CN113472640A - Intelligent gateway information processing method and system - Google Patents

Intelligent gateway information processing method and system Download PDF

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CN113472640A
CN113472640A CN202111027818.9A CN202111027818A CN113472640A CN 113472640 A CN113472640 A CN 113472640A CN 202111027818 A CN202111027818 A CN 202111027818A CN 113472640 A CN113472640 A CN 113472640A
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service information
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point data
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CN113472640B (en
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陈志雄
王杰盛
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Guangzhou Vensi Intelligent Technology Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/66—Arrangements for connecting between networks having differing types of switching systems, e.g. gateways
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    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
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    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2216/00—Indexing scheme relating to additional aspects of information retrieval not explicitly covered by G06F16/00 and subgroups
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Abstract

The application relates to the technical field of intelligent gateways, in particular to an intelligent gateway information processing method and system. The method comprises the steps of obtaining a pre-collected sample gateway service information set, carrying out interest point data mining on the sample gateway service information set to obtain a classification mining result and a data source mining result of interest point data corresponding to the sample gateway service information set, obtaining a plurality of gateway service information sets to be processed from an intelligent gateway to be analyzed based on the sample gateway service information set, the classification mining result of the interest point data and the data source mining result, and finally carrying out interest point data mining on the gateway service information sets to be processed to obtain interest point mining data sets associated with the gateway service information sets to be processed. Therefore, the classification of the point of interest data and the data source of the point of interest data are considered, and the mining effect of the point of interest data of the gateway service information set to be processed is improved.

Description

Intelligent gateway information processing method and system
Technical Field
The application relates to the technical field of intelligent gateways, in particular to an intelligent gateway information processing method and system.
Background
The intelligent gateways may include home-level intelligent gateways and enterprise-level intelligent gateways. Taking a home-level intelligent home gateway as an example, the home-level intelligent home gateway has functions of an intelligent home control hub, wireless routing and the like, and can perform data interaction with products such as an intelligent interactive terminal and the like in a wireless mode. Various devices such as mobile phones, PADs, notebook computers and the like can easily control the smart home at home through the smart home gateway to form a smart home system. The intelligent home system is a comprehensive management system of one of core services of power fiber to the home. The user can install 'intelligent home housekeeper' software through a mobile phone and a computer, log in the operation center for management, remotely control electrical equipment in a home, and improve the safety and the temporary performance of home power utilization. Meanwhile, the related community services, telemedicine, video movies and the like of the periphery can be viewed through the software. The intelligent home is characterized in that a home is used as a platform, facilities related to home life are integrated by utilizing a comprehensive wiring technology, a network communication technology, an intelligent home-system design scheme safety precaution technology, an automatic control technology and an audio and video technology, an efficient management system of home facilities and family schedule affairs is constructed, home safety, convenience, comfort and artistry are improved, and environment-friendly and energy-saving living environment is realized. The data processing and analysis (such as point of interest data analysis) of gateway data such as user behavior data and device operation state data, which are generated by an intelligent gateway in the existing intelligent home system, is beneficial to performing intelligent control or program upgrading optimization on each device in the system.
However, the inventor researches and discovers that in the process of performing information processing and mining on gateway service information of an intelligent gateway, the considered data dimension is single, so that the accuracy of the analyzed data of interest points needs to be improved.
Disclosure of Invention
In order to overcome at least the above disadvantages in the prior art, the present application is directed to provide an intelligent gateway information processing method, including:
acquiring a pre-collected sample gateway service information set, wherein the gateway service information set comprises point of interest data to be processed;
performing interest point data mining on the sample gateway service information set to obtain a classified mining result and a data source mining result of interest point data corresponding to the sample gateway service information set, wherein the classified mining result of the interest point data comprises data classified information associated with each service information in the sample gateway service information set, and the data source mining result of the interest point data comprises a data source of the interest point data associated with each service information in the sample gateway service information set;
acquiring a plurality of gateway service information sets to be processed from an intelligent gateway to be analyzed based on the sample gateway service information sets, the classification mining results of the interest point data and the data source mining results;
and performing interest point data mining on the plurality of gateway service information sets to be processed to obtain interest point mining data sets associated with the plurality of gateway service information sets to be processed, so as to perform service information interest point analysis on the intelligent gateway.
Based on the above purpose, the acquiring multiple gateway service information sets to be processed from an intelligent gateway based on the sample gateway service information set, the classification mining result of the point of interest data, and the data source mining result includes:
based on the classification mining result of the interest point data, determining the interest characteristics of a plurality of target interest point data from the sample gateway service information set, wherein data classification information corresponding to service information in the interest characteristics of any target interest point data is used for identifying the same interest point data classification;
determining an interest point data acquisition mode associated with the interest features of the target interest point data based on the data source mining result of the interest point data, wherein the interest point data acquisition mode corresponding to the interest features of any target interest point data is determined based on the data source of the interest point data corresponding to the service information in the interest features of the any target interest point data;
and acquiring a plurality of gateway service information sets to be processed based on the interest characteristics of the target interest point data and the interest point data acquisition mode associated with the interest characteristics of the target interest point data.
Based on the above purpose, the acquiring a plurality of gateway service information sets to be processed based on the interest features of the target interest point data and the interest point data acquisition modes associated with the interest features of the target interest point data includes:
determining an acquisition mode associated with the interest features of the target interest point data based on the acquisition mode of the interest point data associated with the interest features of the target interest point data;
sampling gateway service information sets of the interest characteristics of the target interest point data in the sample gateway service information sets to obtain sampling gateway service information sets associated with the interest characteristics of the target interest point data;
for the interest feature of any target interest point data in the interest features of the target interest point data, acquiring information of a sampling gateway service information set corresponding to the interest feature of the target interest point data according to an acquisition mode corresponding to the interest feature of the target interest point data to obtain a gateway service information set to be processed corresponding to the interest feature of the target interest point data;
or determining an acquisition mode associated with the interest features of the target interest point data based on the acquisition mode associated with the interest features of the target interest point data;
and acquiring information of the sample gateway service information set according to the acquisition mode associated with the interest features of the target interest point data, and acquiring the gateway service information sets to be processed associated with the interest features of the target interest point data based on a service information acquisition sequence obtained by information acquisition processing.
Based on the above purpose, the acquiring the to-be-processed gateway service information set associated with the interest features of the target interest point data based on the service information acquisition sequence obtained by information acquisition processing by performing information acquisition processing on the sample gateway service information set according to the acquisition mode associated with the interest features of the target interest point data includes:
dividing the interest features of the target interest point data according to the acquisition modes associated with the interest features of the target interest point data to obtain an interest feature queue of the target interest point data, wherein the acquisition modes corresponding to the interest features of the target interest point data in the interest feature queue of any interest point data are the same;
performing information acquisition on the sample gateway service information set according to an acquisition mode corresponding to an interest feature queue of first interest point data in the interest feature queues of the plurality of interest point data to obtain a first service information acquisition sequence, and performing gateway service information set sampling on interest features of target interest point data in the interest feature queue of the first interest point data in the first service information acquisition sequence to obtain a gateway service information set to be processed corresponding to the interest features of the target interest point data in the interest feature queue of the first interest point data;
performing information acquisition on a preamble service information acquisition sequence according to an acquisition mode corresponding to an interest feature queue of subsequent interest point data in the interest feature queues of the interest point data to obtain a subsequent service information acquisition sequence, and performing gateway service information set sampling on the interest features of target interest point data in the interest feature queues of the subsequent interest point data in the subsequent service information acquisition sequence to obtain a gateway service information set to be processed corresponding to the interest features of the target interest point data in the interest feature queues of the subsequent interest point data until obtaining a gateway service information set to be processed associated with the interest features of the target interest point data; and acquiring the first interest point data according to the corresponding acquisition mode of the interest feature queue of the first interest point data, wherein the acquisition mode of the first interest point data corresponding to the interest feature of the target interest point data in the interest feature queue of the first interest point data is the acquisition mode of the first interest point data corresponding to the interest feature of the target interest point data.
Based on the above purpose, the acquiring a plurality of gateway service information sets to be processed based on the interest features of the target interest point data and the interest point data acquisition modes associated with the interest features of the target interest point data includes:
respectively carrying out noise filtration on the interest characteristics of the target interest point data to obtain the interest characteristics of the target interest point data after the noise filtration;
and acquiring a plurality of gateway service information sets to be processed based on the interest characteristics of the plurality of target interest point data after the noise filtration and the interest point data acquisition mode associated with the interest characteristics of the plurality of target interest point data after the noise filtration.
Based on the above purpose, after obtaining a plurality of sets of gateway service information to be processed, the method further includes:
sequencing the plurality of gateway service information sets to be processed to obtain a plurality of sequenced gateway service information sets to be processed;
the performing the interest point data mining on the plurality of gateway service information sets to be processed to obtain the interest point mining data sets associated with the plurality of gateway service information sets to be processed includes:
performing interest point data mining on the sorted gateway service information sets to be processed to obtain interest point mining data sets associated with the sorted gateway service information sets to be processed;
before the obtaining of the plurality of gateway service information sets to be processed based on the sample gateway service information sets, the classification mining results of the point of interest data, and the data source mining results, the method further includes:
obtaining an information decomposition result corresponding to the sample gateway service information set;
determining the service information generation frequency of the intelligent gateway in the sample gateway service information set based on the information decomposition result;
the obtaining a plurality of gateway service information sets to be processed based on the sample gateway service information sets, the classification mining results of the point of interest data and the data source mining results comprises:
when the service information generation frequency reaches a first preset frequency threshold and the classification mining result of the interest point data indicates that the sample gateway service information set comprises the interest characteristics of the interest point data, acquiring a plurality of gateway service information sets to be processed based on the sample gateway service information set, the classification mining result of the interest point data and a data source mining result;
when the generation frequency of the service information is smaller than a second preset frequency threshold, stopping the point-of-interest data mining, wherein the second preset frequency threshold is smaller than the first preset frequency threshold;
when the service information generation frequency does not reach a first preset frequency threshold value, the classification mining result of the interest point data indicates that the sample gateway service information set comprises interest features of the interest point data, and the service information generation frequency exceeds a second preset frequency threshold value, performing gateway service information set sampling on the corresponding position of the intelligent gateway in the sample gateway service information set based on the information decomposition result;
and acquiring a plurality of gateway service information sets to be processed based on the gateway service information sets obtained by sampling.
