CN106557410B - User behavior analysis method and apparatus based on artificial intelligence - Google Patents
User behavior analysis method and apparatus based on artificial intelligence Download PDFInfo
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- CN106557410B CN106557410B CN201610941394.XA CN201610941394A CN106557410B CN 106557410 B CN106557410 B CN 106557410B CN 201610941394 A CN201610941394 A CN 201610941394A CN 106557410 B CN106557410 B CN 106557410B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3438—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment monitoring of user actions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3466—Performance evaluation by tracing or monitoring
- G06F11/3476—Data logging
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/258—Data format conversion from or to a database
Abstract
The user behavior analysis method and apparatus based on artificial intelligence that the invention discloses a kind of, wherein method includes: to filter out the log piece segment information for meeting Log Filter condition according to Log Filter condition resolution User action log is preset；User's interaction scenarios are generated according to log segment information simulation；Mark behavior evaluation information corresponding with user's interaction scenarios.This method carries out user behavior analysis by analog subscriber interaction scenarios, improves the efficiency for carrying out user behavior analysis, convenient for being analyzed based on Product Experience product, realizes to the comprehensive of product analysis.
Description
Technical field
The present invention relates to technical field of data processing more particularly to a kind of user behavior analysis methods based on artificial intelligence
And device.
Background technique
Artificial intelligence (Artificial Intelligence), english abbreviation AI.It is research, develop for simulating,
Extend and the theory of the intelligence of extension people, method, a new technological sciences of technology and application system.Artificial intelligence is to calculate
One branch of machine science, it attempts to understand essence of intelligence, and produce it is a kind of new can be in such a way that human intelligence be similar
The intelligence machine made a response, the research in the field include robot, language identification, image recognition, natural language processing and specially
Family's system etc..
In general, the behavior feedback of user has guiding effect to the optimization and performance boost of product, by analyzing user
User behaviors log and user feedback, can help related personnel understand product experience is upper and performance on deficiency and influence face,
To help to analyze the usage scenario and habit of personnel's understanding real user, so that more preferably Product Experience etc. can be brought by producing piece.
In the related technology, user behavior monitoring carries out the analysis of text level in excel table, can not simulate true production
User's interaction scenario of product, analysis efficiency is low, and the period is long.
Summary of the invention
The purpose of the present invention is intended to solve above-mentioned one of technical problem at least to a certain extent.
For this purpose, the first purpose of this invention is to propose a kind of user behavior analysis method based on artificial intelligence, it should
Method carries out user behavior analysis by analog subscriber interaction scenarios, improves the efficiency for carrying out user behavior analysis, is convenient for base
Product is analyzed in Product Experience, is realized to the comprehensive of product analysis.
Second object of the present invention is to propose a kind of user behavior analysis device based on artificial intelligence.
Third object of the present invention is to propose another user behavior analysis device based on artificial intelligence.
Fourth object of the present invention is to propose a kind of non-transitorycomputer readable storage medium.
5th purpose of the invention is proposing a kind of computer program product.
To achieve the goals above, first aspect present invention embodiment proposes a kind of user behavior based on artificial intelligence
Analysis method, comprising the following steps: according to default Log Filter condition resolution User action log, filter out and meet the log
The log piece segment information of screening conditions；User's interaction scenarios are generated according to the log segment information simulation；Label and the use
The corresponding behavior evaluation information of family interaction scenarios.
The user behavior analysis method based on artificial intelligence of the embodiment of the present invention, according to default Log Filter condition resolution
User action log filters out the log piece segment information for meeting Log Filter condition, and is generated according to log segment information simulation
User's interaction scenarios, and then mark behavior evaluation information corresponding with user's interaction scenarios.Pass through analog subscriber interaction field as a result,
Scape carries out user behavior analysis, improves the efficiency for carrying out user behavior analysis, convenient for being divided based on Product Experience product
Analysis is realized to the comprehensive of product analysis.
