CN116089733B

CN116089733B - Data analysis method based on big data

Info

Publication number: CN116089733B
Application number: CN202310382454.9A
Authority: CN
Inventors: 张兵
Original assignee: Yuexiang Starlight Beijing Technology Co ltd
Current assignee: Yuexiang Starlight Beijing Technology Co ltd
Priority date: 2023-04-12
Filing date: 2023-04-12
Publication date: 2023-06-16
Anticipated expiration: 2043-04-12
Also published as: CN116089733A

Abstract

The invention provides a data analysis method based on big data, which comprises the following steps: acquiring service operation information of each network service to establish an operation list; performing row processing and line processing on the operation list to obtain a service operation list; determining a service access period corresponding to the network service and an access key time point in the access period, and constructing a service access list; collecting and capturing service logs aiming at network services, determining to obtain a use scene set of the corresponding network services, static information and dynamic information under different use scenes, and constructing a service personality list; and based on the service operation list, the service access list and the service personality list of all network services, similar ordering is carried out on the corresponding network services, and output recommendation is carried out. Corresponding exhibition tables are respectively constructed from the three dimensions, so that output recommendation of the same type of network service is realized, and the experience of a user on related software applications is effectively met.

Description

Data analysis method based on big data

Technical Field

The invention relates to the technical field of big data, in particular to a data analysis method based on big data.

Background

With the rapid development of internet of things, various network services are protruded, such as short video service, interactive live broadcast service, network variety service, online game service and the like, however, because the network services are disordered and incomparable, a plurality of software applications corresponding to the same type of network service exist, and because users lack of cognition on different network services, in the process of downloading corresponding software applications, relevant software applications can be randomly selected for downloading or downloading the software applications with high downloading quantity only according to human cognition, in the process, whether the network service corresponding to the software application has downloading value or not is not considered in many aspects, that is, the subsequently downloaded software applications can not well meet user experience.

Therefore, the invention provides a data analysis method based on big data.

Disclosure of Invention

The invention provides a data analysis method based on big data, which is used for respectively constructing corresponding exhibition tables from service operation information, service access information and service logs of network services, so as to realize the output recommendation of the same type of network services, analyze the existence value of the network services in multiple aspects and effectively meet the experience of users on related software applications.

The invention provides a data analysis method based on big data, which comprises the following steps:

step 1: acquiring service operation information of each network service, and establishing an operation list of the corresponding network service;

step 2: performing row processing and column processing on the operation list to obtain corresponding characteristic information, and obtaining a service operation list consistent with the characteristic information from an information-exhibition mapping database;

step 3: determining a service access period of the corresponding network service and an access key time point in the access period according to the access information of the allowed access party for each network service, and constructing a service access list;

step 4: collecting and capturing service logs aiming at network services, analyzing the service logs, determining to obtain a service scene set corresponding to the network services, static information and dynamic information under different service scenes, and constructing a service personality list corresponding to the network services based on a determination result;

step 5: and based on the service operation list, the service access list and the service personality list of all network services, similar ordering is carried out on the corresponding network services, and output recommendation is carried out.

Preferably, acquiring service operation information of each network service, and establishing an operation list of the corresponding network service, including:

monitoring task operation processes of service tasks which are distributed to each network service in advance;

acquiring a service operation script of each network service, and carrying out script analysis on the service operation script to obtain a service operation block;

extracting a first description of an operation parameter of each service operation block and a first standard;

according to the extraction result, constructing and obtaining an operation array of the corresponding service operation block, and constructing and obtaining a standard operation array of the corresponding network service;

and carrying out corresponding placement processing on the process monitoring result and the standard operation array to obtain an operation list of the corresponding network service.

