CN118035527A - Interactive data processing method, medium and equipment for business and resource - Google Patents
Interactive data processing method, medium and equipment for business and resource Download PDFInfo
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Abstract
The application provides a business and resource interactive data processing method, medium and equipment, belonging to the technical field of data processing, comprising the following steps: acquiring target services and target resources matched with each target service in a preset time period based on a big data platform, and carrying out standard matching analysis on each target service and each target resource; determining the resource interaction category of each target service based on the standard matching analysis result, and generating heterogeneous characteristics of the corresponding target service; the feature codes in the feature code set corresponding to each heterogeneous feature are respectively input into an interaction mapping table, and the resource interaction coefficient under each service interaction index and the service interaction coefficient under each resource interaction index are determined; according to the resource interaction coefficient and the service interaction coefficient and in combination with the service resource interaction standard, a deletion mapping function based on a large data platform is established, and supplementary resources based on target service are called to realize data interaction. And the matching accuracy of the service and the resource is improved.
Description
Technical Field
The invention relates to a business and resource interactive data processing method, medium and equipment, belonging to the technical field of data processing.
Background
In the knowledge economy era, the Internet is increasingly changing the life style of people, and the society and economy change is promoted. The service mode and the product structure of the internet are continuously innovated and perfected, and the internet service is continuously developed, wherein the internet service is a fusion innovation representing new generation information technology, modern manufacturing industry, productive service industry and the like, but in the service development process, a common resource calling mode is directly matched with the service, whether the called resource is accurate or not is not concerned too much, that is, certain interaction defects exist in the service and resource interaction process, for example, the service needs to call environment learning materials, but the matched resource only needs to learn materials and does not distinguish environment materials, so that certain errors exist in the resource and service matching.
Therefore, the invention provides a business and resource interaction data processing method, medium and equipment.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a service and resource interaction data processing method, medium and equipment, which are used for determining the heterogeneous characteristics of a target service by carrying out matching analysis on the target service, the target resource and a standard resource, effectively preliminarily determining the existing anomalies to provide traversal for the establishment of a follow-up true function, and calling the supplementary resource by combining the missing mapping function by inputting codes into a mapping table, thereby reducing the condition of unreasonable resource matching caused by the interaction defect in the service and resource interaction process to a certain extent, and further improving the matching accuracy of the service and the resource.
The invention provides a business and resource interaction data processing method, which comprises the following steps:
step 1: acquiring target services and target resources matched with each target service in a preset time period based on a big data platform, and carrying out standard matching analysis on each target service and each target resource;
Step 2: determining the resource interaction category of each target service based on the standard matching analysis result, and generating heterogeneous characteristics of the corresponding target service;
Step 3: the feature codes in the feature code set corresponding to each heterogeneous feature are respectively input into an interaction mapping table, and the resource interaction coefficient under each service interaction index and the service interaction coefficient under each resource interaction index are determined;
Step 4: and establishing a missing mapping function set based on the big data platform according to the resource interaction coefficient and the service interaction coefficient and combining with the service resource interaction standard as a calling supplement for the big data platform to realize the data interaction of new service.
Further, step 1 includes:
Acquiring a process signal for carrying out resource allocation according to the target service based on a big data platform, wherein the process signal comprises a resource calling signal under resource allocation, a resource type matched with the resource calling signal and a signal duration of each resource calling signal;
Acquiring an allocation log of the target service and the target resource in the resource allocation process, and carrying out segmentation processing on the allocation log to acquire the generation frequency of each segmented log;
Fitting treatment is carried out on all the generated frequencies after standardization, a fitting line aiming at the distribution process is constructed, and the protruding points on the fitting line are locked and line-expanded to obtain protruding sections;
Performing response analysis on the process signals, and calculating resource retrieval quality under each resource retrieval signal by combining standard resources predefined and corresponding to the target service;
wherein/> Representing resource retrieval quality under the i1 st resource retrieval signal; /(I)Representing the resource scheduling/>, under the i1 st resource scheduling signalAnd corresponding standard resource/>A similarity function between the two; /(I)Representing signal duration/>, based on i1 st resource scheduling signalResource capacity/>, corresponding to resource typeThe success coefficient is fetched once; /(I)Representing a standard call success coefficient; min represents a minimum symbol; n1 represents the number of resource call signals;
Determining a matching error range from the attribute-error mapping table according to the service attribute of the corresponding target service;
And determining a standard matching analysis result of the corresponding target service based on the resource retrieval quality, the matching error range and all the salient segments.