Based on the above purpose, the mining of the point of interest data of the sample gateway service information set to obtain the classification mining result and the data source mining result of the point of interest data corresponding to the sample gateway service information set includes:
performing interest point data mining on the sample gateway service information set through an interest point data mining model to obtain a classification mining result and a data source mining result of the interest point data corresponding to the sample gateway service information set;
the performing the interest point data mining on the plurality of gateway service information sets to be processed to obtain the interest point mining data sets associated with the plurality of gateway service information sets to be processed includes:
and performing interest point data mining on the plurality of gateway service information sets to be processed through an interest point data mining model to obtain interest point mining data sets associated with the plurality of gateway service information sets to be processed.
Based on the above purpose, the method further includes a model training method for mining the model of the point of interest data, where the model training method includes:
obtaining a model training sample, wherein the model training sample comprises a gateway service information sample set, a reference classification result, a reference information decomposition result, a classification mining result of reference interest point data and a data source mining result of the reference interest point data, which correspond to the gateway service information sample set;
performing interest point data mining on the gateway service information sample set through a preset interest point data mining model to obtain a prediction classification result, a prediction information decomposition result, a prediction interest point data classification mining result and a prediction interest point data source mining result;
acquiring a first model evaluation index aiming at the prediction classification result and the reference classification result, acquiring a second model evaluation index based on the prediction information decomposition result and the reference information decomposition result, acquiring a third model evaluation index based on the classification mining result of the prediction interest point data and the classification mining result of the reference interest point data, and acquiring a fourth model evaluation index based on the data source mining result of the prediction interest point data and the data source mining result of the reference interest point data;
calculating a final model evaluation index based on the first model evaluation index, the second model evaluation index, the third model evaluation index and the fourth model evaluation index;
and (4) performing loop iteration on preset model parameters of the interest point data mining model by using the final model evaluation index until the model converges to obtain the trained interest point data mining model.
Based on the above object, the obtaining a first model evaluation index for the prediction classification result and the reference classification result, obtaining a second model evaluation index based on the prediction information decomposition result and the reference information decomposition result, obtaining a third model evaluation index based on the classification mining result of the prediction interest point data and the classification mining result of the reference interest point data, and obtaining a fourth model evaluation index based on the data source mining result of the prediction interest point data and the data source mining result of the reference interest point data includes:
calculating a relative entropy model evaluation index between the prediction classification result and the reference classification result, and taking the calculated relative entropy model evaluation index as a first model evaluation index;
calculating a relative entropy model evaluation index and a cross entropy model evaluation index between the predicted information decomposition result and the reference information decomposition result, and using the calculated relative entropy model evaluation index and the cross entropy model evaluation index as a second model evaluation index;
calculating a relative entropy model evaluation index between a classification mining result of the predicted interest point data and a classification mining result of the reference interest point data, and taking the calculated relative entropy model evaluation index as a third model evaluation index;
and calculating a relative entropy model evaluation index between the classification mining result of the predicted interest point data and the data source mining result of the reference interest point data, and taking the calculated relative entropy model evaluation index as a fourth model evaluation index.
Another object of the present application is to provide an intelligent gateway information processing system, which includes a processor, a machine-readable storage medium for storing computer instructions, and a processor for executing the computer instructions in the machine-readable storage medium to implement the method described above.
The technical scheme provided by the embodiment of the application at least has the following beneficial effects:
in the embodiment of the application, in the process of acquiring the gateway service information set to be processed, the intelligent gateway information processing method and the intelligent gateway information processing system provided by the embodiment of the application not only consider the classification of the point of interest data, but also consider the data source of the point of interest data, the considered information is comprehensive, the point of interest data mining effect of the gateway service information set to be processed is favorably improved, and after the point of interest data mining processing is performed on the gateway service information set to be processed acquired in the manner, the point of interest mining data set with higher accuracy can be acquired.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be 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 from the drawings without inventive effort.
Fig. 1 is a schematic view of an application scenario of an intelligent gateway information processing method provided in an embodiment of the present application.
Fig. 2 is a schematic flowchart of an intelligent gateway information processing method provided in an embodiment of the present application.
Fig. 3 is a block diagram illustrating a structure of a system for implementing the foregoing intelligent gateway information processing method 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. In the description of the present application, "at least one" includes one or more unless otherwise specified. "plurality" means two or more.
Referring to fig. 1, an embodiment of the present application provides an intelligent gateway information processing method, and fig. 1 is a schematic diagram illustrating an application scenario of the intelligent gateway information processing method provided in the embodiment of the present application. The application scenario may comprise a gateway controller 100 and a data processing server 200 communicatively connected to said gateway controller 100.
The gateway controller 100 can obtain a gateway service information set of the intelligent gateway to be analyzed, and then perform interest point data mining on the gateway service information set of the intelligent gateway to be analyzed to obtain interest point data in the intelligent gateway to be analyzed. Certainly, the gateway controller 100 may also send the gateway service information set of the intelligent gateway to be analyzed to the data processing server 200, and the data processing server 200 performs point-of-interest data mining on the gateway service information set of the intelligent gateway to be analyzed to obtain point-of-interest data in the intelligent gateway to be analyzed. In a possible implementation manner, after obtaining the interest point data in the intelligent gateway to be analyzed, the data processing server 200 may further send the interest point data in the intelligent gateway to be analyzed to the gateway controller 100, so that the gateway controller 100 performs adaptive control on the intelligent gateway according to the interest point data of the intelligent gateway to be analyzed, for example, if the intelligent gateway to be analyzed is an intelligent gateway to be optimized and upgraded, the gateway controller 100 may optimize and configure the interest point data such as the automatic standby time, the data acquisition frequency, and the like of the intelligent gateway to be optimized and upgraded into a corresponding gateway configuration list, thereby improving the intelligent degree of the intelligent gateway and improving user experience. The data of interest point mentioned in this embodiment may be a specific type or some specific types of data that needs to be analyzed and predetermined before the analysis and processing of the intelligent gateway information, and the data attribute or data feature of the corresponding data may be referred to as an interest feature.
In an alternative embodiment, the gateway controller 100 may be a control device located at the control layer and used to control each intelligent gateway that is subordinate to the gateway controller 100, which is a collection of various logic function entities that provide integrated service functions. The data processing server 200 may be a server, a server cluster composed of a plurality of servers, or a cloud computing service center. Gateway controller 100 establishes a communication connection with data processing server 200 via a wired or wireless network. Gateway controller 100 may have multiple intelligent gateways 300 hanging down.
Based on the application scenario shown in fig. 1, an embodiment of the present application provides an intelligent gateway information processing method, in this embodiment, the intelligent gateway information processing method may be implemented by the gateway controller 100, or may be implemented by the server 200, and with the application of the method to the gateway controller 100 as an example, the method may include the following steps shown in fig. 2.
Step S1, obtaining a pre-collected sample gateway service information set, where the intelligent gateway to be analyzed includes the point-of-interest data to be processed.
The gateway service information set of the intelligent gateway to be analyzed may be a gateway service information set including the intelligent gateway to be analyzed, and the intelligent gateway to be analyzed includes the point of interest data to be processed. The type of the intelligent gateway to be analyzed is not limited in the embodiment of the application, for example, the intelligent gateway to be analyzed may be an intelligent gateway which needs to perform point of interest data mining at present to perform gateway function optimization. It should be understood that the gateway service information set of the intelligent gateway to be analyzed may include global gateway service information collected by the intelligent gateway to be analyzed, or may include only local gateway service information of the intelligent gateway to be analyzed, which is not limited specifically. In an alternative embodiment, the manner of obtaining the sample gateway service information set of the intelligent gateway to be analyzed includes, but is not limited to, receiving a sample gateway service information set of the intelligent gateway to be analyzed issued by the server 200, where the sample gateway service information set may be a sample gateway service information set formed by performing sample analysis on a large amount of historically acquired gateway service information by the server 200, so as to be used as reference sample information in the following situations of intelligent gateway information processing or gateway service optimization, and in other embodiments, the sample gateway service information set of the intelligent gateway to be analyzed may also be obtained in other manners, and then the sample gateway service information set of the intelligent gateway to be analyzed is processed to analyze the data of interest in the intelligent gateway to be analyzed.
It should be understood that the triggering time for obtaining the sample gateway service information set of the intelligent gateway to be analyzed is related to the type and actual situation of the intelligent gateway to be analyzed, and is not limited in particular.
Step S2, the sample gateway service information set is mined with the interest point data to obtain the classified mining result and the data source mining result of the interest point data corresponding to the sample gateway service information set, the classified mining result of the interest point data includes the data classified information associated with each service information in the sample gateway service information set, and the data source mining result of the interest point data includes the data source of the interest point data associated with each service information in the sample gateway service information set.
After a sample gateway service information set of an intelligent gateway to be analyzed is obtained, point-of-interest data mining is carried out on the sample gateway service information set so as to mine information related to the point-of-interest data in the sample gateway service information set and provide information reference for subsequently obtaining the gateway service information set to be processed. Information related to the point of interest data includes, but is not limited to, classification mining results and data source mining results of the point of interest data.