Preferably, the processing of the row and the column of the playlist to obtain corresponding feature information includes:

constructing a first difference set of each row of information in the same operation list;

wherein ,

a first difference set representing information of a j1 st row in the same operation list; />

A parameter conversion coefficient representing an i1 st operation parameter in the j1 st row information in the same operation list; />

Representing the actual value of the i1 st operating parameter in the j1 st row information in the same operating list; / >

Representing standard values of the i1 st operation parameters in the j1 st row information in the same operation list; n1 represents the number of parameters of the first description of the information of the j1 st row in the same operation list;

screening for satisfaction from a corresponding first set of differences

Constructing a first difference sequence, and acquiring a first difference characteristic of corresponding line information from a sequence-characteristic mapping table;

constructing a second difference set of the column information under the same operation planning point in the same operation list;

wherein ,

a second set of discrepancies representing column information under the j2 nd co-operation planning point in the same playlist; />

A parameter conversion coefficient representing the ith 2 operating parameters in the information listed under the jth 2 co-operating planning point in the same operation list; />

Removing delays from the list of information representing the j2 nd co-operation planning point in the same operation list

The actual value of the ith 2 operation parameters after the corresponding information; />

Representing standard values of the ith 2 operation parameters in the information under the jth 2 same operation planning points in the same operation list; n2 represents the total number of service operation blocks and is consistent with the number of operation parameters contained in the column information; />

Indicating whether the corresponding business task is delayed to be executed or not in the process of actually monitoring the task operation process, if so, the business task is blocked >

=t; otherwise, go (L)>

=0；/>

Representation pair->

Is a rounding symbol of (2); />

Removing from the list of information representing the j2 nd co-operation planning point in the same operation listDelay->

The actual value of the (i < 2+ > 1 th) operation parameter after the corresponding information;

screening for satisfaction from the corresponding second set of differences

Constructing a second difference sequence, and acquiring a second difference characteristic corresponding to the list information under the same operation planning point from a sequence-characteristic mapping table;

and acquiring corresponding characteristic information based on the first difference characteristic and the second difference characteristic.

Preferably, the acquiring the service operation list consistent with the feature information from the information-display mapping database includes:

according to the first difference characteristic of each service operation block in the same network service, matching to obtain a corresponding first exhibition factor from a block type-difference-exhibition mapping database;

according to the second difference characteristics of all service operation blocks in the same network service based on the same planning time point, matching to obtain corresponding second exhibition factors from the working condition-difference-exhibition mapping database;

comparing each first exhibition factor with the first standard factor, and each second exhibition factor with the second standard factor to obtain a service operation list of the same network service, wherein the service operation list comprises operation comparison curves of the same service operation block and operation comparison curves of all the service operation blocks at different planning time points.

Preferably, determining a service access period and an access key time point in the access period of the corresponding network service according to the access information of the allowed access party for each network service, and constructing a service access list, including:

inputting access information of a corresponding allowed access party into an access analysis model, obtaining access frequency p1 of the corresponding allowed access party to the network service, active access effectiveness z1 of a corresponding access time point and feedback effectiveness y1 of related network service, and calculating access importance F of the same allowed access party to the corresponding network service under the corresponding access time point;

wherein pz represents the total access frequency of all permitted access parties to the same network service;

constructing a first access array of the same permitted access party to different network services according to the access importance, and constructing a second access array of different permitted access parties under the same network service;

based on the first access array, calculating to obtain the user access weight of the same allowed access party;

based on the second access array, calculating to obtain the service access weight of the same network service;

according to the service feedback effectiveness obtained after the same permitted access party actively accesses the same network service under the corresponding access time point, comparing and analyzing the service access weight and the user access weight of the same network service, and taking the corresponding access time point as an access key time point if the time point screening condition is met;

And constructing access sub-tables of the same network service at all access key time points, and further constructing and obtaining a service access list.

Preferably, based on the first access array, the user access weight of the same allowed access party is calculated, including:

wherein ,

representing the number of access importance for the jth 3 network services in the corresponding first access array;

representing the number of access importance which is larger than a preset importance for the jth 3 network service in the corresponding first access array; m3 represents the number of network services; m4 represents m 3->

Is satisfied by->

Is a number of (3).

Preferably, based on the second access array, a service access weight of the same network service is calculated, including:

wherein n01 represents the total number of permitted access parties of the same network service;

indicating the access frequency of the ith allowed access party to the same network service; />

Representing the access importance corresponding to the jth access of the ith permitted access party to the same network service; />

Representing the maximum access importance of the ith permitted access party to the same network service; y1 represents the service access weight of the same network service.