Further, determining a standard matching analysis result of the corresponding target service includes:
Determining the protruding section related to each resource calling signal, determining the first ratio of the section length of each related section to the section length between two adjacent points corresponding to the protruding points, and sequencing according to the time sequence to obtain a corresponding ratio array;
determining a calling abnormal coefficient under a corresponding resource calling signal based on the ratio array, the resource calling quality and the matching error range;
Wherein, Representing the fetch exception coefficient under the i1 st resource fetch signal; /(I)Representing standard call quality under the ith resource call signal; /(I)Representing the number of first ratios in the corresponding ratio array; /(I)Represents the j1 st first ratio; /(I)A protrusion height indicating that the j1 st protrusion point based on the comparison array is higher than the standard set height; /(I)Representing the total protrusion height of the j1 th protrusion point based on the comparison array, wherein the protrusion points are in one-to-one correspondence with the segment lengths of the corresponding related segments and the first ratio; /(I)Representing an analysis function based on the i1 st related segment; /(I)Representing a resource call signal/>, based on the i1 st resourceMatch error Range/>Is a trace of a regulatory factor; /(I)Representing a set weight based on quality; /(I)Representing a set weight based on the salient segments;
If the calling abnormal coefficient is smaller than the preset abnormal coefficient, judging that abnormal matching information of the corresponding resource calling signal does not exist;
otherwise, calculating the resource difference extraction proportion under the corresponding resource calling signal according to the coefficient difference value of the calling abnormal coefficient and the preset abnormal coefficient;
And determining a left extraction boundary and a right extraction boundary for realizing continuous extraction of the corresponding actual allocated resources according to the resource difference extraction proportion and the ratio array, and obtaining a standard matching analysis result.
Further, calculating the resource difference extraction ratio under the corresponding resource call signal includes:
Wherein YX represents a preset difference coefficient; representing the coefficient difference; /(I) Representing all/>Maximum value of (2); /(I)Is a variable, and/>；/>And representing the resource difference extraction ratio under the corresponding resource calling signal.
Further, step 2 includes:
Constructing an abnormal distribution diagram corresponding to the target service according to the standard matching analysis result, wherein the abnormal distribution diagram comprises distribution columns corresponding to the resource calling signals one by one and abnormal types of the resources;
Comparing the abnormal distribution diagram with a standard distribution diagram, determining the amplitude variation of each distribution column according to a comparison result, screening the minimum amplitude variation from all the amplitude variation, and correcting each residual amplitude variation in sequence;
Determining a resource interaction category of the corresponding target service based on the correction distribution diagram;
and obtaining the characteristic expression of the resource interaction category, and inputting the characteristic expression into a heterogeneous analysis model to obtain heterogeneous characteristics.
Further, step 3 includes:
generating feature codes of each heterogeneous feature based on a feature code generation model, wherein the feature codes of all the heterogeneous features are combined into a feature code set;
According to the predefined service interaction description and the resource interaction description in the interaction mapping table, carrying out coding splitting on each feature code and sequentially filling the feature codes into corresponding blank cells to obtain a filled mapping table;
Performing first locking of filling grids on the filled mapping table according to the service interaction indexes to obtain resource interaction coefficients;
and simultaneously, performing second locking of filling grids on the filled mapping table according to the resource interaction index to obtain a service interaction coefficient.
Further, step 4 includes:
Performing field standardized conversion on standard resources matched with a target service to obtain a field expression, and splitting the field expression;
combining the business resource interaction standard, the resource interaction coefficient and the business interaction coefficient to respectively acquire the resource deformation coefficient of the split resource corresponding to each split expression;
Extracting modified resources in one-to-one correspondence with each split resource respectively by using target resources matched with target service, and distributing permission modification tags to the corresponding modified resources by combining resource deformation coefficients corresponding to the modified resources;
And constructing a deletion mapping function of the target resource according to the permission change label, and obtaining a deletion mapping function set.
Further, respectively obtaining the resource deformation coefficient of the split resource corresponding to each split expression includes:
Expression duty ratio based on whole field expression according to each split expression Expression weight/>Obtaining the resource interaction coefficient/>, based onFirst interaction coefficient/>Based on business interaction coefficient/>Second interaction coefficient/>；
Based on the first interaction coefficient and the second interaction coefficient, and combining with a business resource interaction standardCalculating to obtain the resource deformation coefficient/>, corresponding to the split resource；
Wherein,Representing the corresponding split expression; /(I)The representation is based on/>And/>Is a self-deformation function of (a); /(I)The representation is based on/>And/>Is a deformation adjusting function of (a);
The present invention provides a computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of any of the methods.
The present invention provides a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of any of the methods.
Compared with the prior art, the application has the following beneficial effects:
the heterogeneous characteristics of the target service are determined by carrying out matching analysis on the target service, the target resource and the standard resource, the existing abnormality is effectively and preliminarily determined to provide traversal for the establishment of the follow-up true function, and the supplementary resource is called by combining the missing mapping function by inputting the code into the mapping table, so that the condition of unreasonable resource matching caused by the interaction defect in the interaction process of the service and the resource is reduced to a certain extent, and the matching accuracy of the service and the resource is further improved.
Drawings
FIG. 1 is a flow chart of a business and resource interaction data processing method of the present invention;
Fig. 2 is a block diagram of a protruding section of the present invention.
Detailed Description
In order that those skilled in the art will better understand the technical solutions of the present application, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It is noted that when an element is referred to as being "fixed" or "disposed on" another element, it can be directly on the other element or be indirectly disposed on the other element; when an element is referred to as being "connected to" another element, it can be directly connected to the other element or be indirectly connected to the other element.
It is to be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are merely for convenience in describing and simplifying the description based on the orientation or positional relationship shown in the drawings, and do not indicate or imply that the devices or components referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus are not to be construed as limiting the application.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, the meaning of "a plurality" or "a number" means two or more, unless specifically defined otherwise.
It should be understood that the structures, proportions, sizes, etc. shown in the drawings are for the purpose of understanding and reading the disclosure, and are not intended to limit the scope of the application, which is defined by the claims, but rather by the claims, unless otherwise indicated, and that any structural modifications, proportional changes, or dimensional adjustments, which would otherwise be apparent to those skilled in the art, would be made without departing from the spirit and scope of the application.
Example 1:
The invention provides a business and resource interaction data processing method, as shown in figure 1, comprising the following steps:
step 1: acquiring target services and target resources matched with each target service in a preset time period based on a big data platform, and carrying out standard matching analysis on each target service and each target resource;
Step 2: determining the resource interaction category of each target service based on the standard matching analysis result, and generating heterogeneous characteristics of the corresponding target service;
Step 3: the feature codes in the feature code set corresponding to each heterogeneous feature are respectively input into an interaction mapping table, and the resource interaction coefficient under each service interaction index and the service interaction coefficient under each resource interaction index are determined;
Step 4: and establishing a missing mapping function set based on the big data platform according to the resource interaction coefficient and the service interaction coefficient and combining with the service resource interaction standard as a calling supplement for the big data platform to realize the data interaction of new service.
In one embodiment, the big data platform refers to a platform that needs to analyze services and resources, that is, an internet platform, and the preset period of time is, for example, 1 hour, and the target service is a target setting for resource calling in the 1 hour, for example, calling environment learning materials, calling language learning materials, and the like.
The target resource refers to a retrieval result matched with the retrieval learning material service, namely, an actual retrieval resource.
In one embodiment, the standard matching analysis refers to comparing the preset standard resources corresponding to the target service with the actual call resources.
In one embodiment, the resource interaction category refers to the difference between the criteria that the target business exists and the actual, i.e., a determination of which resources are still missing.
In one embodiment, heterogeneous characteristics refer to anomalies that are determined based on absent resources.
In one embodiment, the feature coding of the heterogeneous feature is used for uniquely expressing the feature, so that the feature is conveniently and reasonably placed in an interaction mapping table, and the interaction mapping table contains expressions matched with the business interaction indexes and expressions matched with the resource interaction indexes.
In one embodiment, the resource interaction coefficient and the business interaction coefficient are comprehensively determined based on the filling content in the corresponding filling grid in the interaction mapping table.
In one embodiment, the business resource interaction criteria, i.e., the actual call resources, should at least match the standard resources at 80& and above.
In one embodiment, the construction of the deletion mapping function is to analyze the resource deletion condition of each target service, so that the large data platform can make up the original interaction defect as much as possible in the subsequent service and resource interaction process, ensure the integrity and rationality of resource calling corresponding to the subsequent service (new service), and realize effective data interaction, wherein the function set comprises a plurality of deletion mapping functions.
The beneficial effects of the technical scheme are as follows: the heterogeneous characteristics of the target service are determined by carrying out matching analysis on the target service, the target resource and the standard resource, the existing abnormality is effectively and preliminarily determined to provide traversal for the establishment of the follow-up true function, and the supplementary resource is called by combining the missing mapping function by inputting the code into the mapping table, so that the condition of unreasonable resource matching caused by the interaction defect in the interaction process of the service and the resource is reduced to a certain extent, and the matching accuracy of the service and the resource is further improved.