And the classification mining result of the point of interest data comprises data classification information associated with each service information in the sample gateway service information set. And the data classification information corresponding to one service information is used for indicating the point of interest data classification corresponding to the service information. The form of the data classification information corresponding to one service information is not limited in the embodiment of the application, for example, the data classification information corresponding to one service information includes a category label of the point-of-interest data classification corresponding to the one service information; or, the data classification information corresponding to one service information includes the possibility that the one service information corresponds to each reference point-of-interest data classification. And obtaining the point-of-interest data classification corresponding to one service message according to the data classification information corresponding to the service message. It should be understood that the point of interest data corresponding to one service information is classified into one of the reference point of interest data classifications.
The reference interest point data classification may be an interest point data classification which is configured in advance and may correspond to the to-be-processed interest point data, and the reference interest point data classification is configured according to historical data or dynamically optimized according to an application scenario and the type of the to-be-analyzed intelligent gateway, and is not particularly limited. For example, the reference interest point data category includes device local parameter configuration, service data corresponding to a selected service, user behavior data, and the like, and may also include other categories, such as other interest point data types except for several specific set interest point data types.
The data source mining result of the point of interest data comprises data sources of the point of interest data associated with each service information in the sample gateway service information set. The data source of the point of interest data corresponding to one service information is used to indicate the data source of the point of interest data corresponding to the one service information, for example, the data source may be a spatio-temporal data source of the point of interest data, including a generation time of the point of interest, a generation geographic location information, a corresponding physical device information, and the like. The form of the data source of the point of interest data corresponding to the service information is not limited in the embodiment of the application, for example, the data source of the point of interest data corresponding to one service information includes the source identification information of the data source of the point of interest data corresponding to the one service information; or, the data source of the point of interest data corresponding to one service information includes the possibility that the service information corresponds to the data source of each reference point of interest data. The data source of the point of interest data corresponding to the service information can be obtained according to the data source of the point of interest data corresponding to the service information. It should be understood that the data source of the point of interest data corresponding to one service information is at least one of the data sources of the preset reference point of interest data.
The data source of the reference point-of-interest data may be configured according to historical data or dynamically optimized according to an application scenario, and is not limited in particular. For example, a data source of the point of interest data corresponding to one service information may be a data source of a specific point of interest data, and may also be a data source of non-point of interest data. In general, the corresponding point of interest data is classified into a data source of point of interest data corresponding to the service information acquired by a specific information acquisition, and a data source of point of interest data corresponding to the service information classified as non-point of interest data is a data source of non-point of interest data.
In a possible implementation manner, the classification mining result and the data source mining result of the point of interest data corresponding to the sample gateway service information set may be described by means of a data result or a knowledge graph.
It should be understood that the point of interest data to be processed in the intelligent gateway to be analyzed may be discrete point of interest data, and each local continuous point of interest data to be processed is referred to as a point of interest collected data to be processed. The collected data of different interest points may correspond to the same classification of the data of the interest points, or may correspond to different classifications of the data of the interest points, and the specific limitation is not carried out. For example, each of the collected data of interest points corresponds to a classification of the data of interest points.
It should be further noted that, although the position of the data collected by the interest point in the intelligent gateway to be analyzed may be known, since the data source of the corresponding service information of the intelligent gateway to be analyzed in the sample gateway service information set is not determined, the data mining of the interest point data needs to be performed on the sample gateway service information set to analyze the data classification information associated with each service information and the data source of the interest point data, so as to provide information reference for determining the interest feature of the interest point data in the sample gateway service information set and for subsequently efficiently processing the gateway service information set to be processed.
In an alternative embodiment, the process of performing point-of-interest data mining on the sample gateway service information set to obtain the classification mining result and the data source mining result of the point-of-interest data corresponding to the sample gateway service information set may be as follows:
and performing interest point data mining on the sample gateway service information set through the interest point data mining model to obtain a classification mining result and a data source mining result of the interest point data corresponding to the sample gateway service information set. The interest point data mining model can be a model obtained by pre-training and used for mining the interest point data of the sample gateway business information set of the intelligent gateway to be analyzed, so that the sample gateway business information set can be input into the interest point data mining model to obtain a classification mining result and a data source mining result of the interest point data output by the interest point data mining model.
In an alternative embodiment, in the process of performing the point-of-interest data mining on the sample gateway service information set through the point-of-interest data mining model, besides obtaining the classification mining result and the data source mining result of the point-of-interest data corresponding to the sample gateway service information set, a classification result and an information decomposition result corresponding to the sample gateway service information set may also be obtained.
And the classification result corresponding to the sample gateway service information set is used for indicating the specific classification of the intelligent gateway to be analyzed in the sample gateway service information set. The classification result can be represented by the degree of possibility that the intelligent gateway to be analyzed is matched with each reference specific classification, and the specific classification of the intelligent gateway to be analyzed can be known according to the possibility that the intelligent gateway to be analyzed is matched with each reference specific classification. The reference specific classification is configured according to historical data, and can be dynamically optimized according to application scenes.
And the information decomposition result corresponding to the sample gateway service information set is used for indicating the information decomposition classification associated with each service information in the sample gateway service information set. The information decomposition classification of one service information is any one of the reference information decomposition classifications. And the information decomposition classification corresponding to one service information is used for indicating whether the service information is matched with the intelligent gateway to be analyzed. And analyzing the corresponding position of the service information of the intelligent gateway to be analyzed in the sample gateway service information set and analyzing the generation frequency of the service information of the intelligent gateway to be analyzed in the sample gateway service information set according to the information decomposition result. It should be understood that whether to obtain the information decomposition result corresponding to the sample gateway service information set may be according to a service requirement, for example, when the service requirement indicates that it is necessary to obtain the service information generation frequency of the intelligent gateway to be analyzed in the sample gateway service information set, the information decomposition result corresponding to the sample gateway service information set is obtained.
The embodiment of the present application takes the example of obtaining the classification result, the information decomposition result, the classification mining result of the point of interest data, and the data source mining result corresponding to the sample gateway service information set after the point of interest data mining is performed on the sample gateway service information set through the point of interest data mining model as an example for explanation.
In an alternative embodiment, the method for performing the point-of-interest data mining on the sample gateway service information set through the point-of-interest data mining model to obtain the classification result, the information decomposition result, the classification mining result of the point-of-interest data, and the data source mining result corresponding to the sample gateway service information set may be as follows: performing feature calculation on the sample gateway service information set through the interest point data mining model to obtain classification features of the sample gateway service information set; based on the classification characteristics of the sample gateway service information set, acquiring information decomposition characteristics and prediction characteristics of the sample gateway service information set; classifying the classification characteristics through an interest point data mining model to obtain a classification result corresponding to the sample gateway service information set; performing information decomposition processing on the information decomposition characteristics through an interest point data mining model to obtain an information decomposition result corresponding to a sample gateway service information set; performing classified prediction processing on the predicted characteristics through an interest point data mining model to obtain a classified mining result of the interest point data corresponding to the sample gateway service information set; and performing data source prediction processing on the interest point data on the prediction characteristics through the interest point data mining model to obtain a data source mining result of the interest point data corresponding to the sample gateway service information set.
It should be understood that the above processes of feature calculation, category division, information decomposition processing, point of interest data classification prediction processing, data source prediction processing of the point of interest data, and the like may be respectively performed by different model units in the point of interest data mining model, and are not particularly limited.
In an alternative embodiment, the obtaining manner of the classification features of the sample gateway service information set is related to the structure of a model unit for implementing a feature calculation function in the point-of-interest data mining model, and is not limited specifically. For example, the logic process of performing feature calculation on the sample gateway service information set by the interest point data mining model to obtain the classification features of the sample gateway service information set is as follows: the method comprises the steps that an interest point data mining model carries out first convolution operation on a sample gateway service information set to obtain first gateway service information set characteristics; performing second convolution operation on the first gateway service information set characteristics to obtain second gateway service information set characteristics; performing a third convolution operation on the second gateway service information set characteristics to obtain third gateway service information set characteristics; performing a fourth convolution operation on the third gateway service information set characteristic to obtain a fourth gateway service information set characteristic; performing a fifth convolution operation on the fourth gateway service information set characteristic to obtain a fifth gateway service information set characteristic; and performing convolution operation on the fifth gateway service information set characteristic to obtain the classification characteristic of the sample gateway service information set.
In an alternative embodiment, based on the above process of obtaining the classification features, based on the classification features of the sample gateway service information set, the manner of obtaining the information decomposition features and the prediction features of the sample gateway service information set may be: performing feature fusion analysis on the classification features and the fifth gateway service information set features to obtain sixth gateway service information set features; performing first deconvolution operation on the sixth gateway service information set characteristic, and performing characteristic fusion analysis on the gateway service information set characteristic after the first deconvolution operation and the fourth gateway service information set characteristic to obtain a seventh gateway service information set characteristic; performing second deconvolution operation on the seventh gateway service information set characteristic, and performing characteristic fusion analysis on the gateway service information set characteristic after the second deconvolution operation and the third gateway service information set characteristic to obtain an eighth gateway service information set characteristic; performing a third deconvolution operation on the eighth gateway service information set characteristic, and performing characteristic fusion analysis on the gateway service information set characteristic and the second gateway service information set characteristic after the third deconvolution operation to obtain an information decomposition characteristic; and performing fourth deconvolution operation on the information decomposition characteristics, and performing characteristic fusion analysis on the gateway service information set characteristics and the first gateway service information set characteristics after the fourth deconvolution operation to obtain prediction characteristics. The dimension of the gateway service information set can be amplified through the deconvolution operation, and the specific implementation process of the deconvolution operation is not limited in the embodiment of the present application.
According to the corresponding process, in the process of carrying out the interest point data mining on the sample gateway service information set through the interest point data mining model, the process of carrying out convolution operation and then deconvolution operation is involved. In possible embodiments, the point-of-interest data mining model may be a neural network structure with compressibility or a reduced version, and is not limited in particular.
According to the corresponding flow, the interest point data mining model is used for executing the following mining processes:
A. and a classification process, wherein the classification process can analyze the specific classification of the intelligent gateway to be analyzed in the sample gateway service information set.
