by being integrated into a chip of the apparatus, or may be stored in a memory of the apparatus in the form of program code, and the processing element of the apparatus calls and executes the functions of the generating module 310. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.

For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when some of the above modules are implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor that can call program code. As another example, these modules may be integrated together, implemented in the form of a system-on-a-chip (SOC).

Fig. 4 shows a hardware structure diagram of the cloud computing and big data based information push server 100 for implementing the control device, according to an embodiment of the present disclosure, as shown in fig. 4, the cloud computing and big data based information push server 100 may include a processor 110, a machine-readable storage medium 120, a bus 130, and a transceiver 140.

In a specific implementation process, at least one processor 110 executes computer-executable instructions stored in the machine-readable storage medium 120 (for example, the generation module 310, the acquisition module 320, the adjustment module 330, and the update module 340 included in the cloud computing and big data based information pushing apparatus 300 shown in fig. 3), so that the processor 110 may execute the cloud computing and big data based information pushing method according to the above method embodiment, where the processor 110, the machine-readable storage medium 120, and the transceiver 140 are connected through the bus 130, and the processor 110 may be configured to control transceiving actions of the transceiver 140, so as to transceive data with the aforementioned digital financial terminal 200.

For a specific implementation process of the processor 110, reference may be made to the above-mentioned method embodiments executed by the information push server 100 based on cloud computing and big data, which have similar implementation principles and technical effects, and details of this embodiment are not described herein again.

In the embodiment shown in FIG. 4, it should be understood that the Processor may be a global rule superposition matching process (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.

The machine-readable storage medium 120 may comprise high-speed RAM memory and may also include non-volatile storage NVM, such as at least one disk memory.

The bus 130 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus 130 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.

In addition, an embodiment of the present application further provides a readable storage medium, where the readable storage medium stores computer-executable instructions, and when a processor executes the computer-executable instructions, the verification processing method based on the blockchain offline payment is implemented as above.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be regarded as illustrative only and not as limiting the present specification. Various modifications, improvements and adaptations to the present description may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present specification and thus fall within the spirit and scope of the exemplary embodiments of the present specification.

Also, the description uses specific words to describe embodiments of the description. Such as "one possible implementation," "one possible example," and/or "exemplary" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the specification is included. Therefore, it is emphasized and should be appreciated that two or more references to "one possible implementation," "one possible example," and/or "exemplary" in various places throughout this specification are not necessarily referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the specification may be combined as appropriate.

Moreover, those skilled in the art will appreciate that aspects of the present description may be illustrated and described in terms of several patentable species or contexts, including any new and useful combination of processes, machines, manufacture, or materials, or any new and useful improvement thereof. Accordingly, aspects of this description may be performed entirely by hardware, entirely by software (including firmware, resident software, micro-code, etc.), or by a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the present description may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media.

The computer storage medium may comprise a propagated data signal with the computer program code embodied therewith, for example, on baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, etc., or any suitable combination. A computer storage medium may be any computer-readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer storage medium may be propagated over any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or any combination of the preceding.

Computer program code required for the operation of various portions of this specification may be written in any one or more programming languages, including an object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C + +, C #, VB.NET, Python, and the like, a conventional programming language such as C, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, a dynamic programming language such as Python, Ruby, and Groovy, or other programming languages. The program code may run entirely on the user's computer, or as a stand-alone software package on the user's computer, partly on the user's computer and partly on a remote computer or entirely on the remote computer or digital financial services terminal. In the latter scenario, the remote computer may be connected to the user's computer through any network format, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or in a cloud computing environment, or as a service, such as a software as a service (SaaS).

Additionally, the order in which the elements and lists are processed, the use of alphanumeric characters, or other designations in this specification is not intended to limit the order in which the processes and methods of this specification are performed, unless otherwise specified in the claims. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented through interactive services, they may also be implemented through software-only solutions, such as installing the described system on an existing digital financial services terminal or mobile device.

Similarly, it should be noted that in the preceding description of embodiments of the present specification, 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 one or more of the embodiments. This method of disclosure, however, is not intended to imply that more features than are expressly recited in a claim. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

It is to be understood that the descriptions, definitions and/or uses of terms in the accompanying materials of this specification shall control if they are inconsistent or contrary to the descriptions and/or uses of terms in this specification.

Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present disclosure. Other variations are also possible within the scope of the present description. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the present description are not limited to only those embodiments explicitly described and depicted herein.

Claims

1. An information push method based on cloud computing and big data is applied to an information push server based on cloud computing and big data, and the information push server based on cloud computing and big data is in communication connection with a plurality of digital financial terminals, and the method comprises the following steps:

updating target information hotspot information distributed to the plurality of digital financial terminals according to the adjusted distribution strategy of the information hotspot information;

the step of generating and distributing corresponding information hotspot information to the plurality of digital financial terminals according to the hotspot information association map comprising the target hotspot information comprises the following steps:

2. The information push method based on cloud computing and big data according to claim 1, wherein the step of extracting the hotspot tag feature vector of the hotspot graph node unit in parallel while obtaining the original information hotspot service list associated with the hotspot graph node unit during pushing from the graph data source of the hotspot graph node unit comprises:

3. The information pushing method based on cloud computing and big data according to claim 1, wherein the step of determining screening rule information for screening the original information hotspot service list based on the extracted hotspot tag feature vectors, and extracting rule matching parameters of a plurality of screening rule nodes to be used and service association information between different screening rule nodes from the screening rule information comprises:

4. The information pushing method based on cloud computing and big data according to claim 1, wherein the step of obtaining the information hotspot service list to be pushed by filtering the original information hotspot service list through the target filtering rule element comprises:

5. The information pushing method based on cloud computing and big data according to claim 1, wherein the step of determining the hotspot tag compatible distribution of the information hotspot service list to be pushed according to a target hotspot tag feature vector determined from a preset subscription hotspot record, and determining the hotspot tag extended distribution of the information hotspot service list to be pushed according to the determined service tags in the information hotspot service list to be pushed comprises:

6. The information pushing method based on cloud computing and big data according to any one of claims 1 to 5, wherein the step of determining a target service subscription tag group corresponding to the information hotspot information according to the service subscription operation information includes:

7. The information pushing method based on cloud computing and big data according to claim 6, wherein the obtaining of the plurality of subscription tag coverage objects corresponding to any service subscription tag group based on the service subscription tag group in the service subscription operation information includes:

8. The information pushing method based on cloud computing and big data according to claim 6, wherein the step of obtaining a plurality of subscription tag coverage objects corresponding to the service subscription tag group based on any service subscription tag group in the service subscription operation information includes:

9. An information push server based on cloud computing and big data, characterized in that the information push server based on cloud computing and big data comprises a processor, a machine-readable storage medium, and a network interface, the machine-readable storage medium, the network interface and the processor are connected through a bus system, the network interface is used for being in communication connection with at least one digital financial terminal, the machine-readable storage medium is used for storing programs, instructions or codes, and the processor is used for executing the programs, instructions or codes in the machine-readable storage medium to execute the information push method based on cloud computing and big data according to any one of claims 1 to 8.