In addition, the user behavior analysis method based on artificial intelligence of the embodiment of the present invention, also has following additional skill
Art feature:
In one embodiment of the invention, the basis presets Log Filter condition resolution User action log, screening
Meet the log piece segment information of the Log Filter condition out, comprising:
User action log is parsed to obtain and the matched unstructured information of parameter preset；
The unstructured information is converted into structural data, and data directory is established according to the structural data；
According to data directory described in default Log Filter condition query, the log for meeting the Log Filter condition is filtered out
Piece segment information.
It is in one embodiment of the invention, described that user's interaction scenarios are generated according to the log segment information simulation,
Include:
Extract the text interactive information in the log piece segment information；
The link information in the log piece segment information is sent to predetermined system platform；
Receive the picture interactive information corresponding with the link information of the system platform feedback；
User's interaction scenarios are generated according to the text interactive information and picture interactive information simulation.
In one embodiment of the invention, in label behavior evaluation information corresponding with user's interaction scenarios
Later, further includes:
Obtain evaluation label to be checked；
Go out user's interaction scenarios with the evaluation tag match according to the behavior evaluation information sifting；
Regression analysis processing is done according to user's interaction scenarios.
In one embodiment of the invention, further includes:
Data variation trend corresponding with preset index feature or temporal characteristics is shown in system platform.
To achieve the goals above, second aspect of the present invention embodiment proposes a kind of user behavior based on artificial intelligence
Analytical equipment, comprising: screening module, for filtering out and meeting institute according to Log Filter condition resolution User action log is preset
State the log piece segment information of Log Filter condition；Analog module is handed over for generating user according to the log segment information simulation
Mutual scene；Mark module, for marking behavior evaluation information corresponding with user's interaction scenarios.
The user behavior analysis device based on artificial intelligence of the embodiment of the present invention, according to default Log Filter condition resolution
User action log filters out the log piece segment information for meeting Log Filter condition, and is generated according to log segment information simulation
User's interaction scenarios, and then mark behavior evaluation information corresponding with user's interaction scenarios.Pass through analog subscriber interaction field as a result,
Scape carries out user behavior analysis, improves the efficiency for carrying out user behavior analysis, convenient for being divided based on Product Experience product
Analysis is realized to the comprehensive of product analysis.
In addition, the user behavior analysis device based on artificial intelligence of the embodiment of the present invention, also has following additional skill
Art feature:
In one embodiment of the invention, the screening module includes:
Resolution unit obtains and the matched unstructured information of parameter preset for parsing User action log；
Converting unit, for the unstructured information to be converted into structural data；
Unit is established, for establishing data directory according to the structural data；
Screening unit is used for the data directory according to default Log Filter condition query, filters out and meet the log
The log piece segment information of screening conditions.
In one embodiment of the invention, the analog module includes:
Extraction unit, for extracting the text interactive information in the log piece segment information；
Transmission unit, for sending the link information in the log piece segment information to predetermined system platform；
Receiving unit, for receiving the picture interactive information corresponding with the link information of the system platform feedback；
Analogue unit, for generating user's interaction field according to the text interactive information and picture interactive information simulation
Scape.
In one embodiment of the invention, further includes:
Module is obtained, for obtaining evaluation label to be checked；
The screening module is also used to go out the user with the evaluation tag match according to the behavior evaluation information sifting
Interaction scenarios；
Analysis module, for doing regression analysis processing according to user's interaction scenarios.
In one embodiment of the invention, further includes:
Display module, for showing data variation corresponding with preset index feature or temporal characteristics in system platform
Trend.
To achieve the goals above, third aspect present invention embodiment proposes another user's row based on artificial intelligence
For analytical equipment, comprising: processor；
Memory for storage processor executable instruction；
Wherein, the processor is configured to: according to default Log Filter condition resolution User action log, filter out symbol
Close the log piece segment information of the Log Filter condition；User's interaction scenarios are generated according to the log segment information simulation；Mark
Remember behavior evaluation information corresponding with user's interaction scenarios.
To achieve the goals above, fourth aspect present invention embodiment proposes a kind of computer-readable storage of non-transitory
Medium, when the instruction in the storage medium is performed by the processor of mobile terminal, so that mobile terminal is able to carry out one
Kind is used for behavior analysis method, which comprises
According to default Log Filter condition resolution User action log, the log for meeting the Log Filter condition is filtered out
Piece segment information；
User's interaction scenarios are generated according to the log segment information simulation；
Mark behavior evaluation information corresponding with user's interaction scenarios.
To achieve the goals above, fifth aspect present invention embodiment proposes a kind of computer program product, when described
When instruction processing unit in computer program product executes, a kind of user behavior analysis method is executed, which comprises
According to default Log Filter condition resolution User action log, the log for meeting the Log Filter condition is filtered out
Piece segment information；
User's interaction scenarios are generated according to the log segment information simulation；
Mark behavior evaluation information corresponding with user's interaction scenarios.
The additional aspect of the present invention and advantage will be set forth in part in the description, and will partially become from the following description
Obviously, or practice through the invention is recognized.
Detailed description of the invention
Above-mentioned and/or additional aspect and advantage of the invention will become from the following description of the accompanying drawings of embodiments
Obviously and it is readily appreciated that, in which:
Fig. 1 is the flow chart of the user behavior analysis method according to an embodiment of the invention based on artificial intelligence；
Fig. 2 is the scene according to an embodiment of the invention for filtering out and meeting the log piece segment information of Log Filter condition
Schematic diagram；
Fig. 3 is the schematic diagram of a scenario that simulation according to an embodiment of the invention generates user's interaction scenarios；
Fig. 4 (a) is the schematic diagram of a scenario that simulation in accordance with another embodiment of the present invention generates user's interaction scenarios；
Fig. 4 (b) is that the simulation of another embodiment according to the present invention generates the schematic diagram of a scenario of user's interaction scenarios；
Fig. 5 is the flow chart of the user behavior analysis method in accordance with another embodiment of the present invention based on artificial intelligence；
Fig. 6 (a) is that data corresponding with preset index feature or temporal characteristics according to an embodiment of the invention become
Change trend curve figure；
Fig. 6 (b) is data corresponding with preset index feature or temporal characteristics in accordance with another embodiment of the present invention
Change trend curve figure；
Fig. 6 (c) is that data corresponding with preset index feature or temporal characteristics according to an embodiment of the invention become
Change trend report figure；
Fig. 7 is the structural representation of the user behavior analysis device according to an embodiment of the invention based on artificial intelligence
Figure；
Fig. 8 is the structural representation of the user behavior analysis device in accordance with another embodiment of the present invention based on artificial intelligence
Figure；
Fig. 9 is the structural representation of the user behavior analysis device based on artificial intelligence of another embodiment according to the present invention
Figure；
Figure 10 is that the structure of the user behavior analysis device based on artificial intelligence of further embodiment according to the present invention is shown
It is intended to；And
Figure 11 is that the structure of the user behavior analysis device based on artificial intelligence of a still further embodiment according to the present invention is shown
It is intended to.
Specific embodiment
The embodiment of the present invention is described below in detail, examples of the embodiments are shown in the accompanying drawings, wherein from beginning to end
Same or similar label indicates same or similar element or element with the same or similar functions.Below with reference to attached
The embodiment of figure description is exemplary, it is intended to is used to explain the present invention, and is not considered as limiting the invention.
Below with reference to the accompanying drawings the user behavior analysis method and apparatus based on artificial intelligence of the embodiment of the present invention are described.
It is appreciated that can be that the optimization of product and the raising of performance be played more in order to enable the behavior of user feed back
Comprehensive directive function understands the habit used the product by the user so that related personnel can feed back according to the behavior of user, understands and produces
Insufficient and influence face of the product in experience above and in performance, to make improvement for these deficiencies, and can face according to influence
Development function point carries out waiting, the user behavior analysis method based on artificial intelligence that the invention proposes a kind of.
Specifically, in the user behavior analysis method based on artificial intelligence of the embodiment of the present invention, in order to avoid only
By carrying out the analysis of text level in excel table to user behavior, causes user behavior analysis not comprehensive enough, mould can be passed through
User's interaction scenarios under quasi- real scene intuitively analyze product in terms of Product Experience, strategy push and resource.
It is specific as follows:
Fig. 1 is the flow chart of the user behavior analysis method according to an embodiment of the invention based on artificial intelligence.
As shown in Figure 1, the user behavior analysis method based on artificial intelligence of being somebody's turn to do can include:
S110 filters out the day for meeting Log Filter condition according to default Log Filter condition resolution User action log
Master chip segment information.
It is appreciated that having recorded user information (age of user, user's occupation, User ID, user in the user behaviors log of user
Account etc.), user click history, system version, retrieval city, retrieval client id, term, retrieval time, product IDs etc.
Much information, however according to the difference of analysis scene, the information in User action log relevant to present analysis scene is different.
For example, when the use crowd to product analyzes, User action log relevant to present analysis scene
Information is user information etc.；For another example, when the use city to product is analyzed, user relevant to present analysis scene
The information of user behaviors log is retrieval city etc..
Thus, Log Filter condition can be preset, thus in order to according to Log Filter condition resolution user behavior day
Will filters out the log piece segment information for meeting Log Filter condition, to avoid in User action log, with present analysis scene
Unrelated information is analyzed, and causes the analysis efficiency to user behavior not high.
Wherein, above-mentioned log piece segment information may include that the texts such as the term for meeting Log Filter condition, search result are handed over
Mutual information, link information corresponding with the pictorial information of search result, voice messaging etc..
It should be noted that various ways can be used according to default Log Filter item according to the difference of concrete application scene
Part parses User action log, filters out the log piece segment information for meeting Log Filter condition, is exemplified below:
As an example, index is established for the related data in user journal information, thus according to default Log Filter
Condition query data directory, to filter out the log piece segment information for meeting Log Filter condition.
Specifically, presetting parameter relevant to properties of product, such as when the generation of user name, User action log
Between, system version, retrieval city, term, search result etc., and then parse User action log acquisition and matched with parameter preset
Unstructured data.
Further, for the ease of the analysis to User action log, unstructured data is converted into, bivariate table can be used
Structure carrys out the structural data of logical expression realization, and establishes data directory according to structural data.
Wherein, data element of the data directory to instruction structure data, it may include retrieval the date, retrieval client,
City, the vertical class of system etc. are retrieved, meets log sieve in order to filter out according to preset Log Filter condition query data directory
Select the log piece segment information of condition.
For example, as shown in Fig. 2, can be " film " by selecting the vertical class of system, operating system is that logs such as " IOS " are sieved
Select condition, filter out the log piece segment information for meeting Log Filter condition, the system of the log piece segment information hang down class be " film ",
Operating system is " IOS ".
S120 generates user's interaction scenarios according to log segment information simulation.
It specifically,, can be according to day for assessing product based on Product Experience after obtaining log piece segment information
The simulation of master chip segment information generates user's interaction scenarios.
It should be noted that the information type that user's interaction scenarios include is different under different user's interaction scenarios, than
It such as may include text interactive information, picture interactive information, interactive voice information.It, can and according to the difference of concrete application scene
User's interaction scenarios, the letter for including with user's interaction scenarios below are generated according to log segment information simulation in different ways
Type is ceased, to be illustrated for text interactive information and picture interactive information, is exemplified below:
The first example presets system platform, and link information and corresponding picture are stored in system platform
Interactive information.
Specifically, in this example, extracting the text interactive information in log piece segment information, and then flat to predetermined system
Platform sends the link information in log piece segment information, so that predetermined system platform obtains and feeds back figure corresponding with the link information
Piece interactive information, according to text interactive information and picture interactive information, simulation generates user's interaction scenarios.
In this example, for example, as shown in figure 3, can be believed according to the interaction of the text in the log piece segment information of extraction
The picture interactive information corresponding with link information of breath and system platform feedback, simulation generate according to user demand, recommend cold
User's interaction scenarios of door film, user's interaction scenarios reduce the corresponding true interaction scenarios of log piece segment information.
Second of example, in advance in Cloud Server, according to the retrieval time of picture interactive information and client id, storage
Picture interactive information, and then the text interactive information in log segment is extracted, identification text interactive information corresponding retrieval time
And client id, text interactive information corresponding retrieval time and client id are sent to Cloud Server.
In turn, Cloud Server feedback and retrieval time and the matched picture interactive information of client id, in order to according to text
This interactive information and the simulation of picture interactive information generate user's interaction scenarios.
S130 marks behavior evaluation information corresponding with user's interaction scenarios.
Specifically, after analog subscriber interaction scenarios, behavior evaluation information corresponding with user's interaction scenarios is marked, so as to
In product is optimized according to behavior evaluation information, Performance Evaluation etc..Wherein, behavior evaluation information includes the use to product
Family experience, such as accuracy, the evaluation label of satisfaction, search result of user etc..
For example, in user's interaction scenarios as shown in Fig. 4 (a) left figure, due to being " the performance of the Smurfs for retrieval request
Person is some singer ", the search result provided is the film of the Smurfs, it is clear that this time retrieval is not able to satisfy the inspection of user
Rope request, thus as shown in Fig. 4 (a) right figure, marking user satisfaction corresponding with user's interaction scenarios is poor, evaluation label
Accidentally to recall.
For another example, in user's interaction scenarios as shown in Fig. 4 (b) left figure, due to being that " I will see greatly for retrieval request
Piece ", the search result provided are the film of entitled " sheet ", it is clear that this time retrieval is not able to satisfy the retrieval request of user, because
And as shown in Fig. 4 (b) right figure, mark corresponding with user's interaction scenarios user satisfaction be it is poor, to evaluate label be accidentally to recall
Deng.
In conclusion the user behavior analysis method based on artificial intelligence of the embodiment of the present invention, is sieved according to default log
Condition resolution User action log is selected, filters out the log piece segment information for meeting Log Filter condition, and believe according to log segment
Breath simulation generates user's interaction scenarios, and then marks behavior evaluation information corresponding with user's interaction scenarios.Pass through simulation as a result,
User's interaction scenarios carry out user behavior analysis, improve the efficiency for carrying out user behavior analysis, convenient for being based on Product Experience pair
Product is analyzed, and is realized to the comprehensive of product analysis.
Based on above embodiments, in order to more comprehensively illustrate the user behavior based on artificial intelligence of the embodiment of the present invention
Analysis method is illustrated below with reference to the process analyzed according to user behavior product, is described as follows:
Fig. 5 is the flow chart of the user behavior analysis method in accordance with another embodiment of the present invention based on artificial intelligence,
As shown in figure 5, after above-mentioned steps S130, this method further include:
S210 obtains evaluation label to be checked.
S220 goes out user's interaction scenarios with evaluation tag match according to behavior evaluation information sifting.
It specifically,, can be according to analysis demand in order to improve analysis efficiency and accuracy when carrying out performance evaluation to product
Difference, filter out user's interaction scenarios corresponding with current demand.It can obtain to be checked consistent with present analysis scene
Evaluation label, in turn, according to behavior evaluation information sifting go out with evaluation tag match user's interaction scenarios.
For example, if current analysis scene is, the bad case of product is repaired, then inquires evaluation mark to be checked
Label are " accidentally recalling ", to go out user's interaction scenarios with evaluation tag match, including Fig. 4 according to behavior evaluation information sifting
(b) user's interaction scenarios etc. shown in left figure.
S230 does regression analysis processing according to user's interaction scenarios.
Specifically, after obtaining associated user's interaction scenarios, regression analysis processing is done according to user's interaction scenarios, in order to
The corresponding relationship between each variable of current production is understood, in order to which according to the corresponding relationship between different variables, analysis is corresponded to
The Operational Mechanisms of product can repair with completing loophole, perfect in shape and function etc..
In one embodiment of the invention, product is analyzed in order to more intuitive, can also in system platform,
Show corresponding with preset index feature or temporal characteristics data variation trend, so as to contrast product it is online after, front and back spy
It fixes time the details and variation tendency of section corresponding index, the trend of properties of product and Product Experience is analyzed, in order to make
Corresponding decision realizes the optimization to product.
Wherein, preset index feature or it may include page browsing amount, independent pageview, average interaction times, average hand over
The user behaviors core index such as mutual duration, system version distribution, retrieval city, or may include film card clicking rate, news card
The user behavior index that clicking rate, list and common tabs click condition etc. are segmented according to product function, temporal characteristics include
Retrieve date, retrieval specific time point etc..
It should be noted that various ways can be used and show and preset index spy according to the difference of concrete application demand
Sign or the corresponding data variation trend of temporal characteristics, for example can be showed in a manner of cake chart, curve, histogram, report etc., and
The preset index feature that special time period can be showed can also show the preset index feature etc. of reduced time section.
In one embodiment of the invention, as shown in Fig. 6 (a), when preset index feature is that user behavior core refers to
When mark, in system platform in graph form, user's row in presentation time section on July 25th, 18 days 1 July in 2016
For core index, so as to be got information about in the period according to the curve, the specific trend of user behavior core index
Deng.
In one embodiment of the invention, as shown in Fig. 6 (b), when preset index feature is that user behavior core refers to
When mark, in system platform in graph form, presentation time section A (on July 25,18 days to 2016 July in 2016) is and right
Than the user behavior core index in period B (on July 11,4 days to 2016 July in 2016), so that user can be according to bit
The user behavior core index fixed time in section measures the function situation of the online rear product of a new strategy, according to running feelings
Condition optimizes.
In one embodiment of the invention, as shown in Fig. 6 (c), when preset index feature is that user behavior core refers to
When mark, in system platform in the form of statements, presentation time section on July 25,18 days to 2016 July in 2016, when with comparison
Between the page browsing amount of user in section on July 11st, 4 days 1 July in 2016, independent pageview, averagely interactive duration etc. use
Family behavior core index.
In the present embodiment, in order to enable the content of report is intuitive in further detail, in order to comprehensively be divided product
Analysis, as shown in Fig. 6 (c), indices are shown in report works as the earning in a day, value yesterday, designated time period mean value, reduced time section
The detailed index such as mean value.
In conclusion the user behavior analysis method based on artificial intelligence of the embodiment of the present invention, is handed in label and user
After the corresponding behavior evaluation information of mutual scene, evaluation label to be checked is obtained, goes out and comments according to behavior evaluation information sifting
The matched user's interaction scenarios of price card label, do regression analysis processing according to user's interaction scenarios.As a result, based on Product Experience to production
Product are analyzed, convenient for producing, piece carries out perfect in shape and function and performance optimizes.
To achieve the above object, the present invention also proposes a kind of user behavior analysis device based on artificial intelligence.
Fig. 7 is the structural representation of the user behavior analysis device according to an embodiment of the invention based on artificial intelligence
Figure.
As shown in fig. 7, being somebody's turn to do the user behavior analysis device based on artificial intelligence can include: screening module 10, analog module
20 and mark module 30.
Wherein, screening module 10, for filtering out and meeting day according to Log Filter condition resolution User action log is preset
The log piece segment information of will screening conditions.
In one embodiment of the invention, Fig. 8 is the use in accordance with another embodiment of the present invention based on artificial intelligence
The structural schematic diagram of family behavioural analysis device, as shown in figure 8, the screening module 10 includes parsing on the basis of as shown in Figure 7
Unit 11, establishes unit 13 and screening unit 14 at converting unit 12.
Wherein, resolution unit 11 obtain and the matched unstructured information of parameter preset for parsing User action log.
Converting unit 12, for unstructured information to be converted into structural data.
Unit 13 is established, for establishing data directory according to structural data.
Screening unit 14, for filtering out and meeting Log Filter item according to Log Filter condition query data directory is preset
The log piece segment information of part.
Analog module 20, for generating user's interaction scenarios according to log segment information simulation.
In one embodiment of the invention, Fig. 9 is the use based on artificial intelligence of another embodiment according to the present invention
The structural schematic diagram of family behavioural analysis device, as shown in figure 9, analog module 20 includes extracting list on the basis of as shown in Figure 7
Member 21, transmission unit 22, receiving unit 23 and analogue unit 24.
Wherein, extraction unit 21, for extracting the text interactive information in log piece segment information.
Transmission unit 22, for sending the link information in log piece segment information to predetermined system platform.
Receiving unit 23, for receiving the picture interactive information corresponding with link information of system platform feedback.
Analogue unit 24, for generating user's interaction scenarios according to text interactive information and the simulation of picture interactive information.
Mark module 30, for marking behavior evaluation information corresponding with user's interaction scenarios.
It should be noted that the aforementioned explanation to the user behavior analysis method based on artificial intelligence, is also applied for
The user behavior analysis device based on artificial intelligence of the embodiment of the present invention, the use based on artificial intelligence in the embodiment of the present invention
Undisclosed details in family behavioural analysis device, details are not described herein.
In conclusion the user behavior analysis device based on artificial intelligence of the embodiment of the present invention, is sieved according to default log
Condition resolution User action log is selected, filters out the log piece segment information for meeting Log Filter condition, and believe according to log segment
Breath simulation generates user's interaction scenarios, and then marks behavior evaluation information corresponding with user's interaction scenarios.Pass through simulation as a result,
User's interaction scenarios carry out user behavior analysis, improve the efficiency for carrying out user behavior analysis, convenient for being based on Product Experience pair
Product is analyzed, and is realized to the comprehensive of product analysis.
Figure 10 is that the structure of the user behavior analysis device based on artificial intelligence of further embodiment according to the present invention is shown
It is intended to, as shown in Figure 10, on the basis of as shown in Figure 7, the user behavior analysis device based on artificial intelligence further includes obtaining
Module 40 and analysis module 50.
Wherein, module 40 is obtained, for obtaining evaluation label to be checked.
Screening module 10 is also used to go out user's interaction scenarios with evaluation tag match according to behavior evaluation information sifting.
Analysis module 50, for doing regression analysis processing according to user's interaction scenarios.
Figure 11 is that the structure of the user behavior analysis device based on artificial intelligence of a still further embodiment according to the present invention is shown
It is intended to, as shown in figure 11, on the basis of as shown in Figure 7, the user behavior analysis device based on artificial intelligence further includes showing
Module 60.
Wherein, display module 60, it is corresponding with preset index feature or temporal characteristics for being shown in system platform
Data variation trend.
It should be noted that the aforementioned explanation to the user behavior analysis method based on artificial intelligence, is also applied for
The user behavior analysis device based on artificial intelligence of the embodiment of the present invention, the use based on artificial intelligence in the embodiment of the present invention
Undisclosed details in family behavioural analysis device, details are not described herein.
In conclusion the user behavior analysis device based on artificial intelligence of the embodiment of the present invention, is handed in label and user
After the corresponding behavior evaluation information of mutual scene, evaluation label to be checked is obtained, goes out and comments according to behavior evaluation information sifting
The matched user's interaction scenarios of price card label, do regression analysis processing according to user's interaction scenarios.As a result, based on Product Experience to production
Product are analyzed, convenient for producing, piece carries out perfect in shape and function and performance optimizes.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means specific features, structure, material or spy described in conjunction with this embodiment or example
Point is included at least one embodiment or example of the invention.In the present specification, schematic expression of the above terms are not
It must be directed to identical embodiment or example.Moreover, particular features, structures, materials, or characteristics described can be in office
It can be combined in any suitable manner in one or more embodiment or examples.In addition, without conflicting with each other, the skill of this field
Art personnel can tie the feature of different embodiments or examples described in this specification and different embodiments or examples
It closes and combines.
Although the embodiments of the present invention has been shown and described above, it is to be understood that above-described embodiment is example
Property, it is not considered as limiting the invention, those skilled in the art within the scope of the invention can be to above-mentioned
Embodiment is changed, modifies, replacement and variant.
Claims (8)
1. a kind of user behavior analysis method based on artificial intelligence, which comprises the following steps:
According to default Log Filter condition resolution User action log, the log segment for meeting the Log Filter condition is filtered out
Information, wherein the Log Filter condition is determined according to present analysis scene；
Extract the text interactive information in the log piece segment information；
The link information in the log piece segment information is sent to predetermined system platform；
Receive the picture interactive information corresponding with the link information of the system platform feedback；
User's interaction scenarios are generated according to the text interactive information and picture interactive information simulation；
Mark behavior evaluation information corresponding with user's interaction scenarios.
2. the method as described in claim 1, which is characterized in that the basis presets Log Filter condition resolution user behavior day
Will filters out the log piece segment information for meeting the Log Filter condition, comprising:
User action log is parsed to obtain and the matched unstructured information of parameter preset；
The unstructured information is converted into structural data, and data directory is established according to the structural data；
According to data directory described in default Log Filter condition query, the log segment for meeting the Log Filter condition is filtered out
Information.
3. the method as described in claim 1, which is characterized in that in label behavior corresponding with user's interaction scenarios
After evaluation information, further includes:
Obtain evaluation label to be checked；
Go out user's interaction scenarios with the evaluation tag match according to the behavior evaluation information sifting；
Regression analysis processing is done according to user's interaction scenarios.
4. method a method according to any one of claims 1-3, which is characterized in that further include:
Data variation trend corresponding with preset index feature or temporal characteristics is shown in system platform.
5. a kind of user behavior analysis device based on artificial intelligence characterized by comprising
Screening module, for filtering out and meeting the Log Filter according to Log Filter condition resolution User action log is preset
The log piece segment information of condition, wherein the Log Filter condition is determined according to present analysis scene；
Analog module, the analog module include:
Extraction unit, for extracting the text interactive information in the log piece segment information；
Transmission unit, for sending the link information in the log piece segment information to predetermined system platform；
Receiving unit, for receiving the picture interactive information corresponding with the link information of the system platform feedback；
Analogue unit, for generating user's interaction scenarios according to the text interactive information and picture interactive information simulation；
Mark module, for marking behavior evaluation information corresponding with user's interaction scenarios.
6. device as claimed in claim 5, which is characterized in that the screening module includes:
Resolution unit obtains and the matched unstructured information of parameter preset for parsing User action log；
Converting unit, for the unstructured information to be converted into structural data；
Unit is established, for establishing data directory according to the structural data；
Screening unit is used for the data directory according to default Log Filter condition query, filters out and meet the Log Filter
The log piece segment information of condition.
7. device as claimed in claim 5, which is characterized in that further include:
Module is obtained, for obtaining evaluation label to be checked；
The screening module is also used to be gone out according to the behavior evaluation information sifting and interact with the user of the evaluation tag match
Scene；
Analysis module, for doing regression analysis processing according to user's interaction scenarios.
8. the device as described in claim 5-7 is any, which is characterized in that further include:
Display module, for showing that data variation corresponding with preset index feature or temporal characteristics becomes in system platform
Gesture.
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| CN108108284A (en) * | 2017-12-26 | 2018-06-01 | 广东欧珀移动通信有限公司 | Log processing method, device, terminal device and storage medium |
| CN108197013B (en) * | 2017-12-26 | 2022-03-08 | Oppo广东移动通信有限公司 | Log processing method and device, terminal equipment and storage medium |
| CN108153647B (en) * | 2017-12-26 | 2021-08-06 | Oppo广东移动通信有限公司 | Log processing method and device, terminal equipment and storage medium |
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