CN110415053A - A kind of user experience monitoring system and method based on big data - Google Patents
A kind of user experience monitoring system and method based on big data Download PDFInfo
- Publication number
- CN110415053A CN110415053A CN201910741155.3A CN201910741155A CN110415053A CN 110415053 A CN110415053 A CN 110415053A CN 201910741155 A CN201910741155 A CN 201910741155A CN 110415053 A CN110415053 A CN 110415053A
- Authority
- CN
- China
- Prior art keywords
- user experience
- contact
- data
- index
- user
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0202—Market predictions or forecasting for commercial activities
Abstract
The application provides a kind of user experience monitoring system and method based on big data, which includes: data acquisition module, data modeling module, data analysis module；Data acquisition module stores collected data into system database, and clean to collected data for acquiring the data in data source by acquisition mode；Data modeling module calculates the data processing after cleaning for utilizing algorithm；Data analysis module provides a user analysis result and management application for analyzing treated data, and user oriented.This system collects user's public sentiment data of magnanimity by data acquisition module, the algorithm model built by data modeling module, quantify user experience index, unified indicator evaluation system is established in data analysis module, realize that high efficiency, low cost, accurately the user experience of monitoring brand and competing product is horizontal, the strengths and weaknesses of itself is found out, driving enterprises user experience improves work.
Description
Technical field
The present invention relates to field of computer technology more particularly to a kind of user experience monitoring systems and side based on big data
Method.
Background technique
With the extreme enrichment of social goods and materials, consumer has more selections in consumption, can be in conjunction with personal preference, family
The various aspects such as situation are made decision.Therefore, brand quotient wants to allow the product of consumers oneself, must just see clearly their need
The advantages of asking, collect their opinion, finding out itself product/service and disadvantage improve direction to guide, finally win consumption
The public praise of person.
The mode of existing acquisition consumers' opinions mainly has web crawlers, data docking, data to import three kinds.
Wherein, using web crawlers, negative reviews on available public network realize the monitoring to user's public sentiment, in time
Processing problem prevents the diffusion of the state of affairs.
Data docking obtains the data such as the customer complaint in WorkForm System mainly by way of internal interface.Then
Manually every data is paid a return visit.
Data import, when having completion papery investigation under online, after being counted by Excel, and in a manner of importing template,
It imported into enterprises system.
No matter which kind of above-mentioned mode is required to carry out questionnaire investigation if it is desired to quantitatively understanding situation in depth.Generally pass through
Online tool realizes that backstage draws up a questionnaire, questionnaire is distributed to user, user fills in questionnaires, questionnaire is collected on backstage, system statistics point
Analysis.
However, user, when with the product of enterprise, Service Contact, the impression (user experience) generated is sense organ,
Consumers' opinions also shows fragmentation, diversified situation, is difficult quantitative analysis.Meanwhile there is differences for each experience link
Standard, ununified appraisement system, when analysis, is often dotted, not from problem in terms of entire enterprise.
Questionnaire investigation method efficiency is too low, there is: the outstanding problems such as making time length, Expenses Cost height, Finite Samples,
It constrains to the accurate of user experience and furthers investigate.
Specifically,
1. making time is long.Entire questionnaire investigation, comprising: production questionnaire chooses sample, distributes questionnaire, collects questionnaire, counting and ask
The links such as volume, analysis report.Each link is essential, and entire questionnaire investigation time-consuming at least needs 1 month or more.
2. at high cost.Since making time is long, corresponding personnel's investment is also more.One complete investigation needs, user's investigation
The Team Members such as expert, project manager, Data Analyst, interview personnel, at least scale more than 10 people.
3. Finite Samples.Since national areas is wide, it is desirable to cover all types of users, sample is needed throughout one two three four lines
City.But it is limited to time and cost, representative city can only be selected, in proportion sample drawn.And it also wants simultaneous
Multiple competition brands are cared for, the sample size of each brand can be made too small in this way, lead to the inaccuracy of finding.
Summary of the invention
To solve the above problems, the embodiment of the present application provides a kind of user experience monitoring system based on big data, institute
The system of stating includes: data acquisition module, data modeling module, data analysis module；
The data acquisition module arrives collected data storage for acquiring the data in data source by acquisition mode
In system database, and collected data are cleaned；
The data modeling module calculates the data processing after cleaning for utilizing algorithm；
The data analysis module provides a user analysis result and management for analyzing treated data, and user oriented
Using.
Optionally, the acquisition mode is web crawlers, alternatively, data are docked, alternatively, data import；
The data source is external data and/or internal data；
The external data includes following one or more: electric business platform data, forum website data, social media data,
Quality complains data, and user exchanges data；
The internal data includes following one or more: customer service advisory data, after sale complaint data, user's investigational data.
Optionally, the algorithm in the data modeling module includes: that semantic analysis algorithm and the quantization of user experience index are calculated
Method；
The semantic analysis algorithm, specifically includes: Chinese Word Automatic Segmentation, feature extraction algorithm, text classification algorithm, emotion score
Algorithm；
The user experience index quantization algorithm, specifically includes: contact hierarchical algorithms, contact Weight algorithm, contact user experience
Exponentiation algorithm, index weights algorithm, index user experience exponentiation algorithm.
Optionally, the dimension analyzed in the data analysis module includes following one or more: brand, category, type
Number, price, shop, the time, data source；
The function of analyzing in the data analysis module includes following one or more: user experience map, exponential trend refer to
Number radar, region situation, positioning problems, issue management, improvement tracking, automation report, problem early warning；
The user experience map shows user each with enterprise interaction for building unified appraisement system by map
On a contact, direct user experience index；
The user experience map includes: multistage contact, weight, user experience index, user experience index properties, user experience
Index；
It is the smallest experience granularity that any user, which experiences index, by obtaining after carrying out semantic analysis to the comment of product to user
It arrives, and belongs under a final stage contact；
Any contact or any user experience index have weight；
The weight, for describing contact, alternatively, the significance level of user experience index；
User experience index, including contact user experience index and index user experience index；
The contact user experience index is calculated according to contact user experience exponentiation algorithm, for reacting user in correspondence
User experience on contact；
The index user experience index is calculated according to index user experience exponentiation algorithm, for reacting user in correspondence
User experience in index；
Any user, which experiences index, has a user experience index properties, and the user experience index properties is general character index,
Alternatively, non-general character index；
The exponential trend, for showing variation tendency of the user experience index in the first preset time period；
The index radar, it is strong and weak for comparing the user experience index of brand and competing product on each contact and/or index；
The region situation, for showing that user experience index in the heating power distribution situation of default region, obtains each region and uses
The experience situation at family；
Described problem positioning is found the problem in the user experience map for the height by identification user experience index
Index, and deep-cut problem-indicator there are the problem of；
Described problem management, for carrying out the improvement of problem for problem-indicator；
The improvement tracking, for counting the solution situation of each problem-indicator, the corresponding user's body of monitoring problem index
Index is tested, the improvement of user experience is assessed；
The automation report, for pushing the analysis bulletin of user experience according to experience situation in the second preset time period；
Described problem early warning, for passing through predetermined manner feedback problem index according to preset condition.
Optionally, multistage contact is three-level contact in the user experience map；
Level-one contact includes: Brang Awareness, generates demand, and search understands, selects to shop, is bought, service of delivering goods, installation service,
Use product, after-sale service, value-added service；
Second level contact includes: shopping website, social media, purpose purposes, requirement source, customer service consulting, understands product, outside product
It sees, use process, effect impression；
Three-level contact includes: a day cat, Jingdone district, microblogging, forum, appearance, attachment, manipulation, quality, function use feeling；
User experience index includes: brand competitiveness, and in the past using experience, purposes is bought in advertisement, and using object, kith and kin recommend,
Information source, customer service attitude, customer service response speed, customer service is professional, price fluctuation, cost performance, color, moulding, specification, electricity
Source line, shower, knob, key, electric leakage, leak, heating speed, hot water amount；
When parent contact is Brang Awareness, sub- grade contact is shopping website, social media；
When parent contact is generation demand, sub- grade contact is purpose purposes, requirement source；
Parent contact is when selecting to shop, and sub- grade contact is customer service consulting, understands product；
When parent contact is using product, sub- grade contact is product appearance, use process, effect impression；
When parent contact is shopping website, sub- grade contact is day cat, Jingdone district；
When parent contact is social media, sub- grade contact is microblogging, forum；
When parent contact is product appearance, sub- grade contact is appearance, attachment；
When parent contact is use process, sub- grade contact is manipulation, quality；
When parent contact is experienced for effect, sub- grade contact is function use feeling；
When final stage contact is day cat, user experience index is brand competitiveness, in the past using experience, advertisement；
When final stage contact is purpose purposes, user experience index is purchase purposes, uses object；
When final stage contact is requirement source, user experience index is kith and kin's recommendation, information source；
When final stage contact is that customer service is seeked advice from, user experience index is customer service attitude, and customer service response speed, customer service is professional；
Final stage contact is when understanding product, and user experience index is price fluctuation, cost performance；
When final stage contact is appearance, user experience index is color, moulding；
When final stage contact is attachment, user experience index is specification, power supply line, shower；
When final stage contact is manipulation, user experience index is knob, key；
When final stage contact is quality, user experience index is electric leakage, leak；
When final stage contact is function use feeling, user experience index is heating speed, hot water amount；
Shower, knob, key, heating speed, the user experience index properties of hot water amount are non-general character index.
The embodiment of the present application also provides a kind of user experience monitoring method based on big data, the method packet
It includes:
The data in data source are acquired by acquisition mode；
Collected data are subjected to semantic analysis；
It is given a mark according to semantic analysis result to the data；
User experience index is calculated according to score.
Optionally, for collected any data,
It is described that collected data are subjected to semantic analysis, comprising:
Word segmentation processing is carried out to any data using natural language processing method, obtains one or more phrases；
According to obtained all phrases, core phrase is determined；
Determine the part of speech of the core phrase and the semanteme of any data.
Optionally, for any data,
It is described to be given a mark according to semantic analysis result to the data, comprising:
Any data core phrase is pressed into noun, adjective, adverbial word point according to the part of speech of any data core phrase
Class；
Determine that each core phrase owning user in name word class experiences index based on user experience map；
In adjective classification, the adjective for belonging to owning user experience index is determined；
The emotion of any data is determined according to the adjective for belonging to owning user experience index；
The degree of any data is determined according to the core phrase in adverbial word classification；
It is given a mark according to the emotion of any data and the degree of any data to the data.
It is optionally, described that user experience index is calculated according to score, comprising:
The marking result of each user experience index corresponding data is determined based on user experience map；
The user experience index of each user experience index is determined according to the marking result of each user experience index corresponding data；
Determine that each user experience refers to according to the weight of the user experience index of each user experience index and each user experience index
The user experience index of final stage contact belonging to marking；
The affiliated parent touching in each final stage contact is determined according to the weight of the user experience index of each final stage contact and each final stage contact
The user experience index of point；
It repeats and the affiliated parent in contacts at different levels is determined according to the user experience index of contacts at different levels and the weight of contact at different levels
The step of user experience index of contact, until obtaining the user experience index of level-one contact；
Wherein, the weight W1 of any level contact is calculated by following formula:
When any contact is level-one contact, then W1=[user of any level contact refers to number/all level-one contacts
Maximum user refers to several * 10]Amendment；When any contact is non-level-one contact, then W1=[user of any level contact mentions
And the maximum user of all sub- grade contacts refers to several * 10 under the father contact of number/any contact]Amendment；
Wherein, []AmendmentFor correcting process function；
The weight W2 of any user experience index is calculated by following formula:
W2=[user of any user experience index refers to number/any user experience index affiliated final stage contact institute
The maximum user of Consumer's Experience index refers to several * 10]Amendment；
The user experience index I1 of any contact is calculated by following formula:
When any contact is non-final stage contact, then the user experience of the next sub- each contact of grade in I1=any contact refers to
The sum of the weight of the next sub- each contact of grade in weight/any contact of next sub- each contact of grade of any contact described in number *；
When any contact is final stage contact, then the user experience index * institute of the lower each user experience index in I1=any contact
State the sum of the weight of the lower each user experience index in weight/any contact of lower each user experience index of any contact；
The user experience index I2 of any user experience index is calculated by following formula:
I2=；
Wherein, i is the marking result mark that any user experiences index corresponding data.
Optionally, the correcting process function is bracket function, alternatively, determining rank function.
It has the beneficial effect that:
This system collects user's public sentiment data of magnanimity, the algorithm built by data modeling module by data acquisition module
Model quantifies user experience index, establishes unified indicator evaluation system in data analysis module, realize high efficiency, low cost,
Accurately the user experience of monitoring brand and competing product is horizontal, finds out the strengths and weaknesses of itself, and driving enterprises user experience changes
Kind work.
Detailed description of the invention
The specific embodiment of the application is described below with reference to accompanying drawings, in which:
Fig. 1 shows a kind of structural representation of user experience monitoring system based on big data of one embodiment of the application offer
Figure；
Fig. 2 shows the structural representations for another user experience monitoring system based on big data that one embodiment of the application provides
Figure；
Fig. 3 shows a kind of structural schematic diagram of user experience map of one embodiment of the application offer；
Fig. 4 shows a kind of process signal of user experience monitoring method based on big data of one embodiment of the application offer
Figure；
Fig. 5 shows a kind of method flow given a mark according to semantic analysis result to data of one embodiment of the application offer
Schematic diagram；
Fig. 6 shows a kind of schematic diagram of calculation flow of contact weight of one embodiment of the application offer；
Fig. 7 shows a kind of schematic diagram of calculation flow of contact user experience index of one embodiment of the application offer.
Specific embodiment
For user when with the product of enterprise, Service Contact, the impression (user experience) generated is sense organ, Yong Huyi
See and also show fragmentation, diversified situation, is difficult quantitative analysis.Meanwhile each experience link is there is different standards,
Ununified appraisement system, when analysis, are often dotted, not from problem in terms of entire enterprise.Questionnaire investigation method effect
Rate is too low, there is: the outstanding problems such as making time length, Expenses Cost height, Finite Samples are constrained to the accurate of user experience
And it furthers investigate.
Based on this, the present invention provides a kind of user experience monitoring system based on big data, which is one based on big
Data mode monitors system for the full-range user experience of user.Referring to Fig. 1, which includes: data acquisition module, number
According to modeling module, data analysis module.
(acquisition is the abbreviation of data acquisition module in Fig. 2, is modeled as the abbreviation of data modeling module, analyzes and is referring to fig. 2
The abbreviation of data analysis module), modules in the user experience monitoring system provided by the invention based on big data are carried out
It is described in detail.
1, data acquisition module
Data acquisition module, for acquiring the data in data source by acquisition mode, by collected data storage to system
In database, and collected data are cleaned.
Wherein, acquisition mode includes but is not limited to: web crawlers, alternatively, data are docked, alternatively, data import.
Web crawlers.By existing crawler technology, by data (electric business platform, forum website, the social media on public network
Deng), in the database for periodically crawling this system.
Data docking.It is fixed by the data (customer service consulting, after sale complaint etc.) of enterprises by way of data interaction
When be stored in the database of this system.
Data import.By way of importing by hand, external data is imported into the database of this system.
Cleaning data are mainly the rejecting of abnormal data.Due to user's public sentiment data on public network, there can be only a few weight
Again, the case where pouring water, so needing to reject abnormal data.Specific steps are as follows: first determine whether that whether semantic the data are logical
It is suitable, then check whether the data have repeated.Only meet semantic smoothness, and unduplicated data, after just can enter
Continuous modeling processing.And abnormal data, then it can be removed and filter out.
Data source can be the data source for being only external data, may also be only the data source of internal data, can also be
The data source of external data and the data source of internal data.
External data shows as comment/opinion that user delivers in network, such as following one or more: electric business platform
Data, forum website data, social media data, quality complain data, and user exchanges data.
Internal data shows as the opinion that user directly feeds back to enterprise, such as following one or more: customer service consulting
Data, after sale complaint data, user's investigational data.
Data acquisition module is (crawler, docking, importing) in several ways, by enterprise external data and internal data,
It stores in system database, and data is cleaned.
2, data modeling module
Data modeling module calculates the data processing after cleaning for utilizing algorithm.
Algorithm in data modeling module includes: semantic analysis algorithm and user experience index quantization algorithm.
Semantic analysis algorithm, specifically includes: Chinese Word Automatic Segmentation, feature extraction algorithm, text classification algorithm, emotion score
Algorithm.
User experience index quantization algorithm, specifically includes: contact hierarchical algorithms, contact Weight algorithm, contact user experience
Exponentiation algorithm, index weights algorithm, index user experience exponentiation algorithm.
Data modeling module is to be calculated using distinctive algorithm collected data processing.
3, data analysis module
Data analysis module provides a user analysis result and management is answered for analyzing treated data, and user oriented
With.
By data analysis module, family can be used on system interface, check analytical statement, and closed loop is carried out to problem
Management.
The dimension analyzed in data analysis module includes following one or more: brand, category, model, price, shop
Paving, time, data source.
The function of analyzing in data analysis module includes following one or more: user experience map, exponential trend refer to
Number radar, region situation, positioning problems, issue management, improvement tracking, automation report, problem early warning.
1) user experience map, for building unified appraisement system by map, show user with enterprise interaction
On each contact, direct user experience index.
User experience map builds unified appraisement system (coordinate system) by map, show user with enterprise interaction
Each contact on, direct user experience experiences (i.e. user experience index, subsequent to unitedly call " UE index ").
User experience map includes: multistage contact, weight, user experience index, user experience index properties, user experience
Index.
L user experience index
It is the smallest experience granularity that any user, which experiences index, by obtaining after carrying out semantic analysis to the comment of product to user
It arrives, and belongs under a final stage contact.
User experience index is the smallest experience granularity, is belonged to below specific level-one/second level/three-level contact.With
Comment of the family to some product will be grouped under each index after semantic analysis.
L weight
Any contact or any user experience index have weight.
Weight, for describing contact, alternatively, the significance level of user experience index.
Between father contact and sub- contact, terminal contacts and index, can all there be weight.Weight represents sub- contact/index,
Importance in upper level contact can be measured with 1-10.
For the weight of contact, such as level-one contact, second level contact, three-level contact ... ... passes through subjective determination+objective number
According to combination, it is arranged according to importance of the contact in user.
For example, the weight W1 of any level contact is calculated by following formula:
When any contact is level-one contact, then W1=[user of any level contact refers to the maximum user in number/all level-one contacts
Refer to several * 10]Amendment。
When any contact is non-level-one contact, then W1=[user of any level contact refers to number/any contacts father contact
Under the maximum users of all sub- grade contacts refer to several * 10]Amendment。
Wherein, []AmendmentFor correcting process function.Correcting process function can be bracket function, alternatively, determining grade letter
Number, the present embodiment are not defined the specific process content of correcting process function.
User refers to that number can be the quantity for the data for including in the institute's Consumer's Experience index for be under the jurisdiction of any contact,
Or it is under the jurisdiction of the quantity of different user corresponding to the data in institute's Consumer's Experience index of any contact included,
The present embodiment does not refer to that several methods of determination is defined to user.
In specific implementation, implementation process can be as shown in Figure 6.
For the weight of user experience index, combined by subjective determination+objective data, according to user experience index to
The influence degree at family is arranged.
For example, the weight W2 of any user experience index is calculated by following formula:
W2=[user of any user experience index refers to all user's body of the number/any user experience affiliated final stage contact of index
The maximum user for testing index refers to several * 10]Amendment。
For the user experience index of contact, the user experience index equal to its next stage contact is summed by contact weight.
For example, the user experience index I1 of any contact is calculated by following formula:
When any contact be non-final stage contact, then described in the user experience index * of the next sub- each contact of grade in I1=any contact appoint
The sum of the weight of the next sub- each contact of grade in weight/any contact of next sub- each contact of grade of one contact.
When any contact is final stage contact, then the user experience index * institute of the lower each user experience index in I1=any contact
State the sum of the weight of the lower each user experience index in weight/any contact of lower each user experience index of any contact.
In specific implementation, implementation process can be as shown in Figure 7.
Ownership is equal under the index for the user experience index of user experience index, the emotion score of all comments
Weighted average.
For example, the user experience index I2 of any user experience index is calculated by following formula:
I2=。
Wherein, i is the marking result mark that any user experiences index corresponding data.
L user experience index
User experience index, including contact user experience index and index user experience index.
Contact user experience index is calculated according to contact user experience exponentiation algorithm, for reacting user in correspondence
User experience on contact.
Index user experience index is calculated according to index user experience exponentiation algorithm, for reacting user in correspondence
User experience in index.
According to specific user experience exponentiation algorithm, index/contact user experience index can be calculated.What it was calculated
Process can gradually be calculated by bottom to upper layer according to the sequence of " index, three-level contact, second level contact, level-one contact ".Meanwhile
The range of user experience index value, be 1-5/, reflect impression of the user on index/contact and (be discontented with very much, compare
It is discontented, general, satisfied, very satisfied).
L user experience index properties
Any user, which experiences index, has a user experience index properties, and user experience index properties is general character index, alternatively,
Non- general character index.
The index that each category possesses, be largely it is identical, only fraction is that the category is distinctive.For distinctive
Index, referred to as non-general character index.For identical index, referred to as general character index.
Below by taking user experience map shown in Fig. 3 as an example, it is illustrated.
Referring to Fig. 3 comprising three-level contact.Level-one contact is user in life, the main ring being related with enterprise
Section, shares 10.It can include several second level contacts for each level-one contact, they are the refinements for level-one contact.And
Most of second level contact also can include several three-level contacts.For the contact of least significant end, lower can include several indexs, combination
Evaluate the user experience situation of the terminal contacts.
Level-one contact includes: Brang Awareness, generates demand, and search understands, selects to shop, is bought, service of delivering goods, installation clothes
Business, uses product, after-sale service, value-added service.
Second level contact includes: shopping website, social media, purpose purposes, requirement source, customer service consulting, understanding product, production
Product appearance, use process, effect impression.
Three-level contact includes: a day cat, Jingdone district, microblogging, forum, appearance, attachment, manipulation, quality, function use feeling.
User experience index includes: brand competitiveness, and in the past using experience, advertisement buys purposes, uses object, kith and kin
Recommend, information source, customer service attitude, customer service response speed, customer service is professional, price fluctuation, cost performance, color, moulding, explanation
Book, power supply line, shower, knob, key, electric leakage, leak, heating speed, hot water amount.
When parent contact is Brang Awareness, sub- grade contact is shopping website, social media.
When parent contact is generation demand, sub- grade contact is purpose purposes, requirement source.
Parent contact is when selecting to shop, and sub- grade contact is customer service consulting, understands product.
When parent contact is using product, sub- grade contact is product appearance, use process, effect impression.
When parent contact is shopping website, sub- grade contact is day cat, Jingdone district.
When parent contact is social media, sub- grade contact is microblogging, forum.
When parent contact is product appearance, sub- grade contact is appearance, attachment.
When parent contact is use process, sub- grade contact is manipulation, quality.
When parent contact is experienced for effect, sub- grade contact is function use feeling.
When final stage contact is day cat, user experience index is brand competitiveness, in the past using experience, advertisement.
When final stage contact is purpose purposes, user experience index is purchase purposes, uses object.
When final stage contact is requirement source, user experience index is kith and kin's recommendation, information source.
When final stage contact is that customer service is seeked advice from, user experience index is customer service attitude, customer service response speed, customer service profession
Property.
Final stage contact is when understanding product, and user experience index is price fluctuation, cost performance.
When final stage contact is appearance, user experience index is color, moulding.
When final stage contact is attachment, user experience index is specification, power supply line, shower.
When final stage contact is manipulation, user experience index is knob, key.
When final stage contact is quality, user experience index is electric leakage, leak.
When final stage contact is function use feeling, user experience index is heating speed, hot water amount.
Shower, knob, key, heating speed, the user experience index properties of hot water amount are non-general character index.
Number (1-10) in Fig. 3 on arrow represents the index of arrow meaning or the importance (weight) of contact, and 10 represent
Particularly significant, 1 representative is least important.
For example, the weight of shopping website contact is 6, the weight of social media contact is 7, and the weight of purpose purposes contact is
4, the weight of requirement source contact is 7, and the weight that contact is seeked advice from customer service is 7, and the weight for understanding product contact is 8, product appearance
The weight of contact is 6, and the weight of use process contact is 7, and the weight that effect experiences contact is 9.
The weight of its cat contact is 9, and the weight of Jingdone district contact is 9, and the weight of microblogging contact is 6, the weight of forum contact
It is 5, the weight of appearance contact is 8, and the weight of attachment contact is 7, and the weight for manipulating contact is 8, and the weight of quality contact is 7,
The weight of function use feeling contact is 6.
The weight of brand competitiveness user experience index is 10, the use of the weight of experience user experience index is in the past 9, extensively
The weight for accusing user experience index is 6, and the weight of purchase purposes user experience index is 8, experiences index using object user
Weight is 9, and the weight that kith and kin recommended user experiences index is 4, and the weight that information source user experiences index is 5, customer service attitude
The weight of user experience index is 8, and the weight of customer service response speed user experience index is 6, and the professional user experience of customer service refers to
Target weight is 9, and the weight of price fluctuation user experience index is 6, and the weight of cost performance user experience index is 5, and color is used
The weight that index is experienced at family is 8, and the weight of moulding user experience index is 9, and the weight of specification user experience index is 7, electricity
The weight of source line user experience index is 6, and the weight of shower user experience index is 7, and the weight of knob user experience index is
8, the weight that key user experiences index is 7, and the weight of electric leakage user experience index is 6, the weight of leak user experience index
It is 7, the weight of heating speed user experience index is 8, and the weight of hot water amount's user experience index is 7.
Number in Fig. 3 below contact represents contact user experience index, the number under user experience index in square brackets
Represent index user experience index.User experience index (including contact user experience index and index user experience index) is used for
Measure the level of user experience, 1 point to be very dissatisfied, 5 points are very satisfied.
For example, the contact user experience index of Brang Awareness is 4.1, the contact user experience index for generating demand is 4.5,
The contact user experience index that search understands is 4.67, and the contact user experience index selected to shop is 4.78, the contact of purchase
User experience index is 4.56, and the contact user experience index of service of delivering goods is 4.34, and the contact user experience for installing service refers to
Number is 4.67, and the contact user experience index using product is 4.89, and the contact user experience index of after-sale service is 4.78, is increased
The contact user experience index of value service is 4.98.
The contact user experience index of shopping website is 4.56, and the contact user experience index of social media is 3.1, purpose
The contact user experience index of purposes is 3.4, and the contact user experience index of requirement source is 2.4, and the contact of customer service consulting is used
It is 3.4 that index is experienced at family, and the contact user experience index for understanding product is 4.2, and the contact user experience index of product appearance is
4.21, the contact user experience index of use process is 3.54, and the contact user experience index of effect impression is 4.21.
The contact user experience index of its cat is 2.5, and the contact user experience index in Jingdone district is 4.2, and the contact of microblogging is used
It is 3.8 that index is experienced at family, and the contact user experience index of forum is 4.3, and the contact user experience index of appearance is 3.6, attachment
Contact user experience index be 3.9, the contact user experience index of manipulation is 4.8, and the contact user experience index of quality is
3.5, the contact user experience index of function use feeling is 3.6.
The index user experience index of brand competitiveness is 3.4, is using the index user experience index of experience in the past
4.4, the index user experience index of advertisement is 3.7, and the index user experience index for buying purposes is 4.5, uses the finger of object
Marking user experience index is 4.7, and the index user experience index that kith and kin recommend is 3.5, and the index user experience in information source refers to
Number is 4.3, and the index user experience index of customer service attitude is 3.9, and the index user experience index of customer service response speed is 2.6,
The professional index user experience index of customer service is 4.3, and the index user experience index of price fluctuation is 3.6, the finger of cost performance
Marking user experience index is 4.9, and the index user experience index of color is 4.6, and the index user experience index of moulding is 4.3,
The index user experience index of specification is 3.5, and the index user experience index of power supply line is 4.6, the index user's body of shower
Testing index is 3.7, and the index user experience index of knob is 4.2, and the index user experience index of key is 4.5, the finger of electric leakage
Marking user experience index is 4.2, and the index user experience index of leak is 3.7, and the index user experience index of heating speed is
3.5, the index user experience index of hot water amount is 4.2.
Pass through above-mentioned user experience map, so that it may using the technology of big data, analyze the whole network user to different brands/product
The evaluation of class/model goes quantization user experience index value by user experience exponentiation algorithm, to obtain user in each touching
User experience in point/index is horizontal.In addition, can also compare different brands, category, model in each contact/index
User experience index, finds the strengths and weaknesses of itself, accurately finds improved direction.
2) exponential trend
Exponential trend, for showing variation tendency of the user experience index in the first preset time period.
For example, showing the trend that user experience index changes over time within the period.
3) index radar
Index radar, it is strong and weak for comparing the user experience index of brand and competing product on each contact and/or index.
For example, this product and competing product are contrasted, the strong and weak situation of user experience index in each contact/index.
4) region situation
Region situation, for showing that user experience index in the heating power distribution situation of default region, obtains each region user's
Experience situation.
For example, showing the heating power distribution situation in UE index area throughout the country, the experience situation of each local user is obtained.
5) positioning problems
Positioning problems, for the height by identification user experience index, index of finding the problem in user experience map, and
Deep-cut problem-indicator there are the problem of.
For example, by the height of identification user experience index, index of finding the problem in user experience map, and deep-cut
The index there are the problem of, such as the high frequency problem.
6) issue management
Issue management, for carrying out the improvement of problem for problem-indicator.
For example, forming the management process of " finding the problem "-" transparent transmission problem "-" solution " for problem-indicator, realize
The function that creation problem, assignment problem, progress are fed back, the final improvement for promoting problem.
7) improvement tracks
Improvement tracking, for counting the solution situation of each problem-indicator, the corresponding user experience of monitoring problem index refers to
Number, assesses the improvement of user experience.
For example, the solution situation (used time/reason/result) of each problem is counted, and the corresponding UE index of monitoring problem,
Assess the improvement of user experience.
8) automation report
Automation report, for pushing the analysis bulletin of user experience according to experience situation in the second preset time period.
For example, monthly/weekly, according to the experience situation of each department, push the analysis bulletin of user experience.
9) problem early warning
Problem early warning, for passing through predetermined manner feedback problem index according to preset condition.
For example, system can be according to preset condition, by short message/wechat/mail, in time for urgent important problem
It feeds back at responsible person, prompting processing.
Data analysis module is that user oriented provides the part of analysis result and management application.
The user experience based on big data of foregoing description monitors system, and external, internal user is acquired by big data
Data, using user experience map as analysis model, the exponentiation algorithm of building quantization user experience is qualitative, quantitatively track user
Experience situation.
After constructing the above-mentioned user experience monitoring system based on big data, the present invention also provides one kind to be based on above-mentioned base
In the method that the user experience monitoring system of big data carries out the monitoring of the user experience based on big data, referring to fig. 4, this method stream
Journey is as follows:
401, the data in data source are acquired by acquisition mode.
Wherein, acquisition mode includes but is not limited to: web crawlers, alternatively, data are docked, alternatively, data import.
Web crawlers.By existing crawler technology, by data (electric business platform, forum website, the social media on public network
Deng), in the database for periodically crawling this system.
Data docking.It is fixed by the data (customer service consulting, after sale complaint etc.) of enterprises by way of data interaction
When be stored in the database of this system.
Data import.By way of importing by hand, external data is imported into the database of this system.
In addition, also collected data can be stored into system database, and after collected data to acquisition
To data cleaned.
It cleans the rejecting that data are mainly abnormal data.Due to user's public sentiment data on public network, there can be only a few
The case where repeating, pouring water, so needing to reject abnormal data.Specific steps are as follows: first determine whether the data are semantic
Smoothness, then checks whether the data have repeated.Only meet semantic smoothness, and unduplicated data, just can enter
Subsequent modeling processing.And abnormal data, then it can be removed and filter out.
402, collected data are subjected to semantic analysis.
For collected any data, the implementation of step 402 are as follows:
402-1 carries out word segmentation processing to any data using natural language processing method, obtains one or more phrases.
For example, according to natural language processing (NLP), being split into most to collected user data (as commented on, opinion etc.)
Small phrase.For example, user A " this kitchen ventilator noise that yesterday buys is very big ", detachable are as follows: it bought yesterday, this, oil
Smoke machine, noise, very, greatly.
402-2 determines core phrase according to obtained all phrases.
For example, according to after participle as a result, determining core phrase are as follows: noise, very, greatly.
402-3 determines the part of speech of core phrase and the semanteme of any data.
For example, determining the part of speech of core phrase are as follows: noise-noun, very --- and adverbial word is big --- negative adjective.
The semanteme of the data are as follows: noise is very big.
403, it is given a mark according to semantic analysis result to data.
For collected any data, the implementation of step 403 are as follows:
Any data core phrase is pressed noun, adjective, adverbial word classification according to the part of speech of any data core phrase by 403-1.
403-2 determines that each core phrase owning user in name word class experiences index based on user experience map.
403-3 determines the adjective for belonging to owning user experience index in adjective classification.
403-4 determines the emotion of any data according to the adjective for belonging to owning user experience index.
403-5 determines the degree of any data according to the core phrase in adverbial word classification.
403-6 gives a mark to data according to the emotion of any data and the degree of any data.
By taking example shown in fig. 5 as an example, this step carries out data final by ownership index, emotional color, degree size
Marking.Score is 1-5 point, 1 point be it is very poor, 2 points be it is poor, 3 points be it is general, 4 points be it is preferable, 5 points are fine.For example, needle
It is very big to kitchen ventilator noise, it is assessed as obtaining 1 point in " noise " index.
Data format is as shown in table 1:
Table 1
| User | Source | Score | Index | Level-one contact | Second level contact | Three-level contact |
| A | The comment of its cat | 1 point (very big) | Noise | Use product | Use process | Effect performance |
404, user experience index is calculated according to score.
By step 401-403, the data for a certain product can be acquired, and collected data are attributed to a user
Experience index.It can also give a mark simultaneously for the semanteme of each data.
This step calculates the user experience index of the product according to the marking of all data, realizes that process is as follows:
404-1 determines the marking result of each user experience index corresponding data based on user experience map.
Wherein, the user experience in user experience map, that is, user experience monitoring system shown in Fig. 3 based on big data
Map.
For example, according to actual business, the whole process of analog subscriber experience combs out 10 backbone subscriber contacts.Then
It refines decomposition layer by layer to contact again, forms a tree, show as " level-one contact --- second level contact --- three-level touching
(level-one contact has 10 to the hierarchical relationship of point --- index ", and second level contact has 16, and three-level contact has 50, index 454
It is a), and weight is equipped between level.Each contact and index have the user experience index of oneself, measure its user
Experience is horizontal, supports mutually to compare between brand, category, model.
Between each category, there is a large amount of general character index, while there is also the non-general character indexs of oneself a small number of category.
For the user experience index of each contact, by its subordinate contact/index user experience index, according to corresponding
Weight calculation get.Its calculating process is referring to step 404-2 to step 404-5.
404-2 determines the user's body of each user experience index according to the marking result of each user experience index corresponding data
Test index.
Ownership is equal under the index for the user experience index of user experience index, the emotion score of all comments
Weighted average.
The user experience index I2 of any user experience index is calculated by following formula:
I2=
Wherein, i is the marking result mark that any user experiences index corresponding data.
User refers to that number can be the quantity for the data for including in the institute's Consumer's Experience index for be under the jurisdiction of any contact,
Or it is under the jurisdiction of the quantity of different user corresponding to the data in institute's Consumer's Experience index of any contact included,
The present embodiment does not refer to that several methods of determination is defined to user.
For example, the marking result of user experience index corresponding data is 1 point, 2 points, 3 points, 4 points, 5 points, marking result is identified
It is 1,2,3,4,5, marking result is that 1 point of corresponding marking result mark is also 1, and marking result is 2 points of corresponding marking results
Mark is also 2, and marking result is that 3 points of corresponding marking result marks are also 3, and marking result is 4 points of corresponding marking result marks
Knowing also is 4, and marking result is that 5 points of corresponding marking result marks are also 5.
So, user experience index I2=(1*k1+2*k2+3*k3+4*k4+5*k5)/K of any user experience index
Wherein, k1 is that result of giving a mark in the user experience index is 1 point and refers to number；K2 is knot of giving a mark in the user experience index
Fruit is 2 points and refers to number；K3 is that result of giving a mark in the user experience index is 3 points and refers to number；K4 is the user experience index
Middle marking result is 4 points and refers to number；K5 is that result of giving a mark in the user experience index is 5 points and refers to number；K is the user's body
That tests index always refers to number.
404-3 is determined each according to the weight of the user experience index of each user experience index and each user experience index
The user experience index of the affiliated final stage contact of user experience index.
Wherein, the weight of user experience index is combined by subjective determination+objective data, according to user experience index pair
The influence degree of user is arranged.
For example, the weight W2 of any user experience index is calculated by following formula:
W2=[user of any user experience index refers to all user's body of the number/any user experience affiliated final stage contact of index
The maximum user for testing index refers to several * 10]Amendment。
Wherein, []AmendmentFor correcting process function.Correcting process function can be bracket function, alternatively, determining grade letter
Number, the present embodiment are not defined the specific process content of correcting process function.
For example, the weight W2 of any user experience index=[user of any user experience index refers to number/and any use
The maximum in all indexs under the experience same father contact of index of family refers to several * 10]Amendment。
404-4 determines each final stage contact according to the weight of the user experience index of each final stage contact and each final stage contact
The user experience index of affiliated parent contact.
404-5 is repeated and is determined touchings at different levels according to the user experience index of contacts at different levels and the weight of contact at different levels
The step of user experience index of parent contact belonging to point, until obtaining the user experience index of level-one contact.
Wherein, the weight W1 of any level contact is calculated by following formula:
When any contact is level-one contact, then W1=[user of any level contact refers to the maximum user in number/all level-one contacts
Refer to several * 10]Amendment。
When any contact is non-level-one contact, then W1=[user of any level contact refers to number/any contacts father contact
Under the maximum users of all sub- grade contacts refer to several * 10]Amendment。
The user experience index I1 of any contact is calculated by following formula:
When any contact is non-final stage contact, the then any touching of user experience index * of the next sub- each contact of grade in I1=any contact
The sum of the weight of the next sub- each contact of grade in weight/any contact of next sub- each contact of grade of point.
When any contact is final stage contact, then the user experience index * of the lower each user experience index in I1=any contact appoints
The sum of the weight of the lower each user experience index in weight/any contact of lower each user experience index of one contact.
For example, the user experience index of each non-final stage contact, the user experience index equal to its next stage contact presses touching
Point weight summation.As (w1*e1+...+wn*en)/(w1+w2+...+wn)
Wj is the weight of junior contact；Ej be junior contact user experience index, j be junior contact identify, j value for 1 to
N, n are junior contact total quantity.
The above method first passes through semantic analysis algorithm after collected data, is returned according to user experience impression
Class and marking.Then, user experience index quantization algorithm is recycled, the user experience index of contact and index is calculated.
Data of the invention are mainly derived from user comment or customer complaint, after being user's own experience product or servicing
First impression, have very strong authenticity.
And the mode based on big data, it can accomplish daily more new data by crawling data in real time, on the time, it can be at any time
It is horizontal to monitor user experience, finds the problem in time, timeliness is high.
Simultaneously as user comment derives from whole network, the user in area in all parts of the country can be covered, sample size is enough big,
Decrease the cost of many manpower investigations.
Finally, due to have advanced algorithm and system support, the monitoring accuracy of entire user experience and accuracy have very
Strong guarantee, for each enterprise provide efficiently, accurately performance analysis decision tool.
It should be noted that " first ", " second " in the present embodiment and subsequent embodiment are only to distinguish different preset
Period is used, and has no other substantive meanings.
The utility model has the advantages that
By user's public sentiment data of data acquisition module collection magnanimity, the algorithm model built by data modeling module,
Quantify user experience index, establish unified indicator evaluation system in data analysis module, realizes high efficiency, low cost, high-precision
The user experience of degree ground monitoring brand and competing product is horizontal, finds out the strengths and weaknesses of itself, and driving enterprises user experience improves work
Make.
Claims (10)
1. a kind of user experience based on big data monitors system, which is characterized in that the system comprises: data acquisition module,
Data modeling module, data analysis module；
The data acquisition module arrives collected data storage for acquiring the data in data source by acquisition mode
In system database, and collected data are cleaned；
The data modeling module calculates the data processing after cleaning for utilizing algorithm；
The data analysis module provides a user analysis result and management for analyzing treated data, and user oriented
Using.
2. system according to claim 1, which is characterized in that the acquisition mode is web crawlers, alternatively, data pair
It connects, alternatively, data import；
The data source is external data and/or internal data；
The external data includes following one or more: electric business platform data, forum website data, social media data,
Quality complains data, and user exchanges data；
The internal data includes following one or more: customer service advisory data, after sale complaint data, user's investigational data.
3. system according to claim 2, which is characterized in that the algorithm in the data modeling module includes: semantic point
Analyse algorithm and user experience index quantization algorithm；
The semantic analysis algorithm, specifically includes: Chinese Word Automatic Segmentation, feature extraction algorithm, text classification algorithm, emotion score
Algorithm；
The user experience index quantization algorithm, specifically includes: contact hierarchical algorithms, contact Weight algorithm, contact user experience
Exponentiation algorithm, index weights algorithm, index user experience exponentiation algorithm.
4. system according to claim 3, which is characterized in that the dimension analyzed in the data analysis module includes as follows
It is one or more: brand, category, model, price, shop, time, data source；
The function of analyzing in the data analysis module includes following one or more: user experience map, exponential trend refer to
Number radar, region situation, positioning problems, issue management, improvement tracking, automation report, problem early warning；
The user experience map shows user each with enterprise interaction for building unified appraisement system by map
On a contact, direct user experience index；
The user experience map includes: multistage contact, weight, user experience index, user experience index properties, user experience
Index；
It is the smallest experience granularity that any user, which experiences index, by obtaining after carrying out semantic analysis to the comment of product to user
It arrives, and belongs under a final stage contact；
Any contact or any user experience index have weight；
The weight, for describing contact, alternatively, the significance level of user experience index；
User experience index, including contact user experience index and index user experience index；
The contact user experience index is calculated according to contact user experience exponentiation algorithm, for reacting user in correspondence
User experience on contact；
The index user experience index is calculated according to index user experience exponentiation algorithm, for reacting user in correspondence
User experience in index；
Any user, which experiences index, has a user experience index properties, and the user experience index properties is general character index,
Alternatively, non-general character index；
The exponential trend, for showing variation tendency of the user experience index in the first preset time period；
The index radar, it is strong and weak for comparing the user experience index of brand and competing product on each contact and/or index；
The region situation, for showing that user experience index in the heating power distribution situation of default region, obtains each region and uses
The experience situation at family；
Described problem positioning is found the problem in the user experience map for the height by identification user experience index
Index, and deep-cut problem-indicator there are the problem of；
Described problem management, for carrying out the improvement of problem for problem-indicator；
The improvement tracking, for counting the solution situation of each problem-indicator, the corresponding user's body of monitoring problem index
Index is tested, the improvement of user experience is assessed；
The automation report, for pushing the analysis bulletin of user experience according to experience situation in the second preset time period；
Described problem early warning, for passing through predetermined manner feedback problem index according to preset condition.
5. system according to claim 4, which is characterized in that multistage contact is three-level touching in the user experience map
Point；
Level-one contact includes: Brang Awareness, generates demand, and search understands, selects to shop, is bought, service of delivering goods, installation service,
Use product, after-sale service, value-added service；
Second level contact includes: shopping website, social media, purpose purposes, requirement source, customer service consulting, understands product, outside product
It sees, use process, effect impression；
Three-level contact includes: a day cat, Jingdone district, microblogging, forum, appearance, attachment, manipulation, quality, function use feeling；
User experience index includes: brand competitiveness, and in the past using experience, purposes is bought in advertisement, and using object, kith and kin recommend,
Information source, customer service attitude, customer service response speed, customer service is professional, price fluctuation, cost performance, color, moulding, specification, electricity
Source line, shower, knob, key, electric leakage, leak, heating speed, hot water amount；
When parent contact is Brang Awareness, sub- grade contact is shopping website, social media；
When parent contact is generation demand, sub- grade contact is purpose purposes, requirement source；
Parent contact is when selecting to shop, and sub- grade contact is customer service consulting, understands product；
When parent contact is using product, sub- grade contact is product appearance, use process, effect impression；
When parent contact is shopping website, sub- grade contact is day cat, Jingdone district；
When parent contact is social media, sub- grade contact is microblogging, forum；
When parent contact is product appearance, sub- grade contact is appearance, attachment；
When parent contact is use process, sub- grade contact is manipulation, quality；
When parent contact is experienced for effect, sub- grade contact is function use feeling；
When final stage contact is day cat, user experience index is brand competitiveness, in the past using experience, advertisement；
When final stage contact is purpose purposes, user experience index is purchase purposes, uses object；
When final stage contact is requirement source, user experience index is kith and kin's recommendation, information source；
When final stage contact is that customer service is seeked advice from, user experience index is customer service attitude, and customer service response speed, customer service is professional；
Final stage contact is when understanding product, and user experience index is price fluctuation, cost performance；
When final stage contact is appearance, user experience index is color, moulding；
When final stage contact is attachment, user experience index is specification, power supply line, shower；
When final stage contact is manipulation, user experience index is knob, key；
When final stage contact is quality, user experience index is electric leakage, leak；
When final stage contact is function use feeling, user experience index is heating speed, hot water amount；
Shower, knob, key, heating speed, the user experience index properties of hot water amount are non-general character index.
6. a kind of user experience monitoring method based on big data, which is characterized in that the described method includes:
The data in data source are acquired by acquisition mode；
Collected data are subjected to semantic analysis；
It is given a mark according to semantic analysis result to the data；
User experience index is calculated according to score.
7. according to the method described in claim 6, it is characterized in that, be directed to collected any data,
It is described that collected data are subjected to semantic analysis, comprising:
Word segmentation processing is carried out to any data using natural language processing method, obtains one or more phrases；
According to obtained all phrases, core phrase is determined；
Determine the part of speech of the core phrase and the semanteme of any data.
8. the method according to the description of claim 7 is characterized in that for any data,
It is described to be given a mark according to semantic analysis result to the data, comprising:
Any data core phrase is pressed into noun, adjective, adverbial word point according to the part of speech of any data core phrase
Class；
Determine that each core phrase owning user in name word class experiences index based on user experience map；
In adjective classification, the adjective for belonging to owning user experience index is determined；
The emotion of any data is determined according to the adjective for belonging to owning user experience index；
The degree of any data is determined according to the core phrase in adverbial word classification；
It is given a mark according to the emotion of any data and the degree of any data to the data.
9. according to the method described in claim 8, it is characterized in that, described calculate user experience index according to score, comprising:
The marking result of each user experience index corresponding data is determined based on user experience map；
The user experience index of each user experience index is determined according to the marking result of each user experience index corresponding data；
Determine that each user experience refers to according to the weight of the user experience index of each user experience index and each user experience index
The user experience index of final stage contact belonging to marking；
The affiliated parent touching in each final stage contact is determined according to the weight of the user experience index of each final stage contact and each final stage contact
The user experience index of point；
It repeats and the affiliated parent in contacts at different levels is determined according to the user experience index of contacts at different levels and the weight of contact at different levels
The step of user experience index of contact, until obtaining the user experience index of level-one contact；
Wherein, the weight W1 of any level contact is calculated by following formula:
When any contact is level-one contact, then W1=[user of any level contact refers to number/all level-one contacts
Maximum user refers to several * 10]Amendment；When any contact is non-level-one contact, then W1=[user of any level contact mentions
And the maximum user of all sub- grade contacts refers to several * 10 under the father contact of number/any contact]Amendment；
Wherein, []AmendmentFor correcting process function；
The weight W2 of any user experience index is calculated by following formula:
W2=[user of any user experience index refers to number/any user experience index affiliated final stage contact institute
The maximum user of Consumer's Experience index refers to several * 10]Amendment；
The user experience index I1 of any contact is calculated by following formula:
When any contact is non-final stage contact, then the user experience of the next sub- each contact of grade in I1=any contact refers to
The sum of the weight of the next sub- each contact of grade in weight/any contact of next sub- each contact of grade of any contact described in number *；
When any contact is final stage contact, then the user experience index * institute of the lower each user experience index in I1=any contact
State the sum of the weight of the lower each user experience index in weight/any contact of lower each user experience index of any contact；
The user experience index I2 of any user experience index is calculated by following formula:
I2=
Wherein, i is the marking result mark that any user experiences index corresponding data.
10. according to the method described in claim 9, it is characterized in that, the correcting process function is bracket function, alternatively, sentencing
Determine rank function.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910741155.3A CN110415053A (en) | 2019-08-12 | 2019-08-12 | A kind of user experience monitoring system and method based on big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910741155.3A CN110415053A (en) | 2019-08-12 | 2019-08-12 | A kind of user experience monitoring system and method based on big data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110415053A true CN110415053A (en) | 2019-11-05 |
Family
ID=68367111
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910741155.3A Pending CN110415053A (en) | 2019-08-12 | 2019-08-12 | A kind of user experience monitoring system and method based on big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110415053A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111522950A (en) * | 2020-04-26 | 2020-08-11 | 成都思维世纪科技有限责任公司 | Rapid identification system for unstructured massive text sensitive data |
| CN112053080A (en) * | 2020-09-15 | 2020-12-08 | 上海唐硕信息科技有限公司 | Brand scoring method based on user experience perception |
| CN112801721A (en) * | 2021-04-13 | 2021-05-14 | 腾讯科技（深圳）有限公司 | Information processing method, information processing device, electronic equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102143507A (en) * | 2010-11-23 | 2011-08-03 | 北京中创信测科技股份有限公司 | Method and system for monitoring service quality, and analytical method and system therefor |
| CN104252679A (en) * | 2013-06-30 | 2014-12-31 | 北京百度网讯科技有限公司 | Construction method and system of brand advertisement evaluation system |
| CN107018004A (en) * | 2016-01-28 | 2017-08-04 | 中国移动通信集团福建有限公司 | User satisfaction management system and method |
| CN107578161A (en) * | 2017-08-30 | 2018-01-12 | 咪咕文化科技有限公司 | A kind of product testing method, apparatus and storage medium |
| CN109559162A (en) * | 2018-11-16 | 2019-04-02 | 广州知了科技有限公司 | A method of automatically generating user experience map |
-
2019
- 2019-08-12 CN CN201910741155.3A patent/CN110415053A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102143507A (en) * | 2010-11-23 | 2011-08-03 | 北京中创信测科技股份有限公司 | Method and system for monitoring service quality, and analytical method and system therefor |
| CN104252679A (en) * | 2013-06-30 | 2014-12-31 | 北京百度网讯科技有限公司 | Construction method and system of brand advertisement evaluation system |
| CN107018004A (en) * | 2016-01-28 | 2017-08-04 | 中国移动通信集团福建有限公司 | User satisfaction management system and method |
| CN107578161A (en) * | 2017-08-30 | 2018-01-12 | 咪咕文化科技有限公司 | A kind of product testing method, apparatus and storage medium |
| CN109559162A (en) * | 2018-11-16 | 2019-04-02 | 广州知了科技有限公司 | A method of automatically generating user experience map |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111522950A (en) * | 2020-04-26 | 2020-08-11 | 成都思维世纪科技有限责任公司 | Rapid identification system for unstructured massive text sensitive data |
| CN111522950B (en) * | 2020-04-26 | 2023-06-27 | 成都思维世纪科技有限责任公司 | Rapid identification system for unstructured massive text sensitive data |
| CN112053080A (en) * | 2020-09-15 | 2020-12-08 | 上海唐硕信息科技有限公司 | Brand scoring method based on user experience perception |
| CN112801721A (en) * | 2021-04-13 | 2021-05-14 | 腾讯科技（深圳）有限公司 | Information processing method, information processing device, electronic equipment and storage medium |
| CN112801721B (en) * | 2021-04-13 | 2021-08-10 | 腾讯科技（深圳）有限公司 | Information processing method, information processing device, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Guine et al. | Life cycle assessment | |
| CN103164474B (en) | A kind of method that data service is analyzed | |
| Robst | Overeducation and college major: Expanding the definition of mismatch between schooling and jobs | |
| Watson et al. | Return on Investment in Public Relations: A critique of concepts used by practitioners from the perspectives of communication and management sciences | |
| CN107992609A (en) | A kind of complaint tendency determination methods based on Text Classification and decision tree | |
| CN105117422A (en) | Intelligent social network recommender system | |
| CN110415053A (en) | A kind of user experience monitoring system and method based on big data | |
| Siu et al. | A study of the expected adoption of online shopping—the case of Hong Kong | |
| Diez-Vial et al. | Geographical agglomeration as an alternative to vertical integration | |
| CN106570763A (en) | User influence evaluation method and system | |
| Tong et al. | The research of customer loyalty improvement in telecom industry based on NPS data mining | |
| Nadlifatin et al. | Understanding factors influencing traveler’s adoption of travel influencer advertising: an Information Adoption Model approach | |
| Wang et al. | Does lead userness matter for electric vehicle adoption? An integrated perspective of social capital and domain‐specific innovativeness | |
| CN105740434A (en) | Network information scoring method and device | |
| Franceschini et al. | The condition of uniqueness in manufacturing process representation by performance/quality indicators | |
| Alaouir et al. | Factors driving purchase intention for cruelty-free cosmetics: A study of female millennials in Jönköping, Sweden | |
| CN109658296A (en) | A kind of intelligence service for studying abroad platform | |
| CN108509588A (en) | A kind of lawyer's appraisal procedure and recommendation method based on big data | |
| Law et al. | Modeling tourism demand: A decision rules based approach | |
| CN110532374A (en) | The processing method and processing device of insurance information | |
| Nierling et al. | The landscape of crowd work in Germany: An overview of the scientific and public discourse | |
| CN110442794B (en) | Construction method of analyst portrait system | |
| Arantes | Digital marketing and sustainability: a study on consumer perceptions | |
| Nistor | A conceptual model for the use of social media in companies | |
| Xiao et al. | Understanding consumer’s satisfaction to online hotel review systems: quality perception and usability |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |