CN106683689A - Remote evaluation method for language affinity and system - Google Patents
Remote evaluation method for language affinity and system Download PDFInfo
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- CN106683689A CN106683689A CN201710146455.8A CN201710146455A CN106683689A CN 106683689 A CN106683689 A CN 106683689A CN 201710146455 A CN201710146455 A CN 201710146455A CN 106683689 A CN106683689 A CN 106683689A
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- 238000011156 evaluation Methods 0.000 title claims abstract description 9
- 238000012360 testing method Methods 0.000 claims abstract description 66
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- G—PHYSICS
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- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
- G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination
- G10L25/63—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination for estimating an emotional state
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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Abstract
The invention relates to the technical field of communication and discloses a remote evaluation method for language affinity and a system, in order to reduce cost and increase efficiency. The method disclosed by the invention comprises the following steps: setting at least two answer content options in each test question which is set by a server and relating at least two answer mood options to each answer content option; sending an evaluation request of an user to the server by a client so as to acquire a corresponding test question set from the server, supplying an option to the user by playing a voice corresponding to an answer mood option when a mouse of the user is moved to an area corresponding to any answer mood option, and then sending a test feature of the user to the server; adopting a Pearson correlation coefficient of the test feature and standard feature for performing correlation calculation by the server, thereby acquiring a corresponding evaluation result, wherein the test feature used for calculating the Pearson correlation coefficient includes a selection result for answer content options, a selection result for answer mood options and a consistent feature between a distribution feature of each test question answer time and related test question.
Description
Technical field
The present invention relates to communication technical field, more particularly to a kind of long-range assessment method of language affinity and system.
Background technology
Affinity is belonging to earliest a concept of chemical field, refers in particular between a kind of atom and another atom
Associate feature, but inter personal contact field is increasingly being used for now, the friendly gesture that someone has to an other people, generally
Just describe that this people has affinity.Affinity is that metaphor makes one to get close to, be ready the strength of contact.The both sides for having affinity are exactly
There are the both sides that collective strength is represented, this friendly gesture so that mutual cooperation together, has a kind of consciousness of cooperation and tends to meaning
Know, and coefficient strength.
Language is the core index for reflecting people's affinity, and everyone has the used diction having, in each scene,
The difference of the difference of particular content and the content statement tone all can be to the vivid direct correlation of personal affinity.And in job market
In the activity such as recruitment and matchmaking services, generally require to carry out the matching of affinity according to supply and demand both sides, and pass through the language parent that tests and assesses
With the Proper Match that power can preferably promote supply and demand both sides, it is significant.
Traditional language affinity measures typically carry out man-to-man interview by professional person, its exist high cost,
The low problem of efficiency.And the continuous development of the rise and artificial intelligence technology with Intelligent mobile equipment so that by long-range
Mode carries out the test and appraisal of language affinity and possesses condition.
The content of the invention
Present invention aim at disclosing a kind of long-range assessment method of language affinity and system, with reduced cost, effect is improved
Rate.
For achieving the above object, the invention discloses a kind of long-range assessment method of language affinity, including：
At least two answer content options are set in each examination question set by server, and each answer content option is closed
Connection at least two answers tone option；
The telecommunication set up between client and the server by B/S structural modelss is connected；
The client to the server sends user's test and appraisal request to obtain corresponding examination question collection from the server,
And when user's mouse moves to region corresponding to arbitrary answer tone option, play the voice corresponding to the answer tone option
For user's selection, then the test feature of user is sent to into the server；
The server adopts test feature to carry out correlation calculations to draw with the Pearson correlation coefficients of standard feature
Corresponding test and appraisal conclusion：
Wherein, ρx,yFor the Pearson's correlation coefficient for calculating, x and y is that two groups of length for needing calculating dependency are
The array of n, xiAnd yiI-th data respectively in x and y arrays,WithThe meansigma methodss of data respectively in x and y arrays；With
Include in the dependence test feature for calculating Pearson correlation coefficients：The selection result of answer content option, answer tone option
Concordance feature between selection result, the distribution characteristicss of each examination question time for replying and association examination question.
For achieving the above object, invention additionally discloses a kind of long-range evaluation system of language affinity, including based on B/S structures
The client and server of pattern：
The client, for sending user's test and appraisal request to obtain corresponding examination from the server to the server
Topic collection, and when user's mouse moves to region corresponding to arbitrary answer tone option, play corresponding to the answer tone option
Voice for user selection, then the test feature of user is sent to into the server；
The server, for arranging at least two answer content options in set each examination question, and by each answer
Tone option is answered in content options association at least two, and is entered with the Pearson correlation coefficients of standard feature using test feature
Row correlation calculations test and assess accordingly conclusion to draw：
Wherein, ρx,yFor the Pearson's correlation coefficient for calculating, x and y is that two groups of length for needing calculating dependency are
The array of n, xiAnd yiI-th data respectively in x and y arrays,WithThe meansigma methodss of data respectively in x and y arrays；With
Include in the dependence test feature for calculating Pearson correlation coefficients：The selection result of answer content option, answer tone option
Concordance feature between selection result, the distribution characteristicss of each examination question time for replying and association examination question.
The invention has the advantages that：
The test and appraisal of language affinity are realized by long-range mode, user can be logged in anywhere or anytime by client and be taken
Business device to complete dependence test, and adopt test feature and the Pearson correlation coefficients of standard feature to carry out correlation calculations with
Corresponding test and appraisal conclusion is drawn, while also having considered the choosing of the selection result by answer content option, answer tone option
The multidimensional test feature of the concordance feature composition between result, the distribution characteristicss of each examination question time for replying and association examination question is selected,
So that whole process processes and judge speed soon, accuracy rate is high.
Below with reference to accompanying drawings, the present invention is further detailed explanation.
Description of the drawings
The accompanying drawing for constituting the part of the application is used for providing a further understanding of the present invention, the schematic reality of the present invention
Apply example and its illustrate, for explaining the present invention, not constituting inappropriate limitation of the present invention.In the accompanying drawings：
Fig. 1 is the long-range assessment method flow chart of language affinity disclosed in the embodiment of the present invention.
Specific embodiment
Embodiments of the invention are described in detail below in conjunction with accompanying drawing, but the present invention can be defined by the claims
Implement with the multitude of different ways for covering.
Embodiment 1
The embodiment of the present invention discloses a kind of long-range assessment method of language affinity, as shown in figure 1, including：
Step S1, at least two answer content options are set in each examination question set by server, and by each answer
Hold option association at least two and answer tone option.
Step S2, the telecommunication set up between client and server by B/S structural modelss are connected.
Step S3, user end to server send user's test and appraisal request to obtain corresponding examination question collection from server, and
When user's mouse moves to region corresponding to arbitrary answer tone option, play voice corresponding to the answer tone option for
User selects, and then the test feature of user is sent to into server.
Step S4, server adopt the Pearson correlation coefficients of test feature and standard feature to carry out correlation calculations to obtain
Go out corresponding test and appraisal conclusion.In the step, the dependence test feature for calculating Pearson correlation coefficients includes：Answer content is selected
Between the selection result of item, the selection result for answering tone option, the distribution characteristicss of each examination question time for replying and association examination question
Concordance feature.Specifically computing formula is：
Wherein, ρx,yFor the Pearson's correlation coefficient for calculating, x and y is that two groups of length for needing calculating dependency are
The array of n, xiAnd yiI-th data respectively in x and y arrays,WithThe meansigma methodss of data respectively in x and y arrays.It is excellent
Choosing, in the step is specifically calculated, test feature can be carried out data normalization process, will result data by same
Same multi-C vector is indicated under yardstick.
In the present embodiment, " selection result of answer content option " can be considered each particular content choosing for arbitrary examination question
The ground floor assessment indicator of the microcosmic point that item is carried out, " answering the selection result of tone option " can be considered for arbitrary examination question
The second layer assessment indicator of the microcosmic point that each concrete tone option is carried out；" distribution characteristicss of each examination question time for replying " are visual
It is the third layer assessment indicator of the macroscopic aspect replied for whole examination question collection, generally, the Time-distribution of standard should be abundant
The instinct of reflection test user is selected, and generally pursues that the used time is as short as possible and Annual distribution of on each examination question is uniform；" association examination
Concordance feature between topic " can be considered the 4th layer of assessment indicator of the macroscopic aspect replied for whole examination question collection, if together
One test and appraisal user make between associated examination question run counter in the perhaps tone select, then the affinity of explanation test user holds
Easily wave, the verity of related evaluating result leaves a question open, so as to weights of such evaluating result in integral evaluation result can be reduced,
If conversely, a test and appraisal user makes in identical between associated examination question, and perhaps the tone is selected, illustrating to test user's
Affinity has formed attainment, and the trend instinct of related evaluating result with verity, and then can improve such evaluating result whole
Weights in body evaluating result.
When the present embodiment method is applied in the concrete scene hunted for a job, all processes of the test are all carried out in page end,
Test and appraisal can be completed by operations described below：
Step A, job hunter are input into network address connecting test server by the browser in smart machine, then press display screen
Prompting on curtain selects job market session operational scenarios.Preferably, the session operational scenarios storehouse designed by server needs to meet：Session operational scenarios are logical
Cross conversation content differentiation；The type of session operational scenarios is related to job market work；Question and answer simulation job market scene in session operational scenarios.
Step B, server show the examination question collection under the scene according to the selection of job hunter, so that job hunter determines individual
Answer content option and corresponding answer tone option.In specific examination question, optionally, for the language of the side of dialogue scenarios one
Gas and language content, are provided with some key words that may use as the job hunter of response side and are provided with as returning
The different tone that the job hunter of side may use are answered for user's selection.Wherein, for server end session operational scenarios storehouse with
And concrete examination question collection is storable in server end MSSQL data bases, and using sql like language operation is written and read.
Step C, server are analyzed according to the situation of answering of job hunter to its affinity feature.The test analyzed is special
Levy including：The selection result of answer content option, selection result, the distribution characteristicss of each examination question time for replying of answering tone option
And the concordance feature between association examination question, specific analysis mode using test feature and standard feature Pearson's phase relation
Number carries out correlation analysiss.Afterwards, server refers to standard feature and returns the feature survey of display job hunter's affinity to client
Test result.
To sum up, the long-range assessment method of language affinity disclosed in the present embodiment, realizes that language is affine by long-range mode
The test and appraisal of power, user can be to complete dependence test and special using test by accessing server by customer end anywhere or anytime
Levy and carry out correlation calculations with the Pearson correlation coefficients of standard feature to draw corresponding test and appraisal conclusion, while also considering
By the selection result of answer content option, the selection result for answering tone option, the distribution characteristicss of each examination question time for replying and
The multidimensional test feature of the concordance feature composition between association examination question so that whole process processes and judge speed soon, accurately
Rate is high.
Embodiment 2
Corresponding with said method embodiment, the present embodiment discloses a kind of long-range evaluation system of language affinity, including
Client and server based on B/S structural modelss：
Client, for sending user's test and appraisal request to obtain corresponding examination question collection from server to server, and with
When family mouse moves to region corresponding to arbitrary answer tone option, play voice corresponding to the answer tone option for
Family selects, and then the test feature of user is sent to into server；
Server, for arranging at least two answer content options in set each examination question, and by each answer content
Tone option is answered in option association at least two, and carries out phase with the Pearson correlation coefficients of standard feature using test feature
Closing property calculates to draw corresponding test and appraisal conclusion：
Wherein, ρx,yFor the Pearson's correlation coefficient for calculating, x and y is that two groups of length for needing calculating dependency are
The array of n, xiAnd yiI-th data respectively in x and y arrays,WithThe meansigma methodss of data respectively in x and y arrays；With
Include in the dependence test feature for calculating Pearson correlation coefficients：The selection result of answer content option, answer tone option
Concordance feature between selection result, the distribution characteristicss of each examination question time for replying and association examination question.
In the same manner, the long-range evaluation system of language affinity disclosed in the present embodiment, realizes that language is affine by long-range mode
The test and appraisal of power, user can be to complete dependence test and special using test by accessing server by customer end anywhere or anytime
Levy and carry out correlation calculations with the Pearson correlation coefficients of standard feature to draw corresponding test and appraisal conclusion, while also considering
By the selection result of answer content option, the selection result for answering tone option, the distribution characteristicss of each examination question time for replying and
The multidimensional test feature of the concordance feature composition between association examination question so that whole process processes and judge speed soon, accurately
Rate is high.
The preferred embodiments of the present invention are the foregoing is only, the present invention is not limited to, for the skill of this area
For art personnel, the present invention can have various modifications and variations.It is all within the spirit and principles in the present invention, made any repair
Change, equivalent, improvement etc., should be included within the scope of the present invention.