Preferably, the service log is parsed to determine a usage scenario set of the corresponding network service, static information and dynamic information under different usage scenarios, and a service personality list of the corresponding network service is constructed based on a determination result, including:

Analyzing and acquiring the dominant use scene of the same network service from the service log;

determining preset dynamic parameters and preset static parameters corresponding to each dominated usage scene according to the scene attribute of each dominated usage scene, and acquiring a first value consistent with the preset dynamic parameters and a second value consistent with the preset static parameters from the service log;

based on the first value and the second value of the same dominated scene, matching to obtain a corresponding personality display sub-table from a personality database;

acquiring a service personality display list based on all personality display sub-tables;

wherein all first values in the same dominated scene are dynamic information and all second values in the same dominated scene are static information.

Preferably, the method includes the steps of sorting the corresponding network services in the same class based on the service operation list, the service access list and the service personality list of all the network services, and performing output recommendation, including:

determining to obtain the display effective information quantity of the corresponding network service according to the first display effective range of the service operation list of the same network service, the second display effective range of the service access list and the third display effective range of the service personality list;

And sorting the sizes of the exhibition effective information volumes related to the similar network services, and outputting and recommending the network service corresponding to the maximum effective information volume.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.

The technical scheme of the invention is further described in detail through the drawings and the embodiments.

Drawings

The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:

FIG. 1 is a flow chart of a data analysis method based on big data in an embodiment of the invention;

FIG. 2 is a block diagram of a first exhibition factor according to an embodiment of the present invention;

fig. 3 is a block diagram of a second exhibition factor according to an embodiment of the present invention.

Detailed Description

The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.

The invention provides a data analysis method based on big data, as shown in figure 1, comprising the following steps:

In this embodiment, the service operation information refers to a pre-allocated task corresponding to a network service, for example, a short video service is jittered, and in the process of uploading a short video, the pre-allocated task is needed: the method comprises the steps of screening pictures to be uploaded, selecting video templates, adding words and music, uploading, selecting keywords to edit information texts, and sending, wherein in the process, the operation process of a task is preset, namely, each subtask in the operation process is realized by depending on a corresponding service operation script in the execution process, and corresponding program codes are preset, wherein the execution code of each subtask is preset, so that corresponding operation standards are provided for different subtasks, a standard array aiming at service operation information is constructed, and although the network service is executed according to the preset codes, certain errors exist in the execution process, so that a corresponding actual array is required to be acquired, and an operation list is obtained through the combination of the actual array and the standard array.

In this embodiment, the operation list is constructed for the service itself, the row information of the operation service refers to the standard operation condition and the actual operation condition under the same subtask, the column information refers to the standard operation condition and the actual operation condition of all the subtasks involved under the same planning time point, the standard operation condition and the actual operation condition are compared and analyzed to obtain the feature information, and the network service refers to the realization of the corresponding service which needs to be ensured by means of the network level, such as the online game service, the short video service, and the like.

In this embodiment, after each piece of line information is analyzed, a calculated value for a line may be obtained, and then, through a corresponding mapping table, a difference feature related to the calculated value retained by the line may be obtained.

In this embodiment, the information-display mapping table includes different feature information and a service operation display table matched with the feature information, so that the service operation display table for the feature information can be obtained effectively.

In this embodiment, the purpose of acquiring the service operation list is to reasonably display service related operation information of a corresponding network service, on one hand, to display sub-task attributes of the network service, and on the other hand, to display possible anomalies of the network service in an operation process, so as to provide a basis for subsequent recommendation, where the service operation list includes operation information of the network service, difference features, and display modes corresponding to the difference features.

In this embodiment, the access permission party refers to an access user to the network service, for example, for a short video uploading function, there may be a plurality of click accesses of users to the short video uploading, which may be regarded as existing access information.

In this embodiment, the service access period may be preset, for example, one day.