Example 2:
the invention provides a business and resource interaction data processing method, which comprises the following steps:
Acquiring a process signal for carrying out resource allocation according to the target service based on a big data platform, wherein the process signal comprises a resource calling signal under resource allocation, a resource type matched with the resource calling signal and a signal duration of each resource calling signal;
Acquiring an allocation log of the target service and the target resource in the resource allocation process, and carrying out segmentation processing on the allocation log to acquire the generation frequency of each segmented log;
Fitting treatment is carried out on all the generated frequencies after standardization, a fitting line aiming at the distribution process is constructed, and the protruding points on the fitting line are locked and line-expanded to obtain protruding sections;
Performing response analysis on the process signals, and calculating resource retrieval quality under each resource retrieval signal by combining standard resources predefined and corresponding to the target service;
wherein/> Representing resource retrieval quality under the i1 st resource retrieval signal; /(I)Representing the resource scheduling/>, under the i1 st resource scheduling signalAnd corresponding standard resource/>A similarity function between the two; /(I)Representing signal duration/>, based on i1 st resource scheduling signalResource capacity/>, corresponding to resource typeThe success coefficient is fetched once; /(I)Representing a standard call success coefficient; min represents a minimum symbol; n1 represents the number of resource call signals;
Determining a matching error range from the attribute-error mapping table according to the service attribute of the corresponding target service;
And determining a standard matching analysis result of the corresponding target service based on the resource retrieval quality, the matching error range and all the salient segments.
In one embodiment, in the process of performing resource allocation, a large data platform issues an allocation request to a corresponding resource according to a target service, that is, the allocation request is a resource allocation signal, because the target service has requirements for different resource data, the resource requirements of the target service can be split into a plurality of resource types according to the resource requirements, the allocation request corresponding to each resource type is a resource allocation signal, and the duration of the signal refers to the average duration of response received by the corresponding allocation request in the history request process, and subsequent resource allocation can be performed only after the response.
In one embodiment, the standard resource refers to a resource that needs to be called for corresponding to the target service, but a certain error exists in the calling process, so that the actually called resource is different from the standard resource.
In one embodiment, the allocation log is obtained by the capturing tool during the allocation process of the resource, mainly for reasonably obtaining the data generated during the allocation process, and the capturing tool is set on a large data platform in advance, which belongs to the prior art.
In one embodiment, the purpose of the segmentation process is to analyze the distribution log in parallel, for example, segment the distribution log according to a certain time length, where the log under each time length is the segmented log, and the frequency generated by capturing the corresponding log is generally the inverse of the total amount of captured data/capturing time.
In one embodiment, the normalization and fitting process is performed on the frequencies to construct a fit line for the assignment process, and is plotted from several fit frequencies.
In one embodiment, a salient point refers to a point that exceeds a set standard fit value, and a salient segment refers to a segment that includes the salient point, and a line extension is an extension that depends on a difference from the value of the salient point and the set standard fit value as a reference, the larger the difference is, the larger the range of the corresponding extension is,
As shown in fig. 2, a1 is a salient point, the line is expanded to an expansion of a1, the last salient section is a b1 section, and the longest length of the line expansion is smaller than the length of a line segment formed by midpoints of line segments corresponding to a1 and a2 and a1 and a 3.
In one embodiment, the business attributes are related to resource invocation, such as learning business attributes, network business attributes, and the like.
In one embodiment, the attribute-to-error mapping table contains different attributes and error ranges matched with the attributes, facilitating subsequent determination of standard match analysis results.
The beneficial effects of the technical scheme are as follows: the standard matching analysis result is comprehensively determined according to the resource retrieval quality obtained by the response analysis of the process signals and the salient segments under the corresponding generation frequency of the distribution log, the reliability and the rationality of the result acquisition are ensured, and a foundation is provided for the rationality of the subsequent resource retrieval.
Example 3:
The invention provides a business and resource interaction data processing method, which determines a standard matching analysis result of a corresponding target business, and comprises the following steps:
Determining the protruding section related to each resource calling signal, determining the first ratio of the section length of each related section to the section length between two adjacent points corresponding to the protruding points, and sequencing according to the time sequence to obtain a corresponding ratio array;
determining a calling abnormal coefficient under a corresponding resource calling signal based on the ratio array, the resource calling quality and the matching error range;
Wherein, Representing the fetch exception coefficient under the i1 st resource fetch signal; /(I)Representing standard call quality under the ith resource call signal; /(I)Representing the number of first ratios in the corresponding ratio array; /(I)Represents the j1 st first ratio; /(I)A protrusion height indicating that the j1 st protrusion point based on the comparison array is higher than the standard set height; /(I)Representing the total protrusion height of the j1 th protrusion point based on the comparison array, wherein the protrusion points are in one-to-one correspondence with the segment lengths of the corresponding related segments and the first ratio; /(I)Representing an analysis function based on the i1 st related segment; /(I)Representing a resource call signal/>, based on the i1 st resourceMatch error Range/>Is a trace of a regulatory factor; /(I)Representing a set weight based on quality; /(I)Representing a set weight based on the salient segments;
If the calling abnormal coefficient is smaller than the preset abnormal coefficient, judging that abnormal matching information of the corresponding resource calling signal does not exist;
otherwise, calculating the resource difference extraction proportion under the corresponding resource calling signal according to the coefficient difference value of the calling abnormal coefficient and the preset abnormal coefficient;
And determining a left extraction boundary and a right extraction boundary for realizing continuous extraction of the corresponding actual allocated resources according to the resource difference extraction proportion and the ratio array, and obtaining a standard matching analysis result.