B. And a data source mining process, wherein the data source mining process can mine the data source of the interest point data corresponding to each service information, and then vote to determine the data source of the interest point data corresponding to the interest characteristics of the interest point data according to the data source of the interest point data corresponding to each service information.
C. And an interest point data attribute mining process, wherein the interest point data attribute mining process can obtain a classification mining result of the interest point data so as to judge whether each service information is matched with the interest point collected data and which interest point collected data.
D. And an information decomposition process, wherein the information decomposition process is used for decomposing the intelligent gateway to be analyzed in the sample gateway service information set. On the premise that the frequency of generating the service information in the sample gateway service information set by the intelligent gateway to be analyzed is too low, the classification process is likely to misjudge that the sample gateway service information set does not include the interest point acquisition data, and therefore, the information decomposition process is added. On the premise that the frequency of the service information of the intelligent gateway to be analyzed in the sample gateway service information set is too low, the gateway service information set of the corresponding position of the intelligent gateway to be analyzed can be sampled in the sample gateway service information set and then mined again, so that the data reliability of the mining of the point of interest data is improved.
It should be understood that, the above description has been given only by taking the example of obtaining the classification result, the information decomposition result, the classification mining result of the interest point data and the data source mining result by performing the interest point data mining on the sample gateway service information set through the interest point data mining model, and in a possible implementation, only the classification mining result of the interest point data and the data source mining result may be obtained through the interest point data mining model; or only obtaining information decomposition results, classification mining results of the interest point data and data source mining results; or only obtaining the classification result, the classification mining result of the interest point data and the data source mining result. Under the above condition, the task processing mode of the point-of-interest data mining model can be adjusted. For example, on the premise that only the classification mining result and the data source mining result of the point of interest data are obtained through the point of interest data mining model, classification of the classification features and information decomposition processing of the information decomposition features may not be performed.
On the premise of not executing classification division on the classification features and information decomposition processing on the information decomposition features, the method for mining the interest point data of the sample gateway service information set through the interest point data mining model to obtain the classification mining result and the data source mining result of the interest point data can be as follows:
firstly, performing feature calculation on a sample gateway service information set through an interest point data mining model to obtain classification features of the sample gateway service information set;
then, based on the classification characteristics of the sample gateway service information set, acquiring the information decomposition characteristics and the prediction characteristics of the sample gateway service information set;
finally, performing classified prediction processing on the predicted features through an interest point data mining model to obtain a classified mining result of the interest point data corresponding to the sample gateway service information set; and performing data source prediction processing on the interest point data on the prediction characteristics through the interest point data mining model to obtain a data source mining result of the interest point data corresponding to the sample gateway service information set.
It should be appreciated that the point of interest data mining model may be model trained prior to performing point of interest data mining on the sample gateway business information set via the point of interest data mining model. In an alternative embodiment, taking the premise that the classification result, the information decomposition result, the classification mining result of the interest point data, and the data source mining result can be obtained by the interest point data mining model, the interest point data mining model training method may include the following steps.
(1) And obtaining model training samples, wherein the model training samples comprise a gateway service information sample set, a reference classification result corresponding to the gateway service information sample set, a reference information decomposition result, a classification mining result of reference interest point data and a data source mining result of the reference interest point data.
(2) And performing interest point data mining on the gateway service information sample set through a preset interest point data mining model to obtain a prediction classification result, a prediction information decomposition result, a prediction interest point data classification mining result and a prediction interest point data source mining result.
(3) Acquiring a first model evaluation index aiming at the prediction classification result and the reference classification result, acquiring a second model evaluation index based on the prediction information decomposition result and the reference information decomposition result, acquiring a third model evaluation index based on the classification mining result of the prediction interest point data and the classification mining result of the reference interest point data, and acquiring a fourth model evaluation index based on the data source mining result of the prediction interest point data and the data source mining result of the reference interest point data;
(4) calculating a final model evaluation index based on the first model evaluation index, the second model evaluation index, the third model evaluation index and the fourth model evaluation index;
(5) and (4) performing loop iteration on preset model parameters of the interest point data mining model by using the final model evaluation index until the model converges to obtain the trained interest point data mining model.
It should be understood that the gateway service information sample set in the model training sample is a gateway service information set which can be acquired under the same application environment as the point-of-interest data mining performed on the sample gateway service information set of the intelligent gateway to be analyzed, so as to improve the point-of-interest data mining effect on the sample gateway service information set.
In a possible implementation manner, the embodiment of the present application is not limited to a specific manner of obtaining the model evaluation index based on the prediction result of the model and the reference result in the model training sample. For example, obtaining the first model evaluation index based on the prediction classification result and the reference classification result may calculate a relative entropy model evaluation index between the prediction classification result and the reference classification result, and use the calculated relative entropy model evaluation index as the first model evaluation index. For example, obtaining the second model evaluation index based on the decomposition result of the prediction information and the decomposition result of the reference information may calculate a relative entropy model evaluation index and a cross entropy model evaluation index between the decomposition result of the prediction information and the decomposition result of the reference information, respectively, and use the calculated relative entropy model evaluation index and cross entropy model evaluation index together as the second model evaluation index.
For example, the third model evaluation index obtained based on the classification mining result of the predicted interest point data and the classification mining result of the reference interest point data may be obtained by calculating a relative entropy model evaluation index between the classification mining result of the predicted interest point data and the classification mining result of the reference interest point data, and using the calculated relative entropy model evaluation index as the third model evaluation index. For example, obtaining the fourth model evaluation index based on the data source mining result of the predicted interest point data and the data source mining result of the reference interest point data may calculate a relative entropy model evaluation index between the classification mining result of the predicted interest point data and the data source mining result of the reference interest point data, and use the calculated relative entropy model evaluation index as the fourth model evaluation index.
It should be understood that the above describes a process of training to obtain the interest point data mining model on the premise that the classification result, the information decomposition result, the classification mining result of the interest point data, and the data source mining result can be obtained by the interest point data mining model. On the premise that only a classification mining result and a data source mining result of the point of interest data are required to be obtained through the point of interest data mining model; or, on the premise that only the classification result, the classification mining result of the interest point data and the data source mining result need to be obtained through the interest point data mining model; or, on the premise that the interest point data mining model only needs to obtain the information decomposition result, the classification mining result of the interest point data and the data source mining result, the process of training the interest point data mining model can be similar to the corresponding process.
For example, on the premise that only the classification mining result and the data source mining result of the interest point data are required to be obtained through the interest point data mining model, only the third model evaluation index and the fourth model evaluation index in the corresponding processes are required to be obtained in the process of obtaining the interest point data mining model through training, and then the model parameters of the interest point data mining model are iterated circularly through the final model evaluation index calculated based on the third model evaluation index and the fourth model evaluation index.
In an alternative embodiment, the implementation process of performing point-of-interest data mining on the sample gateway service information set to obtain the classification mining result and the data source mining result of the point-of-interest data corresponding to the sample gateway service information set includes: and when the interest characteristic identification of the intelligent gateway to be analyzed is not obtained based on the sample gateway service information set, performing interest point data mining on the sample gateway service information set to obtain a classification mining result and a data source mining result of the interest point data corresponding to the sample gateway service information set. That is to say, in a possible implementation manner, the step 2 is executed again only on the premise that the interest feature identifier of the intelligent gateway to be analyzed is not obtained based on the sample gateway service information set, so as to improve the efficiency of the interest point data mining.
The interest feature identifier of the intelligent gateway to be analyzed is associated with the service type of the intelligent gateway to be analyzed, for example, for the intelligent gateway to be analyzed of the user behavior data monitoring type, the service type of the intelligent gateway to be analyzed is a behavior monitoring type gateway, and in this case, the interest feature identifier of the intelligent gateway to be analyzed refers to a function identifier of the intelligent gateway to be analyzed. When the interest feature identifier of the intelligent gateway to be analyzed is not obtained based on the sample gateway service information set, step S2 may be entered to provide information reference for subsequent good point of interest data mining.
In a possible implementation manner, when the interest feature identifier of the intelligent gateway to be analyzed is obtained based on the sample gateway service information set, noise filtering may be directly performed on an area corresponding to the interest feature identifier of the intelligent gateway to be analyzed, so as to optimize the service information of the intelligent gateway to be analyzed in the sample gateway service information set, and then the interest feature of the point-of-interest data is directly mined from the optimized sample gateway service information set of the intelligent gateway to be analyzed and the point-of-interest data is mined.
And step S3, acquiring a plurality of gateway service information sets to be processed based on the sample gateway service information sets, the classified mining results of the interest point data and the data source mining results.
After the classification mining result and the data source mining result of the point of interest data corresponding to the sample gateway service information set are obtained, a plurality of gateway service information sets to be processed can be obtained based on the sample gateway service information set, the classification mining result and the data source mining result of the point of interest data. The gateway service information set to be processed refers to a gateway service information set of a subsequent interest point data sequence to be analyzed. The set of gateway service information to be processed may be a plurality of data sets, and is not limited specifically.
In an alternative embodiment, the process of obtaining a plurality of to-be-processed gateway service information sets based on the sample gateway service information sets, the classification mining results of the point of interest data, and the data source mining results includes the following steps S31 to S33, which are exemplarily described as follows.
Step S31, based on the classification mining result of the interest point data, the interest characteristics of a plurality of target interest point data are determined from the sample gateway service information set, and the data classification information corresponding to the service information in the interest characteristics of any target interest point data is used for identifying the same interest point data classification.
The classification mining result of the point of interest data may include data classification information associated with each business information in the sample gateway business information set. And indicating the point of interest data classification associated with each service information according to the data classification information associated with each service information. In an alternative embodiment, the process of determining the interest characteristics of a plurality of target point of interest data from the sample gateway service information sets based on the classification mining results of the point of interest data includes the following steps S311 and S312.
Step S311, based on the classification mining result of the interest point data, the interest characteristics of a plurality of initial interest point data are determined from the sample gateway service information set, and the data classification information corresponding to the service information in the interest characteristics of any initial interest point data is used for identifying the same interest point data classification.