Claims (2)
1. the long-range assessment method of a kind of language affinity, it is characterised in that include：
At least two answer content options are set in each examination question set by server, and by each answer content option associate to
Few two kinds of answers tone option；
The telecommunication set up between client and the server by B/S structural modelss is connected；
The client to the server sends user's test and appraisal request to obtain corresponding examination question collection from the server, and
When user's mouse moves to region corresponding to arbitrary answer tone option, play voice corresponding to the answer tone option for
User selects, and then the test feature of user is sent to into the server；
It is corresponding to draw that the server adopts test feature to carry out correlation calculations to the Pearson correlation coefficients of standard feature
Test and appraisal conclusion：
Wherein, ρx,yFor the Pearson's correlation coefficient for calculating, it is n that x and y is two groups of length for needing to calculate dependency
Array, xiAnd yiI-th data respectively in x and y arrays,WithThe meansigma methodss of data respectively in x and y arrays；For
Calculating the dependence test feature of Pearson correlation coefficients includes：The selection result of answer content option, the choosing for answering tone option
Select the concordance feature between result, the distribution characteristicss of each examination question time for replying and association examination question.
2. the long-range evaluation system of a kind of language affinity, it is characterised in that include the client based on B/S structural modelss and service
Device：
The client, for sending user's test and appraisal request to obtain corresponding examination question from the server to the server
Collection, and when user's mouse moves to region corresponding to arbitrary answer tone option, play corresponding to the answer tone option
Then the test feature of user is sent to the server by voice for user's selection；
The server, for arranging at least two answer content options in set each examination question, and by each answer content
Tone option is answered in option association at least two, and carries out phase with the Pearson correlation coefficients of standard feature using test feature
Closing property calculates to draw corresponding test and appraisal conclusion：
Wherein, ρx,yFor the Pearson's correlation coefficient for calculating, it is n that x and y is two groups of length for needing to calculate dependency
Array, xiAnd yiI-th data respectively in x and y arrays,WithThe meansigma methodss of data respectively in x and y arrays；For
Calculating the dependence test feature of Pearson correlation coefficients includes：The selection result of answer content option, the choosing for answering tone option
Select the concordance feature between result, the distribution characteristicss of each examination question time for replying and association examination question.
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| CN201710146455.8A CN106683689B (en) | 2017-03-13 | 2017-03-13 | The long-range assessment method of language affinity and system |
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| CN201710146455.8A CN106683689B (en) | 2017-03-13 | 2017-03-13 | The long-range assessment method of language affinity and system |
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101315680A (en) * | 2007-05-31 | 2008-12-03 | 中国科学院自动化研究所 | Group qualitative analysis tool based on automatic investigation questionnaire and implementing method thereof |
| US20090112715A1 (en) * | 2007-10-31 | 2009-04-30 | Ryan Steelberg | Engine, system and method for generation of brand affinity content |
| CN103336953A (en) * | 2013-07-05 | 2013-10-02 | 深圳市中视典数字科技有限公司 | Movement judgment method based on body sensing equipment |
| CN105025383A (en) * | 2010-12-23 | 2015-11-04 | Rovi技术公司 | Electronic programming guide (EPG) affinity clusters |
| CN106407446A (en) * | 2016-09-29 | 2017-02-15 | 中科易研（北京）科技股份公司 | Network questionnaire establishment method and device |
-
2017
- 2017-03-13 CN CN201710146455.8A patent/CN106683689B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101315680A (en) * | 2007-05-31 | 2008-12-03 | 中国科学院自动化研究所 | Group qualitative analysis tool based on automatic investigation questionnaire and implementing method thereof |
| US20090112715A1 (en) * | 2007-10-31 | 2009-04-30 | Ryan Steelberg | Engine, system and method for generation of brand affinity content |
| CN105025383A (en) * | 2010-12-23 | 2015-11-04 | Rovi技术公司 | Electronic programming guide (EPG) affinity clusters |
| CN103336953A (en) * | 2013-07-05 | 2013-10-02 | 深圳市中视典数字科技有限公司 | Movement judgment method based on body sensing equipment |
| CN106407446A (en) * | 2016-09-29 | 2017-02-15 | 中科易研（北京）科技股份公司 | Network questionnaire establishment method and device |
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