In this embodiment, different users may access the same network service at different time points, for example, access of a jittered short video upload service may only enter the upload interface for viewing or enter the upload interface for video editing at different access time points, so that access to the same service may be different, and therefore, an access time key point is determined, and in general, the more complete the access chain of the corresponding access content based on the network service, the more the corresponding time point can be used as the access time key point.

For example, uploading video traffic includes: content 1-content 2-content 3, at this time, time point 1: the service is exited only when content 1 is accessed, and time point 1 is regarded as a non-access time key point, and time point 2: after accessing the content 1, 2, 3, the service is exited and time 2 is considered as the access time key point.

In this embodiment, the service access exhibition table includes access time points of the user to the network service and access content conditions under different access time points, and also includes a saliency representation of access time key points.

In this embodiment, the service log is a list of information generated in the process of using the service, which is obtained by automatically monitoring the running process of the running task by the monitoring tool in the background in the running process of the corresponding running task, that is, in the process of effectively determining the service. For example, in the process of uploading the jittering audio and video, the format, the size and the image content of the uploaded image are determined, the added text content is determined, and the like, so that the log information of the task is captured.

In this embodiment, the usage scenario set refers to a usage scenario set determined by the same network service for different applications, where the network service not only can be used for video uploading on tremble applications, but also can use the same task process for fast handoffs, news headlines, and the like to realize video uploading.

In this embodiment, the service log includes a used scenario of the same service, and values of dynamic parameters and static parameters related to different used scenarios, where the values, static parameters corresponding to the values, and static parameter descriptions constitute static information and dynamic information, the static information and dynamic information in different used scenarios are different, and the values of the related static parameters and dynamic parameters can be directly obtained from the log, where, for example, the dynamic parameters of the short video upload service based on the jittering use scenario are related to the size of the uploaded video capacity and the actual number of texts in the uploaded video, and the static parameters are related to the size range of the uploaded video capacity and the number range of the uploaded video texts, that is, the static parameters are parameters set by default by the system, and the dynamic parameters refer to the variable conditions existing in the running process of the service.

In this embodiment, the personalized service list refers to the dynamic situation of the network service under different Yangtze river, so as to conveniently and effectively know the personalized situation of the service.

In this embodiment, in the process of similar sorting, the service operation list, the service access list and the service personality list are used to determine the effective amount of the corresponding network service by extracting the effective exhibition information related to the three lists under the same network service, so that sorting is convenient, for example:

the effective amount of the network service 1 is y1, the effective amount of the network service 2 is y2, the effective amount of the network service 3 is y3, and the network services 1, 2 and 3 belong to the same type of service, and y1> y3> y2, then the final output recommendation sequence is: network traffic 1 takes precedence over network traffic 3 and network traffic 3 takes precedence over network traffic 2.

The beneficial effects of the technical scheme are as follows: corresponding exhibition tables are respectively constructed from service operation information, service access information and service logs of the network service, so that output recommendation of the same type of network service is realized, the existence value of the network service can be analyzed in multiple aspects, and the experience of a user on related software applications is effectively met.

The invention provides a data analysis method based on big data, which obtains service operation information of each network service and establishes an operation list of the corresponding network service, and comprises the following steps:

In this embodiment, each network service has a service task that exists, and the service tasks are set when the network service is deployed, for example, for a short video service, a relevant process of video uploading can be monitored, that is, a task running process is performed in the video uploading process, for example, for an online game service, a person skill, death, assistance, survival, and the like set by each game person and a corresponding game in the use process of the game process can be monitored.

In this embodiment, the service running script refers to codes related to the corresponding service, the codes corresponding to different services are different, the codes are designed for logic blocks of functions to be implemented in the process of designing, that is, splitting the execution functions corresponding to the codes is performed on the script to obtain service running blocks, that is, logic blocks, for example, character playing skills of the same game character can be used as a logic block, and walking positions of the game character in the process of game operation can be used as a logic block.