The interest features of the plurality of initial interest point data refer to the interest features of all the interest point data which can be determined according to the classification mining result of the interest point data. In an alternative embodiment, based on the classification mining result of the point of interest data, the interest features of a plurality of initial point of interest data determined from the sample gateway service information set may be traversed by service information in the sample gateway service information set, and the interest features corresponding to the service information having the same classification and service association relationship with the point of interest collected data indicated by the corresponding data classification information are used as the interest features of the arbitrary initial point of interest data. It should be understood that the data classification indicated by the data classification information corresponding to the service information in the interest feature of different initial interest point data may be the same or different, and is not limited specifically.
In an alternative embodiment, after the interest features of a plurality of initial interest point data are determined, the interest point data classification indicated by the data classification information corresponding to the service information in the interest feature of each initial interest point data is used as the interest point data classification corresponding to the interest feature of the initial interest point data, so that the interest point data classification associated with the interest features of the plurality of initial interest point data can be obtained.
In step S312, the interest features of the target interest point data are determined among the interest features of the initial interest point data.
The interest feature of the target interest point data refers to the interest feature of the interest point data needing to be analyzed. In an alternative embodiment, the manner of determining the interest features of the multiple target point of interest data in the interest features of the multiple initial point of interest data may be to use all the interest features of the multiple initial point of interest data as the interest features of the target point of interest data, or to filter the interest features of the multiple initial point of interest data and use the interest features of the filtered remaining point of interest data as the interest features of the target point of interest data. The manner of filtering the interest features of the multiple initial interest point data may be configured according to historical data, or may be dynamically optimized according to business requirements or application scenarios, and is not particularly limited.
In a possible implementation manner, filtering the interest features of the plurality of initial interest point data, and taking the interest features of the interest point data left after filtering as the interest features of the target interest point data may specifically be that the interest features of the initial interest point data at a position corresponding to the service information of the intelligent gateway to be analyzed in the interest features of the plurality of initial interest point data are taken as the interest features of the first interest point data; classifying the corresponding interest point data in the interest features of the first interest point data into the interest features of the first interest point data classified by reference as the interest features of the second interest point data; and filtering the non-relevant positions of the interest features of the second interest point data, and taking the interest features of the rest interest point data as the interest features of the target interest point data. The corresponding position can be obtained based on the information decomposition result corresponding to the sample gateway service information set, and as the point of interest data in the intelligent gateway to be analyzed needs to be analyzed, the interest feature of the initial point of interest data in the corresponding position of the service information of the intelligent gateway to be analyzed is only needed to be used as the interest feature of the first point of interest data, and the interest feature of the initial point of interest data outside the corresponding position of the service information of the intelligent gateway to be analyzed is filtered.
Step S32, based on the data source mining result of the interest point data, determining the interest point data collection mode associated with the interest features of the multiple target interest point data, wherein the interest point data collection mode corresponding to the interest features of any target interest point data is determined based on the data source of the interest point data corresponding to the service information in the interest features of any target interest point data.
The data source mining result of the point of interest data comprises data sources of the point of interest data associated with each service information in the sample gateway service information set, and the data sources of the point of interest data associated with each service information are used for indicating the data sources of the point of interest data associated with each service information. In an alternative embodiment, based on the data source mining result of the point of interest data, the point of interest data associated with the interest features of the plurality of target point of interest data is determined in a manner that: for the interest feature of any target interest point data in the interest features of the target interest point data, determining the data source of the interest point data associated with each service information in the interest feature of the target interest point data based on the data source mining result of the interest point data; and determining an interest point data acquisition mode corresponding to the interest feature of the any target interest point data based on the data source of the interest point data associated with each service information in the interest feature of the any target interest point data.
In an alternative embodiment, based on the data source of the interest point data associated with each service information in the interest feature of any target interest point data, the manner of determining the interest point data acquisition manner corresponding to the interest feature of the any target interest point data is as follows: and counting the quantity of the service information associated with the data source of each interest point data based on the data source of the interest point data associated with each service information in the interest features of any target interest point data, and taking the data source of the interest point data with the maximum corresponding service information quantity as the collection mode of the interest point data corresponding to the interest features of the any target interest point data. The point-of-interest data acquisition mode determined based on the method can be regarded as a point-of-interest data acquisition mode determined according to the number of data sources of the point-of-interest data corresponding to the service information.
Based on the above manner, the point-of-interest data acquisition manner associated with the interest feature of each target point-of-interest data can be obtained. It should be understood that the acquisition modes of the interest point data corresponding to the interest features of different target interest point data may be the same or different, and are not limited specifically. In a possible implementation manner, if it is determined that the interest features of each target interest point data in the intelligent gateway to be analyzed all correspond to the same interest point data acquisition manner, the result is mined based on the data source of the interest point data. The manner of acquiring the interest point data associated with the interest features of the target interest point data may be: determining data sources of the interest point data associated with all service information in the interest features of the target interest point data based on the data source mining result of the interest point data; and counting the quantity of the service information associated with the data source of each point of interest data based on the data sources of the point of interest data associated with all the service information, taking the data source of the point of interest data with the maximum corresponding quantity of the service information as a specified point of interest data acquisition mode, and taking the specified point of interest data acquisition mode as a unified corresponding point of interest data acquisition mode of the interest characteristics of a plurality of target point of interest data. In a possible implementation manner, the interest characteristics of each interest point data in the intelligent gateway to be analyzed may have the same interest point data collection manner.
Step S33: and acquiring a plurality of gateway service information sets to be processed based on the interest characteristics of the target interest point data and the interest point data acquisition mode associated with the interest characteristics of the target interest point data.
The gateway service information set to be processed may be a gateway service information set for which point of interest data mining processing has not been performed. In an alternative embodiment, the step of obtaining a plurality of to-be-processed gateway service information sets based on the interest features of the plurality of target interest point data and the interest point data acquisition manner associated with the interest features of the plurality of target interest point data may include the following steps S331 to S333.
Step S331, based on the interest point data collection modes associated with the interest features of the target interest point data, determining the collection modes associated with the interest features of the target interest point data.
The method comprises the steps that an interest point data acquisition mode corresponding to an interest feature of target interest point data is used for representing a data source of the interest point data where the target interest point acquisition data in the interest feature of the target interest point data is located at present, and an interest feature acquisition mode corresponding to the target interest feature of the target interest point data is used for representing a data acquisition mode corresponding to the target interest point acquisition data in the interest feature of the target interest point data.
Step S332: and sampling the gateway service information set for the interest characteristics of the target interest point data in the sample gateway service information set to obtain a sampled gateway service information set associated with the interest characteristics of the target interest point data.
The interest features of the target interest point data are in the sample gateway service information set, the gateway service information set sampling is carried out on the interest features of the target interest point data in the sample gateway service information set, and a sampling gateway service information set associated with the interest features of the target interest point data can be obtained. And the sampling gateway service information set corresponding to the interest characteristics of the target interest point data is a gateway service information set comprising the target interest point collected data.
Step S333: and for the interest characteristics of any target interest point data in the interest characteristics of the target interest point data, acquiring information of a sampling gateway service information set corresponding to the interest characteristics of the target interest point data according to an acquisition mode corresponding to the interest characteristics of the target interest point data to obtain a gateway service information set to be processed corresponding to the interest characteristics of the target interest point data.
Because the data source of the data collected by the target interest point in the sampling gateway service information set corresponding to the interest feature of the target interest point data may not be the positive data source and analysis errors may be caused by directly analyzing and processing the sampling gateway service information set corresponding to the interest feature of the target interest point data, the information collection is performed on the sampling gateway service information set corresponding to the interest feature of the target interest point data according to the collection mode corresponding to the interest feature of the target interest point data, so that the target interest point collected data in the gateway service information set after data collection is the interest point collected data of the previously determined data source, the gateway service information set after data collection is used as the gateway service information set to be processed corresponding to the interest feature of the target interest point data, and the data to be processed in the gateway service information set to be processed is the interest point data of the previously determined data source, the accuracy of the point of interest data mining is improved.
It should be understood that, in the process of obtaining the to-be-processed gateway service information sets corresponding to the interest features of each target interest point data based on step S333, data collection may be performed sequentially on the sampling gateway service information sets corresponding to the interest features of each target interest point data according to a corresponding collection manner, or data collection may be performed simultaneously on a group of sampling gateway service information sets corresponding to the interest features of the target interest point data corresponding to the same collection manner according to the same collection manner, which is not limited specifically.
In another possible implementation manner, the step of obtaining a plurality of to-be-processed gateway service information sets based on the interest features of the plurality of target interest point data and the interest point data acquisition manners associated with the interest features of the plurality of target interest point data includes the following steps S33a and S33 b.
Step S33a, based on the collection modes of the interest point data associated with the interest features of the target interest point data, determining the collection modes of the interest features of the target interest point data. The implementation of step S33a can refer to step S331, and is not described herein again.
Step S33 b: and acquiring data of the sample gateway service information set according to the acquisition mode associated with the interest features of the target interest point data, and acquiring the gateway service information sets to be processed associated with the interest features of the target interest point data based on the service information acquisition sequence obtained by data acquisition and processing.
It should be understood that the number of the service information collection sequences obtained by the data collection process may be one or more, and is related to the actual data collection process. A to-be-processed gateway service information set corresponding to the interest features of one or more target interest point data may be obtained based on one service information acquisition sequence, which is not particularly limited.
In an alternative embodiment, step S33b may include the following steps a-f.
Dividing the interest features of the target interest point data according to the collection mode associated with the interest features of the target interest point data to obtain an interest feature queue of the target interest point data, wherein the collection modes corresponding to the interest features of the target interest point data in the interest feature queue of any interest point data are the same.