In one embodiment, the ratio between the length of the segment b1 corresponding to the first ratio a1 and the length of the segment between a2 and a3 is the ratio between the length of the segment b1 and the length of the segment between a2 and a3, and since the line involved in one resource retrieval signal is one segment, that is, there may be a plurality of protruding segments, and thus the ratio array { the first ratio of the protruding segment 1 and the protruding segment 2 of the protruding segment may be constructed according to the sequence.
In one embodiment, the preset anomaly coefficient is preset, and a judgment basis is provided for the standard matching analysis result.
In one embodiment, the coefficient difference is an anomaly coefficient-a predetermined anomaly coefficient.
In one embodiment, since the ratio arrays are sequentially ordered, the more significant the ratio, the more significant the highlighting is, and further, in the process of determining the boundary according to the extraction ratio, the resource frames with significant highlighting need to be selected as far as possible to implement continuous extraction, and at this time, there are a left extraction boundary and a right extraction boundary, where the comparison result of the resources corresponding to the ratio in the range is regarded as the standard matching analysis result.
The beneficial effects of the technical scheme are as follows: the ratio value of each resource calling signal is determined by determining the salient segment, the calling abnormal coefficient is calculated by combining the resource calling quality and the matching error range, the final standard matching analysis result is determined by comparing and judging the coefficient, and in the process of determining the result, the key abnormal result is conveniently extracted by determining the resource difference extraction proportion, namely, the abnormality can be analyzed and judged as completely as possible under the condition of reducing the consumption of the abnormal analysis, so that the analysis efficiency is improved, and the matching rationality of the service and the resource is also ensured.
Example 4:
The invention provides a business and resource interaction data processing method, which calculates the resource difference extraction proportion under the corresponding resource calling signal, and comprises the following steps:
Wherein YX represents a preset difference coefficient; representing the coefficient difference; /(I) Representing all/>Maximum value of (2); /(I)Is a variable, and/>；/>And representing the resource difference extraction ratio under the corresponding resource calling signal.
In one embodiment of the present invention, in one embodiment,With/>But the overall calculated value is less than 1.
The beneficial effects of the technical scheme are as follows: the resource difference extraction proportion under different ranges is discussed through three kinds of condition classification, so that a foundation is provided for the acquisition of the subsequent standard matching analysis result.
Example 5:
the invention provides a business and resource interaction data processing method, which comprises the following steps:
Constructing an abnormal distribution diagram corresponding to the target service according to the standard matching analysis result, wherein the abnormal distribution diagram comprises distribution columns corresponding to the resource calling signals one by one and abnormal types of the resources;
Comparing the abnormal distribution diagram with a standard distribution diagram, determining the amplitude variation of each distribution column according to a comparison result, screening the minimum amplitude variation from all the amplitude variation, and correcting each residual amplitude variation in sequence;
Determining a resource interaction category of the corresponding target service based on the correction distribution diagram;
and obtaining the characteristic expression of the resource interaction category, and inputting the characteristic expression into a heterogeneous analysis model to obtain heterogeneous characteristics.
In one embodiment, each resource anomaly type corresponds to a distribution bar, i.e., the anomaly profile is represented in a cylindrical form.
In one embodiment, the standard profile is set according to standard resources.
In one embodiment, the magnitude change of the distribution column refers to the difference in column height for the same distribution column in the anomaly profile and the standard profile.
In one embodiment, the minimum amplitude variation refers to the amplitude differences of other distribution columns that are consistent with respect to anomalies of the distribution columns as compared to the standard.
In one embodiment, correction of amplitude variation = amplitude variation- (sum of minimum amplitude variation/amplitude variation) ×unit adjustment coefficient.
In one embodiment, the corrected profile is a graph after the magnitude adjustment of the abnormal profile.
In one embodiment, the resource interaction category refers to an abnormal condition that exists as determined by the correction profile, for example, the resource call signal 1 is in the absence of the resource 01 and the absence is b1.
In one embodiment, the feature expression is: resource 01- -b1, etc.
In one embodiment, the heterogeneous analysis model is obtained by training a neural network model based on a combination of different feature expressions and features obtained by performing anomaly analysis on the combination of feature expressions by an expert, so that heterogeneous features can be directly obtained and mainly used for determining the real situation corresponding to the anomaly.
The beneficial effects of the technical scheme are as follows: by constructing an abnormal distribution diagram and comparing the abnormal distribution diagram with a standard distribution diagram, correction of each distribution column in the abnormal distribution diagram is realized, the resource interaction category is further determined, heterogeneous characteristics are obtained, a basis is provided for the rationality of subsequent interaction matching of resources and services, and the reliability of the construction of subsequent functions is further ensured.
Example 6:
the invention provides a business and resource interaction data processing method, which comprises the following steps:
generating feature codes of each heterogeneous feature based on a feature code generation model, wherein the feature codes of all the heterogeneous features are combined into a feature code set;
According to the predefined service interaction description and the resource interaction description in the interaction mapping table, carrying out coding splitting on each feature code and sequentially filling the feature codes into corresponding blank cells to obtain a filled mapping table;
Performing first locking of filling grids on the filled mapping table according to the service interaction indexes to obtain resource interaction coefficients;
and simultaneously, performing second locking of filling grids on the filled mapping table according to the resource interaction index to obtain a service interaction coefficient.
In one embodiment, the feature code generation model is obtained by training a neural network model based on different heterogeneous features and the codes of the heterogeneous features by an expert as samples, and feature codes can be directly obtained.
In one embodiment, the interactive mapping table is a preset blank table, and the interactive descriptions of the predetermined service and resource in the table are all present and are in one-to-one correspondence with the feature codes, so that the filled mapping table can be obtained by splitting the corresponding codes and filling the codes, for example, the feature codes are as follows: the mapping table is obtained by filling correspondingly, wherein the business interaction description 1 is the business interaction description 2, and the resource interaction description 1 is the percentage.
In an embodiment, the first locking refers to locking the filling grid corresponding to the service interaction description corresponding to the service interaction index, and the second locking is similar to the first locking in principle, which is not described herein.
In one embodiment, the resource interaction coefficient=the difference coefficient between the content in the corresponding filling grid and the content standard is obtained by summing and then averaging, and the calculation manner of the service interaction coefficient is similar, which is not described herein.
The beneficial effects of the technical scheme are as follows: the feature codes are split to fill the response content into blank lattices according to the service interaction description and the resource interaction description, and then the interaction coefficients are obtained according to the locking of corresponding indexes, so that a foundation is provided for the subsequent construction of the deletion mapping function.
Example 7:
The invention provides a business and resource interaction data processing method, which comprises the following steps:
Performing field standardized conversion on standard resources matched with a target service to obtain a field expression, and splitting the field expression;
combining the business resource interaction standard, the resource interaction coefficient and the business interaction coefficient to respectively acquire the resource deformation coefficient of the split resource corresponding to each split expression;
Extracting modified resources in one-to-one correspondence with each split resource respectively by using target resources matched with target service, and distributing permission modification tags to the corresponding modified resources by combining resource deformation coefficients corresponding to the modified resources;
And constructing a deletion mapping function of the target resource according to the permission change label, and obtaining a deletion mapping function set.
Further, respectively obtaining the resource deformation coefficient of the split resource corresponding to each split expression includes:
Expression duty ratio based on whole field expression according to each split expression Expression weight/>Obtaining the resource interaction coefficient/>, based onFirst interaction coefficient/>Based on business interaction coefficient/>Second interaction coefficient/>；
Based on the first interaction coefficient and the second interaction coefficient, and combining with a business resource interaction standardCalculating to obtain the resource deformation coefficient/>, corresponding to the split resource；
Wherein,Representing the corresponding split expression; /(I)The representation is based on/>And/>Is a self-deformation function of (a); /(I)The representation is based on/>And/>Is a deformation adjusting function of (a).
In one embodiment, the field standardization is a conversion standard preset by an expert to implement conversion of standard resources, for example, field expression is obtained after conversion of standard resources: Y1U2Y1O1, two split expressions can be obtained: Y1U2, Y1O1.
In one embodiment, the purpose of determining the resource deformation coefficient is to determine that in the process of calling the corresponding resource according to the same service, the different possibility exists between the resource deformation coefficient and the standard resource, and the larger the resource deformation coefficient is, the larger the different possibility exists correspondingly.
In one embodiment, the modification of the labels is allowed to label the corresponding resource deformation coefficients and the modified resources for subsequent presentation.