In this embodiment, each business tile has its corresponding operating parameters, wherein, for example, character athletic skills for a game character include: skill 1, skill 2, and skill 3, wherein skill 1, skill 2, and skill 3 may be the first descriptions, the first criteria refer to that the output injury of skill 1 is 5, the output injury of skill 2 is 7, the output injury of skill 3 is 9, at this time, each skill has its set output criteria, and the output injury is the corresponding output criteria.

In this embodiment, the array is run: service execution block 1: skill 1-output injury 5 skill 2-output injury 7 skill 3-output injury 9].

In this embodiment, the standard operation array for the same network service is:

wherein, the operation list is obtained by combining the standard operation data and the actual operation array together, and the operation list is obtained by combining the standard operation data and the actual operation array together, as follows:

playlist:

。

the beneficial effects of the technical scheme are as follows: the operation list is obtained by monitoring the actual monitoring result corresponding to the operation process of the corresponding service and carrying out placing processing with the standard operation array, a basis is provided for the follow-up acquisition of the operation exhibition list of the service, and the effective recommended output of the follow-up network service is ensured.

The invention provides a data analysis method based on big data, which carries out row processing and column processing on the operation list to obtain corresponding characteristic information, and comprises the following steps:

wherein ,

Representing the actual value of the i1 st operating parameter in the j1 st row information in the same operating list; />

Screening for satisfaction from a corresponding first set of differences

wherein ,

representing the first of the same playlistj2 second difference sets of the column information under the same operation planning point; />

Indicating whether the corresponding business task is delayed to be executed or not in the process of actually monitoring the task operation process, if so, the business task is blocked>

=t; otherwise, go (L)>

=0；/>

Representation pair->

Is a rounding symbol of (2); />

Removing delay from the list of information representing the j2 nd co-operation planning point in the same operation list >

screening for satisfaction from the corresponding second set of differences

In this embodiment, the difference set of the row information is mainly obtained after comparing standard information and actual information in the same operation block, where the standard information is a standard value set in advance for the operation block, and the actual information is an actual value obtained after the operation block is operated, for example, standard parameters 1, 2, 3 exist in a first row, and actual parameters 1, 2, 3 also exist in the first row, and the standard value and the actual value of the same parameter are respectively compared and analyzed to obtain the existing difference.

In this embodiment, the parameter conversion coefficients are all preset, so as to facilitate the effective conversion of the difference value, so that the difference value meets the standard of the subsequent comparison calculation.

In this embodiment, the actual value may be captured directly during the running of the running task.

In this embodiment, since the parameters related to different running blocks are different, the number of parameters existing in each row may also be different, and the number of parameters of different rows is a variable.

In this embodiment, for example, the first set of differences includes: 0.2,0.3,0.3,0.4, at this time, corresponding to

The value of (2) is 0.3, and at this time, a value greater than 0.3, that is, 0.4 is selected, and then the first main difference is the difference of the parameter r1 corresponding to 0.4, and the first difference sequence is as follows: parameter r1 (0.4)The sequence-feature mapping table includes different sequence combinations and feature differences matched with the sequence combinations, so that the first difference features for the first difference sequence can be directly obtained from the sequence-feature mapping table.

In this embodiment, the second difference set includes the difference between the standard column information and the actual column information at different planning time points, for example, at the standard time point 1, the parameter 11 in the running block 1 and the parameter 21 in the running block 2 start to run, so when the running task is in the process of actually executing, the actual values of the parameter 11 in the running block 1 and the parameter 21 in the running block 2 are obtained at the actual time point 1 corresponding to the standard time point 1, and thus, the calculation is performed, where there is no service delay, that is, the actual time point 1 of the running task in the process of actually executing the standard time point 1 and the actual time point 1 of the running task in the process of actually executing the standard time point are completely corresponding, where no delay is determined, but in the process of actually executing the running task, that is, the execution of the network or application may be delayed, that is, but the service is not actually executed is not started, and thus, the corresponding delay time and the first time point related to the corresponding delay time point are locked are calculated, and the rationality is guaranteed.