And b, dividing the interest features of the target interest point data with the same corresponding acquisition mode into an interest feature queue of the same interest point data to obtain an interest feature queue of a plurality of interest point data. It should be understood that the number of the interest features of the target interest point data included in the interest feature queue of different interest point data may be the same or different, and is not limited specifically. In an alternative embodiment, after obtaining the interest feature queues of the multiple interest point data, the interest feature queues of the multiple interest point data are sorted, so that the interest feature queues of the interest point data are sequentially processed in the order of the sorting. It should be understood that, in the embodiment of the present application, a manner of sorting the interest feature queues of the multiple interest point data is not limited, for example, the interest features of the multiple interest point data may be sorted according to a random sorting manner, and the interest features of the multiple interest point data may also be sorted according to a different order of the acquisition manners corresponding to the interest features of the included target interest point data.
And c, performing information acquisition on the sample gateway service information set according to an acquisition mode corresponding to an interest feature queue of first interest point data in the interest feature queues of the plurality of interest point data to obtain a first service information acquisition sequence, and performing gateway service information set sampling on the interest features of the target interest point data in the interest feature queue of the first interest point data in the first service information acquisition sequence to obtain a gateway service information set to be processed corresponding to the interest features of the target interest point data in the interest feature queue of the first interest point data.
The acquisition mode corresponding to the interest feature queue of the first interest point data is the acquisition mode corresponding to the interest feature of the target interest point data in the interest feature queue of the first interest point data. It should be understood that the interest feature queue of the first point of interest data may refer to the first of the interest feature queues of any of the plurality of interest feature queues of interest data that has not been processed. After obtaining the interest feature queues of the multiple interest point data, the first interest feature queue of the interest point data refers to the interest feature queue arranged in the first interest point data on the premise that the interest feature queues of the multiple interest point data can be sorted.
In the process of acquiring the gateway service information set to be processed corresponding to the interest feature of the target interest point data in the interest feature queue of the first interest point data, information acquisition can be performed on the sample gateway service information set according to an acquisition mode corresponding to the interest feature of the first interest point data to obtain a first service information acquisition sequence. And in the obtained first service information acquisition sequence, the target interest point acquisition data in the interest features of the target interest point data in the interest feature queue of the first interest point data is the previously determined interest point acquisition data of the data source. And sampling gateway service information sets of the interest features of the target interest point data in the interest feature queue of the first interest point data in the first service information acquisition sequence to obtain a gateway service information set to be processed corresponding to the interest features of the target interest point data in the interest feature queue of the first interest point data. And the target interest point acquisition data in the gateway service information set to be processed is the previously determined interest point acquisition data of the data source. In the process, the interest characteristics of each target interest point data in the interest characteristic queue of the first interest point data can be obtained through the data acquisition primary sample gateway service information set, and the efficiency of obtaining the gateway service information set to be processed is improved.
And e, acquiring information of the preamble service information acquisition sequence according to an acquisition mode corresponding to an interest feature queue of subsequent interest point data in the interest feature queue of the interest point data to obtain a subsequent service information acquisition sequence, and sampling a gateway service information set of the interest feature of the target interest point data in the interest feature queue of the subsequent interest point data in the subsequent service information acquisition sequence to obtain a gateway service information set to be processed corresponding to the interest feature of the target interest point data in the interest feature queue of the subsequent interest point data.
The acquisition mode corresponding to the interest feature queue of the subsequent interest point data may be a mixed acquisition mode in which the acquisition mode corresponding to the interest feature of the target interest point data in the interest feature queue of the subsequent interest point data corresponds to the acquisition mode corresponding to the interest feature of the target interest point data in the interest feature queue of the preceding interest point data.
For example, assuming that the interest feature queue of the subsequent interest point data is the interest feature queue of the second interest point data, the interest feature queue of the subsequent interest point data is the interest feature queue of the first interest point data, the acquisition mode corresponding to the interest feature of the target interest point data in the interest feature queue of the first interest point data is first data acquisition, the acquisition mode corresponding to the interest feature of the target interest point data in the interest feature queue of the second interest point data is second acquisition mode, and the acquisition mode corresponding to the interest feature queue of the second target interest point data is a mixed acquisition mode including the first acquisition mode and the second acquisition mode, for example, one part of the target interest point data is acquired by using the first acquisition mode, and the other part of the target interest point data is acquired by using the second acquisition mode.
And in the obtained subsequent service information acquisition sequence, target interest point acquisition data in the interest features of the target interest point data in the interest feature queue of the subsequent interest point data is previously determined interest point acquisition data of a data source, so that gateway service information sets to be processed, which are sampled from the subsequent service information acquisition sequence, are gateway service information sets corresponding to the interest point data sequence.
And f, circularly executing the steps until a to-be-processed gateway service information set associated with the interest features of the target interest point data is obtained.
And when the interest feature queue comprises unprocessed interest point data, continuously acquiring a gateway service information set to be processed corresponding to the interest feature of the target interest point data in the interest feature queue of the new interest point data until obtaining the gateway service information sets to be processed associated with the plurality of target interest point data gateway service information sets. At the moment, the obtained gateway service information sets to be processed are all gateway service information sets of the interest point data sequence, and the accuracy of interest point data mining is improved.
It should be understood that, in the embodiment of the present application, the number of the interest feature queues of the interest point data is not limited, for example, assuming that the acquisition manners corresponding to the interest features of all the target interest point data are the same, the number of the interest feature queues of the interest point data at this time is one, and in this case, the to-be-processed gateway service information sets associated with the interest features of the target interest point data can be obtained directly based on the step a and the step b.
It should be understood that the above steps a to f are only one exemplary description for implementing the step S33 b. In a possible implementation manner, after the step a and the step b are executed, the first service information acquisition sequence can be restored to a state before data acquisition, so as to obtain a restored gateway service information set; then, performing information acquisition on the recovered gateway service information set according to an acquisition mode corresponding to the interest feature of the target interest point data in the interest feature queue of the subsequent interest point data to obtain a subsequent service information acquisition sequence, performing gateway service information set sampling on the interest feature of the target interest point data in the interest feature queue of the subsequent interest point data in the subsequent service information acquisition sequence to obtain a gateway service information set to be processed corresponding to the interest feature of the target interest point data in the interest feature queue of the subsequent interest point data, and recovering the subsequent service information acquisition sequence to a state before data acquisition to obtain a recovered gateway service information set; and repeating the steps until a to-be-processed gateway service information set associated with the interest features of the target interest point data is obtained.
In an alternative embodiment, the step of obtaining a plurality of to-be-processed gateway service information sets based on the interest features of the target interest point data and the interest point data acquisition mode associated with the interest features of the target interest point data may include:
respectively carrying out noise filtration on the interest characteristics of the target interest point data to obtain the interest characteristics of the target interest point data after the noise filtration;
and acquiring a plurality of gateway service information sets to be processed based on the interest characteristics of the plurality of target interest point data after the noise filtration and the interest point data acquisition mode associated with the interest characteristics of the plurality of target interest point data after the noise filtration. In a possible implementation manner, the acquisition manner of the interest point data associated with the interest features of the plurality of target interest point data after noise filtering is the same as the acquisition manner of the interest point data associated with the interest features of the plurality of target interest point data before noise filtering. That is to say, the method for acquiring the point-of-interest data associated with the interest features of the target point-of-interest data before noise filtering may be directly used as the method for acquiring the point-of-interest data associated with the interest features of the target point-of-interest data after noise filtering.
In a possible implementation manner, based on the interest features of the multiple target interest point data after noise filtering and the interest point data acquisition manner associated with the interest features of the multiple target interest point data after noise filtering, the implementation process of obtaining the multiple gateway service information sets to be processed may refer to steps S331 to S333 or step S33a and step S33b, and only needs to adjust the interest features of the target interest point data to the interest features of the target interest point data after noise filtering, and adjust the interest point data acquisition manner corresponding to the interest features of the target interest point data to the interest point data acquisition manner corresponding to the interest features of the target interest point data after noise filtering.
In an alternative embodiment, after obtaining a plurality of sets of gateway service information to be processed, the method further includes: and sequencing the plurality of to-be-processed gateway service information sets to obtain a plurality of sequenced to-be-processed gateway service information sets. The gateway service information sets to be processed are sequenced, so that the gateway service information sets to be processed, which form the same interest point data sequence, can be sequenced according to the sequence of the interest point data sequence. The method can quickly determine the point-of-interest data sequence which needs to be actually applied finally according to the analyzed point-of-interest data.
In an alternative embodiment, before obtaining a plurality of gateway service information sets to be processed based on the sample gateway service information set, the classification mining result of the point of interest data, and the data source mining result, it may be determined whether the current condition matches a first set condition, and when the current condition matches the first set condition, a plurality of gateway service information sets to be processed may be obtained based on the sample gateway service information set, the classification mining result of the point of interest data, and the data source mining result, so as to improve the obtaining effect of the gateway service information sets to be processed. That is, when the current situation matches the first setting situation, a plurality of gateway service information sets to be processed are obtained based on the sample gateway service information sets, the classification mining results of the point of interest data, and the data source mining results. The first setting condition may include that the service information generation frequency reaches a first preset frequency threshold and the classification mining result of the point of interest data indicates that the sample gateway service information set includes the interest feature of the point of interest data. The service information generation frequency refers to the service information generation frequency of the service information of the intelligent gateway to be analyzed in the sample gateway service information set. That is, before determining whether the current situation matches the first setting situation, the service information generation frequency needs to be determined.
In an alternative embodiment, the manner of determining the generation frequency of the service information may be: obtaining an information decomposition result corresponding to a sample gateway service information set; and determining the service information generation frequency of the intelligent gateway to be analyzed in the sample gateway service information set based on the information decomposition result. It should be understood that the manner of obtaining the information decomposition result corresponding to the sample gateway service information set may be obtained in the process of performing point-of-interest data mining on the sample gateway service information set through the point-of-interest data mining model in step S2, or may also be obtained by performing information decomposition processing on the sample gateway service information set through a separate information decomposition model, which is not limited in particular.
And the information decomposition result corresponding to the sample gateway service information set is used for indicating the information decomposition classification associated with each service information in the sample gateway service information set. And the information decomposition classification corresponding to any service information is used for indicating whether the any service information is matched with the intelligent gateway to be analyzed. The corresponding position of the intelligent gateway to be analyzed in the sample gateway service information set can be analyzed according to the information decomposition result, and then the service information generation frequency of the intelligent gateway to be analyzed in the sample gateway service information set is determined according to the corresponding position of the intelligent gateway to be analyzed in the sample gateway service information set.
The first preset frequency threshold is configured according to historical data or dynamically optimized according to application scenarios, for example, the first preset frequency threshold is f 1. When the generation frequency of the service information of the intelligent gateway to be analyzed in the sample gateway service information set reaches a first preset frequency threshold, it is indicated that the generation frequency of the service information of the intelligent gateway to be analyzed in the sample gateway service information set is relatively high. The classification mining result of the point of interest data indicates that the sample gateway service information set comprises the interest characteristics of the point of interest data, and the interest characteristics of the point of interest data can be calculated in the sample gateway service information set. In an alternative embodiment, the case where the sample gateway service information set does not include the interest feature of the point of interest data includes, but is not limited to: the classification mining result indication of the interest point data does not comprise any service information matched with the collected data of the interest point; or the classification mining result of the interest point data indicates that the quantity of the service information matched with each interest point data classification is less than a certain quantity. And when the condition that the interest characteristics of the point of interest data are not included in the sample gateway service information set is not satisfied, indicating that the classification mining result of the point of interest data indicates that the interest characteristics of the point of interest data are included in the sample gateway service information set.
When the generation frequency of the service information reaches a first preset frequency threshold and the classification mining result of the interest point data indicates that the sample gateway service information set comprises the interest characteristics of the interest point data, the gateway service information set to be processed with higher reliability can be obtained, at the moment, the first setting condition is judged to be matched, and therefore a plurality of gateway service information sets to be processed are obtained based on the sample gateway service information set, the classification mining result of the interest point data and the data source mining result.
In alternative embodiments, the following two cases are also included.
First, the current situation matches the second set situation. The second setting condition includes that the service information generation frequency is smaller than a second preset frequency threshold, and the second preset frequency threshold is smaller than the first preset frequency threshold. At this time, it is shown that the frequency of generating the service information in the sample gateway service information set by the intelligent gateway to be analyzed is low, and a reliable point of interest mining data set cannot be obtained based on the sample gateway service information set. At this point, point of interest data mining may be terminated directly. That is, when the current situation matches the second setting situation, the point-of-interest data mining is terminated. The second setting condition includes that the service information generation frequency is smaller than a second preset frequency threshold, the second preset frequency threshold is dynamically optimized according to historical data configuration or an application scene, and the second preset frequency threshold is not limited specifically, and only needs to be smaller than the first preset frequency threshold. For example, the second preset frequency threshold is f 2.
Second, the current situation does not match the second setting and does not match the first setting. The first setting condition includes that the service information generation frequency reaches a first preset frequency threshold and the classification mining result of the point of interest data indicates that the sample gateway service information set comprises the interest characteristics of the point of interest data, and the second setting condition includes that the service information generation frequency is smaller than a second preset frequency threshold (the second preset frequency threshold is smaller than the first preset frequency threshold), so that the current condition does not match the second setting condition and does not match the first setting condition and the current condition comprises the following types.
The type I is that the service information generation frequency is greater than a second preset frequency threshold, the service information generation frequency is less than a first preset frequency threshold, and the classification mining result of the interest point data indicates that the sample gateway service information set comprises the interest characteristics of the interest point data. And the type II, the service information generation frequency is greater than a second preset frequency threshold, the service information generation frequency is less than a first preset frequency threshold, and the classification mining result of the interest point data indicates that the sample gateway service information set does not include the interest characteristics of the interest point data. And thirdly, the generation frequency of the service information is greater than a first preset frequency threshold value, and the classification mining result of the interest point data indicates that the interest characteristics of the interest point data are not included in the sample gateway service information set. Under the three types, it is stated that the point-of-interest data mining cannot be directly terminated, and a to-be-processed gateway service information set with a good effect cannot be directly obtained. At this time, the gateway service information set sampling can be carried out on the corresponding position of the intelligent gateway to be analyzed in the sample gateway service information set based on the information decomposition result; and acquiring a plurality of gateway service information sets to be processed based on the gateway service information sets obtained by sampling. The frequency of generating the service information of the intelligent gateway to be analyzed in the sampled gateway service information set is high, so that the reliability of the gateway service information set to be processed, which is obtained based on the sampled gateway service information set, is high, and the accuracy of searching the point of interest data is improved.
The way of obtaining a plurality of gateway service information sets to be processed based on the sampled gateway service information sets is as follows:
performing interest point data mining on the sampled gateway service information set to obtain a classification mining result and a data source mining result of the interest point data corresponding to the sampled gateway service information set;
and acquiring a plurality of gateway service information sets to be processed based on the sampled gateway service information sets, the classified mining results of the point of interest data corresponding to the sampled gateway service information sets and the data source mining results, wherein the specific implementation manner can refer to step S2 and step S3, and details are not repeated here.
Illustratively, in the process of obtaining a gateway service information set to be processed according to a mining result obtained after interest point data mining after the interest point data mining is performed on a sample gateway service information set, the mining result obtained after interest point data mining is performed on the sample gateway service information set may include an information decomposition result, a classification mining result of the interest point data, and a data source mining result. And determining the generation frequency of the service information of the intelligent gateway to be analyzed in the sample gateway service information set according to the information decomposition result. And judging whether the current situation is matched with a second set situation by judging whether the service information generation frequency is smaller than a second preset frequency threshold value. And when the current situation is matched with the second set situation, directly terminating the point of interest data mining. When the current situation does not match the second setting situation, executing a process of calculating the interest characteristics of the interest point data, judging whether the current situation matches the first setting situation or not in the process of executing the interest characteristics of the interest point data, and if the current situation matches the first setting situation, acquiring a gateway service information set to be processed; and if the current situation does not match the first setting situation, performing excavation again.
Step S4, performing interest point data mining processing on the plurality of gateway service information sets to be processed to obtain interest point mining data sets associated with the plurality of gateway service information sets to be processed, so as to perform service information interest point analysis on the intelligent gateway.
The process of performing the point of interest data mining on the multiple gateway service information sets to be processed may refer to performing the point of interest data mining on each gateway service information set to be processed one by one, or may refer to performing the point of interest data mining on the batched gateway service information sets to be processed synchronously in batches, and is not limited specifically. The batch mode may be configured based on historical data or dynamically optimized based on application scenarios, for example.
In an alternative embodiment, the method of performing the point of interest data mining on the gateway service information sets of the multiple point of interest data point of interest mining data sets to obtain the point of interest mining data sets associated with the multiple to-be-processed gateway service information sets may be: and performing interest point data mining on the gateway service information sets of the multiple interest point data interest point mining data sets through the interest point data mining model to obtain the interest point mining data sets associated with the multiple to-be-processed gateway service information sets. The embodiment of the application has no limitation on the structure of the point of interest data mining model, and the point of interest data can be analyzed from the gateway service information to be processed in a centralized manner.
In an alternative embodiment, on the premise that after the plurality of gateway service information sets to be processed are obtained, the plurality of gateway service information sets to be processed are sorted to obtain a plurality of gateway service information sets to be processed after sorting, the step S4 may be implemented by performing point of interest data mining on the plurality of gateway service information sets to be processed after sorting to obtain a point of interest mining data set associated with the plurality of gateway service information sets to be processed after sorting. The interest point mining data set obtained in the mode is beneficial to quickly obtaining the interest point data sequence needing mining.
For example, in the process of interest point data mining, a sample gateway service information set of an intelligent gateway to be analyzed may be first obtained, then a plurality of gateway service information sets to be processed are obtained based on the sample gateway service information set of the intelligent gateway to be analyzed, and then the interest point data mining processing is performed on the plurality of gateway service information sets to be processed to obtain an interest point mining data set.
Fig. 3 is a schematic diagram of an intelligent gateway information processing system for implementing the intelligent gateway information processing method according to the embodiment of the present application. In this embodiment, the system may be the gateway controller 100 or the server 200 shown in fig. 1, and preferably, in this embodiment, the system is the server 200. In detail, in the present embodiment, the system may include a processor 10, a machine-readable storage medium 20, and a communication module 30. The communication module 30 is used for realizing communication between the system and external devices. The machine-readable storage medium 20 is used for storing computer instructions, and the processor 10 is used for executing the computer instructions in the machine-readable storage medium to realize the method.
In this embodiment, the processor 10, the machine-readable storage medium 20, and the communication module 30 may be communicatively connected to each other through a bus 40 for information interaction and data communication.
The intelligent gateway information processing method and the intelligent gateway information processing system provided by the embodiment of the application excavate the interest point data of the gateway service information set of the intelligent gateway to be analyzed, which is obtained from various data sources, and the excavation effect of the gateway service information set of the intelligent gateway to be analyzed is good, so that the interest point data excavation can be suitable for more complex scenes. In addition, in the embodiment of the application, in the process of acquiring the gateway service information set to be processed, not only the classification of the point of interest data but also the data source of the point of interest data are considered, the considered information is comprehensive, and the method is favorable for improving the mining effect of the point of interest data of the gateway service information set to be processed.
It will be apparent to those skilled in the art that various changes and modifications may be made in the embodiments of the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the embodiments of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to encompass such modifications and variations.

Claims (10)

1. An intelligent gateway information processing method is characterized by comprising the following steps:
acquiring a pre-collected sample gateway service information set, wherein the gateway service information set comprises point of interest data to be processed;
performing interest point data mining on the sample gateway service information set to obtain a classified mining result and a data source mining result of interest point data corresponding to the sample gateway service information set, wherein the classified mining result of the interest point data comprises data classified information associated with each service information in the sample gateway service information set, and the data source mining result of the interest point data comprises a data source of the interest point data associated with each service information in the sample gateway service information set;
acquiring a plurality of gateway service information sets to be processed from an intelligent gateway to be analyzed based on the sample gateway service information sets, the classification mining results of the interest point data and the data source mining results;
and performing interest point data mining on the plurality of gateway service information sets to be processed to obtain interest point mining data sets associated with the plurality of gateway service information sets to be processed, so as to perform service information interest point analysis on the intelligent gateway.
2. The method of claim 1, wherein obtaining a plurality of gateway service information sets to be processed from an intelligent gateway based on the sample gateway service information sets, the classification mining results of the point of interest data, and the data source mining results comprises:
based on the classification mining result of the interest point data, determining the interest characteristics of a plurality of target interest point data from the sample gateway service information set, wherein data classification information corresponding to service information in the interest characteristics of any target interest point data is used for identifying the same interest point data classification;
determining an interest point data acquisition mode associated with the interest features of the target interest point data based on the data source mining result of the interest point data, wherein the interest point data acquisition mode corresponding to the interest features of any target interest point data is determined based on the data source of the interest point data corresponding to the service information in the interest features of the any target interest point data;
and acquiring a plurality of gateway service information sets to be processed based on the interest characteristics of the target interest point data and the interest point data acquisition mode associated with the interest characteristics of the target interest point data.
3. The method of claim 2, wherein the obtaining a plurality of gateway service information sets to be processed based on the interest features of the target interest point data and the interest point data acquisition modes associated with the interest features of the target interest point data comprises:
determining an acquisition mode associated with the interest features of the target interest point data based on the acquisition mode of the interest point data associated with the interest features of the target interest point data;
sampling gateway service information sets of the interest characteristics of the target interest point data in the sample gateway service information sets to obtain sampling gateway service information sets associated with the interest characteristics of the target interest point data;
for the interest feature of any target interest point data in the interest features of the target interest point data, acquiring information of a sampling gateway service information set corresponding to the interest feature of the target interest point data according to an acquisition mode corresponding to the interest feature of the target interest point data to obtain a gateway service information set to be processed corresponding to the interest feature of the target interest point data;
or determining an acquisition mode associated with the interest features of the target interest point data based on the acquisition mode associated with the interest features of the target interest point data;
and performing data acquisition processing on the sample gateway service information set according to the acquisition mode associated with the interest features of the target interest point data, and acquiring the gateway service information sets to be processed associated with the interest features of the target interest point data based on a service information acquisition sequence obtained by the data acquisition processing.
4. The method as claimed in claim 3, wherein the acquiring the to-be-processed gateway service information set associated with the interest features of the target interest point data based on the service information acquisition sequence obtained by information acquisition processing by performing information acquisition processing on the sample gateway service information set according to the acquisition manner associated with the interest features of the target interest point data comprises:
dividing the interest features of the target interest point data according to the acquisition modes associated with the interest features of the target interest point data to obtain an interest feature queue of the target interest point data, wherein the acquisition modes corresponding to the interest features of the target interest point data in the interest feature queue of any interest point data are the same;
performing information acquisition on the sample gateway service information set according to an acquisition mode corresponding to an interest feature queue of first interest point data in the interest feature queues of the plurality of interest point data to obtain a first service information acquisition sequence, and performing gateway service information set sampling on interest features of target interest point data in the interest feature queue of the first interest point data in the first service information acquisition sequence to obtain a gateway service information set to be processed corresponding to the interest features of the target interest point data in the interest feature queue of the first interest point data;
and performing information acquisition on the preamble service information acquisition sequence according to an acquisition mode corresponding to an interest feature queue of subsequent interest point data in the interest feature queues of the plurality of interest point data to obtain a subsequent service information acquisition sequence, and performing gateway service information set sampling on the interest features of the target interest point data in the interest feature queue of the subsequent interest point data in the subsequent service information acquisition sequence to obtain a gateway service information set to be processed corresponding to the interest features of the target interest point data in the interest feature queue of the subsequent interest point data until obtaining a gateway service information set to be processed associated with the interest features of the plurality of target interest point data.
5. The method of claim 2, wherein the obtaining a plurality of gateway service information sets to be processed based on the interest features of the target interest point data and the interest point data acquisition modes associated with the interest features of the target interest point data comprises:
respectively carrying out noise filtration on the interest characteristics of the target interest point data to obtain the interest characteristics of the target interest point data after the noise filtration;
and acquiring a plurality of gateway service information sets to be processed based on the interest characteristics of the plurality of target interest point data after the noise filtration and the interest point data acquisition mode associated with the interest characteristics of the plurality of target interest point data after the noise filtration.
6. The method of claim 1, wherein after obtaining the plurality of sets of gateway traffic information to be processed, the method further comprises:
sequencing the plurality of gateway service information sets to be processed to obtain a plurality of sequenced gateway service information sets to be processed;
the performing the interest point data mining on the plurality of gateway service information sets to be processed to obtain the interest point mining data sets associated with the plurality of gateway service information sets to be processed includes:
performing interest point data mining on the sorted gateway service information sets to be processed to obtain interest point mining data sets associated with the sorted gateway service information sets to be processed;
before the obtaining of the plurality of gateway service information sets to be processed based on the sample gateway service information sets, the classification mining results of the point of interest data, and the data source mining results, the method further includes:
obtaining an information decomposition result corresponding to the sample gateway service information set;
determining the service information generation frequency of the intelligent gateway in the sample gateway service information set based on the information decomposition result;
the obtaining a plurality of gateway service information sets to be processed based on the sample gateway service information sets, the classification mining results of the point of interest data and the data source mining results comprises:
when the service information generation frequency reaches a first preset frequency threshold and the classification mining result of the interest point data indicates that the sample gateway service information set comprises the interest characteristics of the interest point data, acquiring a plurality of gateway service information sets to be processed based on the sample gateway service information set, the classification mining result of the interest point data and a data source mining result;
when the generation frequency of the service information is smaller than a second preset frequency threshold, stopping the point-of-interest data mining, wherein the second preset frequency threshold is smaller than the first preset frequency threshold;
when the service information generation frequency does not reach a first preset frequency threshold value, the classification mining result of the interest point data indicates that the sample gateway service information set comprises interest features of the interest point data, and the service information generation frequency exceeds a second preset frequency threshold value, performing gateway service information set sampling on the corresponding position of the intelligent gateway in the sample gateway service information set based on the information decomposition result;
and acquiring a plurality of gateway service information sets to be processed based on the gateway service information sets obtained by sampling.
7. The method according to any one of claims 1 to 6, wherein the performing point-of-interest data mining on the sample gateway service information set to obtain a classification mining result and a data source mining result of the point-of-interest data corresponding to the sample gateway service information set includes:
performing interest point data mining on the sample gateway service information set through an interest point data mining model to obtain a classification mining result and a data source mining result of the interest point data corresponding to the sample gateway service information set;
the performing the interest point data mining on the plurality of gateway service information sets to be processed to obtain the interest point mining data sets associated with the plurality of gateway service information sets to be processed includes:
and performing interest point data mining on the plurality of gateway service information sets to be processed through an interest point data mining model to obtain interest point mining data sets associated with the plurality of gateway service information sets to be processed.
8. The method of claim 7, further comprising a model training method for the point of interest data mining model, the model training method comprising:
obtaining a model training sample, wherein the model training sample comprises a gateway service information sample set, a reference classification result, a reference information decomposition result, a classification mining result of reference interest point data and a data source mining result of the reference interest point data, which correspond to the gateway service information sample set;
performing interest point data mining on the gateway service information sample set through a preset interest point data mining model to obtain a prediction classification result, a prediction information decomposition result, a prediction interest point data classification mining result and a prediction interest point data source mining result;
acquiring a first model evaluation index aiming at the prediction classification result and the reference classification result, acquiring a second model evaluation index based on the prediction information decomposition result and the reference information decomposition result, acquiring a third model evaluation index based on the classification mining result of the prediction interest point data and the classification mining result of the reference interest point data, and acquiring a fourth model evaluation index based on the data source mining result of the prediction interest point data and the data source mining result of the reference interest point data;
calculating a final model evaluation index based on the first model evaluation index, the second model evaluation index, the third model evaluation index and the fourth model evaluation index;
and (4) performing loop iteration on preset model parameters of the interest point data mining model by using the final model evaluation index until the model converges to obtain the trained interest point data mining model.
9. The method of claim 8, wherein obtaining a first model evaluation index for the predicted classification result and the reference classification result, obtaining a second model evaluation index based on the predicted information decomposition result and the reference information decomposition result, obtaining a third model evaluation index based on the classified mining result of the predicted point of interest data and the classified mining result of the reference point of interest data, and obtaining a fourth model evaluation index based on the data source mining result of the predicted point of interest data and the data source mining result of the reference point of interest data comprises:
calculating a relative entropy model evaluation index between the prediction classification result and the reference classification result, and taking the calculated relative entropy model evaluation index as a first model evaluation index;
calculating a relative entropy model evaluation index and a cross entropy model evaluation index between the predicted information decomposition result and the reference information decomposition result, and using the calculated relative entropy model evaluation index and the cross entropy model evaluation index as a second model evaluation index;
calculating a relative entropy model evaluation index between a classification mining result of the predicted interest point data and a classification mining result of the reference interest point data, and taking the calculated relative entropy model evaluation index as a third model evaluation index;
and calculating a relative entropy model evaluation index between the classification mining result of the predicted interest point data and the data source mining result of the reference interest point data, and taking the calculated relative entropy model evaluation index as a fourth model evaluation index.
10. An intelligent gateway information processing system, comprising a processor, a machine-readable storage medium for storing computer instructions, and a machine-readable storage medium for executing the computer instructions in the machine-readable storage medium to implement the method of any one of claims 1-9.
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