In one embodiment, the deletion mapping function = GQ { tag 1 tag 2.
The beneficial effects of the technical scheme are as follows: and determining a resource deformation coefficient by carrying out field expression on the standard resource, setting a change label to construct a deletion mapping function, providing a basis for resource allocation of a subsequent new service, and reducing overlarge resource matching difference of the new service caused by interaction defects.
Example 8:
The present invention provides a computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the method steps of:
step 1: acquiring target services and target resources matched with each target service in a preset time period based on a big data platform, and carrying out standard matching analysis on each target service and each target resource;
Step 2: determining the resource interaction category of each target service based on the standard matching analysis result, and generating heterogeneous characteristics of the corresponding target service;
Step 3: the feature codes in the feature code set corresponding to each heterogeneous feature are respectively input into an interaction mapping table, and the resource interaction coefficient under each service interaction index and the service interaction coefficient under each resource interaction index are determined;
Step 4: and establishing a missing mapping function set based on the big data platform according to the resource interaction coefficient and the service interaction coefficient and combining with the service resource interaction standard as a calling supplement for the big data platform to realize the data interaction of new service.
Example 9:
The invention provides a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the method steps of:
step 1: acquiring target services and target resources matched with each target service in a preset time period based on a big data platform, and carrying out standard matching analysis on each target service and each target resource;
Step 2: determining the resource interaction category of each target service based on the standard matching analysis result, and generating heterogeneous characteristics of the corresponding target service;
Step 3: the feature codes in the feature code set corresponding to each heterogeneous feature are respectively input into an interaction mapping table, and the resource interaction coefficient under each service interaction index and the service interaction coefficient under each resource interaction index are determined;
Step 4: and establishing a missing mapping function set based on the big data platform according to the resource interaction coefficient and the service interaction coefficient and combining with the service resource interaction standard as a calling supplement for the big data platform to realize the data interaction of new service.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A business and resource interaction data processing method is characterized by comprising the following steps:
step 1: acquiring target services and target resources matched with each target service in a preset time period based on a big data platform, and carrying out standard matching analysis on each target service and each target resource;
Step 2: determining the resource interaction category of each target service based on the standard matching analysis result, and generating heterogeneous characteristics of the corresponding target service;
Step 3: the feature codes in the feature code set corresponding to each heterogeneous feature are respectively input into an interaction mapping table, and the resource interaction coefficient under each service interaction index and the service interaction coefficient under each resource interaction index are determined;
Step 4: and establishing a missing mapping function set based on the big data platform according to the resource interaction coefficient and the service interaction coefficient and combining with the service resource interaction standard as a calling supplement for the big data platform to realize the data interaction of new service.
2. The method for processing interactive data between service and resource according to claim 1, wherein step 1 comprises:
Acquiring a process signal for carrying out resource allocation according to the target service based on a big data platform, wherein the process signal comprises a resource calling signal under resource allocation, a resource type matched with the resource calling signal and a signal duration of each resource calling signal;
Acquiring an allocation log of the target service and the target resource in the resource allocation process, and carrying out segmentation processing on the allocation log to acquire the generation frequency of each segmented log;
Fitting treatment is carried out on all the generated frequencies after standardization, a fitting line aiming at the distribution process is constructed, and the protruding points on the fitting line are locked and line-expanded to obtain protruding sections;
Performing response analysis on the process signals, and calculating resource retrieval quality under each resource retrieval signal by combining standard resources predefined and corresponding to the target service;
Wherein, Representing resource retrieval quality under the i1 st resource retrieval signal; /(I)Representing the resource scheduling/>, under the i1 st resource scheduling signalAnd corresponding standard resource/>A similarity function between the two; /(I)Representing signal duration/>, based on i1 st resource scheduling signalResource capacity/>, corresponding to resource typeThe success coefficient is fetched once; /(I)Representing a standard call success coefficient; min represents a minimum symbol; n1 represents the number of resource call signals;
Determining a matching error range from the attribute-error mapping table according to the service attribute of the corresponding target service;
And determining a standard matching analysis result of the corresponding target service based on the resource retrieval quality, the matching error range and all the salient segments.
3. The service and resource interaction data processing method according to claim 2, wherein determining a standard match analysis result of the corresponding target service includes:
Determining the protruding section related to each resource calling signal, determining the first ratio of the section length of each related section to the section length between two adjacent points corresponding to the protruding points, and sequencing according to the time sequence to obtain a corresponding ratio array;
determining a calling abnormal coefficient under a corresponding resource calling signal based on the ratio array, the resource calling quality and the matching error range;
Wherein, Representing the fetch exception coefficient under the i1 st resource fetch signal; /(I)Representing standard call quality under the ith resource call signal; /(I)Representing the number of first ratios in the corresponding ratio array; /(I)Represents the j1 st first ratio; /(I)A protrusion height indicating that the j1 st protrusion point based on the comparison array is higher than the standard set height; /(I)Representing the total protrusion height of the j1 th protrusion point based on the comparison array, wherein the protrusion points are in one-to-one correspondence with the segment lengths of the corresponding related segments and the first ratio; /(I)Representing an analysis function based on the i1 st related segment; /(I)Representing a resource call signal/>, based on the i1 st resourceMatch error Range/>Is a trace of a regulatory factor; /(I)Representing a set weight based on quality; /(I)Representing a set weight based on the salient segments;
If the calling abnormal coefficient is smaller than the preset abnormal coefficient, judging that abnormal matching information of the corresponding resource calling signal does not exist;
otherwise, calculating the resource difference extraction proportion under the corresponding resource calling signal according to the coefficient difference value of the calling abnormal coefficient and the preset abnormal coefficient;
And determining a left extraction boundary and a right extraction boundary for realizing continuous extraction of the corresponding actual allocated resources according to the resource difference extraction proportion and the ratio array, and obtaining a standard matching analysis result.
4. The method for processing interactive data between service and resource according to claim 3, wherein calculating the resource difference extraction ratio under the corresponding resource call signal comprises:
wherein YX represents a preset difference coefficient; Representing the coefficient difference; /(I) Representing all/>Maximum value of (2); /(I)Is a variable, and/>； />And representing the resource difference extraction ratio under the corresponding resource calling signal.
5. A method for processing interactive data between services and resources according to claim 3, wherein step 2 comprises:
Constructing an abnormal distribution diagram corresponding to the target service according to the standard matching analysis result, wherein the abnormal distribution diagram comprises distribution columns corresponding to the resource calling signals one by one and abnormal types of the resources;
Comparing the abnormal distribution diagram with a standard distribution diagram, determining the amplitude variation of each distribution column according to a comparison result, screening the minimum amplitude variation from all the amplitude variation, and correcting each residual amplitude variation in sequence;
Determining a resource interaction category of the corresponding target service based on the correction distribution diagram;
and obtaining the characteristic expression of the resource interaction category, and inputting the characteristic expression into a heterogeneous analysis model to obtain heterogeneous characteristics.
6. The method for processing interactive data between service and resource according to claim 1, wherein step 3 comprises:
generating feature codes of each heterogeneous feature based on a feature code generation model, wherein the feature codes of all the heterogeneous features are combined into a feature code set;
According to the predefined service interaction description and the resource interaction description in the interaction mapping table, carrying out coding splitting on each feature code and sequentially filling the feature codes into corresponding blank cells to obtain a filled mapping table;
Performing first locking of filling grids on the filled mapping table according to the service interaction indexes to obtain resource interaction coefficients;
and simultaneously, performing second locking of filling grids on the filled mapping table according to the resource interaction index to obtain a service interaction coefficient.
7. The method for processing interactive data between service and resource according to claim 1, wherein step 4 comprises:
Performing field standardized conversion on standard resources matched with a target service to obtain a field expression, and splitting the field expression;
combining the business resource interaction standard, the resource interaction coefficient and the business interaction coefficient to respectively acquire the resource deformation coefficient of the split resource corresponding to each split expression;
Extracting modified resources in one-to-one correspondence with each split resource respectively by using target resources matched with target service, and distributing permission modification tags to the corresponding modified resources by combining resource deformation coefficients corresponding to the modified resources;
And constructing a deletion mapping function of the target resource according to the permission change label, and obtaining a deletion mapping function set.
8. The method for processing interactive data between service and resource according to claim 7, wherein obtaining the resource deformation coefficient of the split resource corresponding to each split expression respectively comprises:
Expression duty ratio based on whole field expression according to each split expression Expression weight/>Obtaining the resource interaction coefficient/>, based onFirst interaction coefficient/>Based on business interaction coefficient/>Second interaction coefficient/>；
Based on the first interaction coefficient and the second interaction coefficient, and combining with a business resource interaction standard/>Calculating to obtain the resource deformation coefficient/>, corresponding to the split resource；
Wherein/>Representing the corresponding split expression; /(I)The representation is based on/>And/>Is a self-deformation function of (a); /(I)The representation is based on/>And/>Is a deformation adjusting function of (a).
9. A computer-readable storage medium, characterized in that a computer program is stored, which, when being executed by a processor, causes the processor to perform the steps of the method according to any one of claims 1 to 8.
10. A computer device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the method according to any one of claims 1 to 8.
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