In this embodiment, for example, the second set of differences includes: 0.3,0.4,0.5,0.6,0.7, the corresponding average value is 0.5, and the corresponding second main difference is determined by the parameters corresponding to 0.6 and 0.7, and the second difference sequence is as follows: the second difference characteristic corresponding to the same operation planning point is obtained from the sequence-characteristic mapping table at the moment of the operation block 01-parameter r 2-0.6 and the operation block 02-parameter r 3-0.7.

In this embodiment, the feature information is composed of a first difference feature and a second difference feature under all network services.

The beneficial effects of the technical scheme are as follows: by calculating row information and column information of the operation list, a first difference characteristic and a second difference characteristic aiming at the same network service are effectively determined, so that a difference sequence is conveniently constructed, the difference characteristic with the consistent sequence is obtained by matching from a mapping table, a basis is provided for obtaining a follow-up service operation list, and the reliable recommendation of the network service is indirectly improved.

The invention provides a data analysis method based on big data, which obtains a service operation list consistent with the characteristic information from an information-exhibition mapping database, and comprises the following steps:

according to the second difference characteristics of all service operation blocks in the same network service based on the same planning time point, matching to obtain corresponding second exhibition factors from a working condition-difference-exhibition mapping database;

In this embodiment, the block type refers to the operation type of the corresponding service operation block, mainly related to the corresponding operation function, and the different functions correspond to different block types.

In this embodiment, the block type-difference-exhibition mapping database includes the block types of the different service operation blocks, the possible difference features of the different service operation blocks, and the important salient portions of the possible difference features for the different service operation blocks, which are all the salient display conditions of the important salient portions that can be referred to by the first exhibition factor.

In this embodiment, since the operation condition of each standard time point in the standard operation process is different in each network service and is preset, the second exhibition factor can be obtained by matching from the working condition-difference-exhibition mapping database, wherein the working condition-difference-exhibition mapping database is an important salient part including the second difference feature possibly existing in the standard execution condition and the same standard execution condition of different network services at different standard time points, and therefore, the second exhibition factor for the second difference feature can be obtained.

In this embodiment, the display factor is presented for the purpose of effectively displaying the corresponding difference, and the first standard factor refers to displaying in a manner corresponding to the first standard factor in the absence of the difference.

In this embodiment, the display effect of the first standard factor corresponding to the first difference feature 1 is that the standard information corresponding to the first difference feature 1 is displayed normally, the display effect of the first display factor is that the standard information corresponding to the first difference feature 1 is displayed normally, the information of the difference feature part existing in the standard information is displayed in an enlarged manner, as shown in fig. 2, u01 is a corresponding standard display result, u02 is a display result corresponding to the first difference feature, and u03 in u02 is a part needing to be displayed in an enlarged manner, such as a thickening display, so as to obtain the operation ratio poor diagram for the operation block.

In this embodiment, each second exhibition factor is for a corresponding time point, so the second standard factor and the second exhibition factor for the same time point are different for a certain time point, for example, for time points t1, t2 and t3, as shown in fig. 3.

In this embodiment, the information-display map database includes a work condition-difference-display map database and a block type-difference-display map database.

The beneficial effects of the technical scheme are as follows: the business operation list is conveniently constructed and obtained by acquiring the exhibition factors consistent with the first difference characteristics and the exhibition factors consistent with the second difference characteristics.

The invention provides a data analysis method based on big data, which determines the service access period of the corresponding network service and the access key time point in the access period according to the access information of the allowed access party of each network service, and constructs a service access list, comprising the following steps:

inputting the access information of the corresponding allowed access party into an access analysis model, obtaining the access frequency p1 of the corresponding allowed access party to the network service, the active access effectiveness z1 of the corresponding access time point and the feedback effectiveness y1 of the related network service, and calculating the access importance F of the same allowed access party to the corresponding network service under the corresponding access time point;

In this embodiment, the access analysis model is obtained by training samples based on different access information, effective access content in the access information, and service feedback information for the effective access content, and the access frequency is obtained by counting the number of accesses of the same party based on the model, and the active access validity refers to an active effective access condition of the party, for example, the network service includes: content 1-content 2-content 3, and the access validity of this time is calculated only when the access position accesses content 2, so that the access validity=valid access frequency/p 1; the feedback validity refers to the corresponding access success times/p 1 when the access party accesses the network service each time, and the access success times refer to the situation that the access authority set by the network service cannot be matched after the access party accesses the network service, that is, the access authority of the access party cannot be matched, that is, the access is unsuccessful due to insufficient qualification of the access authority of the access party.

In this embodiment, the first access array: [ access importance of visitor 1 to service 1 at time point 1 access importance of visitor 1 to service 2 at time point 1. ];

a second access array: access importance of access party 1 to service 1 at time point 1 access party 2 to service 1 at time point 1.

In this embodiment, the user access weight and the service access weight are used to determine the importance of the corresponding access party and the importance of the same service.

In this embodiment, since the access importance of each acquired time point is used to determine the user access weight and the service access weight, for example, the user weight to be compared corresponding to the service feedback availability of time point 1 is g01, the service weight to be compared is g02, and at this time, if the corresponding user access weight is greater than the user weight to be compared and the service access weight is greater than the service weight to be compared, the corresponding time point corresponding to the service feedback availability is reserved as the access key time point, that is, the user weight to be compared and the service weight to be compared which can acquire the service feedback availability at each time point are obtained by comparing in the availability-service type-execution time point-comparison weight mapping table, and the mapping table includes the execution availability, the execution service type and the related weight at different execution time points, so that the user weight to be compared and the service weight to be compared can be obtained by effective matching.

In this embodiment, after determining the access key time point, an access sub-table for the network service may be constructed, where the access sub-table includes specific inclusion of the access condition at the key time point and general inclusion of the access condition at the non-key time point, that is, more specifically included information than general inclusion.

In this embodiment, the combination of all access sub-tables is the service access list.

The beneficial effects of the technical scheme are as follows: based on analysis of the access information by the model, relevant effective parameters are obtained, further, the access importance under the network service is calculated, the user access weight and the service access weight are calculated through different arrays, and the access key time point is determined by comparing with screening conditions under different time points, so that a reliable basis is provided for obtaining the service access list, and the follow-up effective recommended output is ensured.

The invention provides a data analysis method based on big data, which is based on the first access array and calculates the user access weight of the same allowed access party, and comprises the following steps:

wherein ,

Is satisfied by->

Is a number of (3).

In this embodiment, the preset importance is preset, and the value is generally 0.3.

The beneficial effects of the technical scheme are as follows: and a comparison basis is provided for judging the subsequent screening conditions by calculating the access weight of the user, so that the effectiveness of the subsequent recommendation output is ensured.

The invention provides a data analysis method based on big data, which is based on the second access array to calculate the service access weight of the same network service, and comprises the following steps:

The beneficial effects of the technical scheme are as follows: and by calculating the service access weight, a comparison basis is provided for judging the subsequent screening conditions, so that the effectiveness of the subsequent recommended output is ensured.

The invention provides a data analysis method based on big data, which analyzes the service log, determines to obtain a service scene set, static information and dynamic information under different service scenes of corresponding network services, and constructs a service personality list of the corresponding network services based on the determination result, comprising the following steps:

In this embodiment, the dominant usage scenario refers to an application range in which the network service can be used, and the usage situation of the network service by different software applications can be regarded as the dominant usage scenario.

In this embodiment, the scene attribute refers to an application type of the software application, and parameter descriptions of static parameters and dynamic parameters preset by different application types are different, that is, a preset dynamic parameter and a preset static parameter, and the log includes actual running values of the static parameter and the dynamic parameter, so that a first value consistent with the preset dynamic parameter and a second value consistent with the preset static parameter can be obtained.

In this embodiment, for example, the scene attribute is a video upload service for a fast-handed, where the only preset dynamic parameters for the dominant use scene include parameters 1, 2, and 3, and the preset static parameters include parameters 4 and 5, where the first value a1 of the parameter 1, the first value a2 of the parameter 2, and the first value a2 of the parameter 3 are obtained from the log, and the second value b1 of the parameter 4 and the second value b2 of the parameter 5 are obtained from the log.

In this embodiment, the personality database includes different dominant scenes and different combinations of values in the same dominant scene, so that a matched personality display table may be effectively called from the database, and because the first value and the second value in the different scenes are different, in the matching process, the obtained personality display sub-table highlights certain personality values, for example, in the case that there is an excessive difference between the first value and the second value and the standard value, at this time, the personality factors corresponding to the values with the excessive difference need to be displayed, that is, based on the matched personality display sub-table, or certain static values or dynamic values preset in the personality display sub-table need to be displayed, so that the personalized display is realized, for example, the personalized display is enlarged display, and an effective reference for facilitating subsequent sorting is needed.

The beneficial effects of the technical scheme are as follows: the dominant use scene is determined by analyzing the log, and the sub-personality display sub-table is matched from the database by acquiring a first value and a second value consistent with the scene, so that a basis is provided for effective recommendation of the follow-up service, and the service experience is indirectly improved.

The invention provides a data analysis method based on big data, which is based on a service operation list, a service access list and a service personality list of all network services, carries out similar ordering on the corresponding network services and carries out output recommendation, and comprises the following steps:

In this embodiment, the display valid range refers to the content to be displayed in the corresponding display list, for example, the first display valid range in the service operation list is the display operation condition 1 and the operation condition 2, at this time, the corresponding number is 2, the second display valid range of the service access list is the display service access condition 02, the service access condition 03 and the service access condition 04, at this time, the corresponding number is 3, the third display valid range is the personality condition 09 and 08 to be displayed in the corresponding display list, at this time, the corresponding number is 2, therefore, the display valid information amount of the corresponding network service is 2+3+2=7,

For example, the similar network services include network service 1, network service 2 and network service 3, wherein the effective information amount of the network service 1 is 7, the effective information amount of the network service 2 is 9, the effective information amount of the network service 3 is 3, and at this time, the size sorting result is: network traffic 2> network traffic 1> network traffic 3, output recommendations are made in this order.

The beneficial effects of the technical scheme are as follows: and determining the effective information quantity by determining the effective ranges of different exhibition tables corresponding to each network service, and further realizing effective output recommendation by size sorting.

It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.

Claims

1. A data analysis method based on big data, comprising:

step 5: based on the service operation list, service access list and service personality list of all network services, the corresponding network services are ordered in the same class and output and recommended;

performing row processing and column processing on the operation list to obtain corresponding characteristic information, wherein the method comprises the following steps:

wherein ,

screening for satisfaction from a corresponding first set of differences

wherein ,

Representing corresponding business in the process of actually monitoring the task operation process Whether or not delayed execution of the transaction occurs, if so, < >>

=t; otherwise, go (L)>

=0；/>

Representation pair->

Is a rounding symbol of (2); />

Removing delay from the list of information representing the j2 nd co-operation planning point in the same operation list>

screening for satisfaction from the corresponding second set of differences

2. The big data based data analysis method of claim 1, wherein obtaining service operation information of each network service and establishing an operation list of the corresponding network service comprises:

3. The big data based data analysis method of claim 1, wherein obtaining a business operation list consistent with the characteristic information from an information-to-display mapping database comprises:

4. The big data based data analysis method of claim 1, wherein determining a service access period of each network service and an access key time point in the access period according to access information of an allowed access party for each network service, and constructing a service access list comprises:

5. The big data based data analysis method of claim 4, wherein calculating the user access weight of the same allowed access party based on the first access array comprises:

wherein ,

representing the number of access importance for the jth 3 network services in the corresponding first access array; />

Is satisfied by->

Is a number of (3).

6. The big data based data analysis method of claim 4, wherein calculating the service access weight of the same network service based on the second access array comprises:

7. The data analysis method based on big data according to claim 1, wherein analyzing the service log, determining to obtain a usage scenario set of the corresponding network service, static information and dynamic information under different usage scenarios, and constructing a service personality list of the corresponding network service based on a determination result, includes:

8. The big data based data analysis method of claim 1, wherein the sorting of the corresponding network services in class and the output recommendation are performed based on the service operation list, the service access list, and the service personality list of all network services, comprising: