CN109522511B - Multiple-disk-based interview scoring method - Google Patents

Multiple-disk-based interview scoring method Download PDF

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CN109522511B
CN109522511B CN201811226815.6A CN201811226815A CN109522511B CN 109522511 B CN109522511 B CN 109522511B CN 201811226815 A CN201811226815 A CN 201811226815A CN 109522511 B CN109522511 B CN 109522511B
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similarity
interviewer
vector
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CN109522511A (en
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邹德岳
赵楠
刘鑫
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Dalian University of Technology
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
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Abstract

A face test scoring method based on a compound disk belongs to the technical field of computers. The invention realizes the storage, analysis, elimination and feedback of the face test score by forming application software. The result vector of each interviewer is compared with the average results given by other interviewers in a similarity manner, and whether the results are abnormal or not is detected by adopting a gross error detection method. The invention has the advantages of improving the objectivity of the interview and helping to improve the business quality of interviewers.

Description

Multiple-disk-based interview scoring method
Technical Field
The invention belongs to the technical field of computers, relates to the field of education, particularly relates to the evaluation of interview objectivity, and provides an interview scoring method based on a compound disk.
Background
In the traditional interviewing process, interviewers score independently and calculate average scores to obtain a conclusion. Even if the strategy of removing the highest score or the lowest score is adopted, the cheating phenomenon can be only partially avoided. More common than the phenomenon of fraud is the uneven ability of the interviewer: novices in the interviewer group who are inexperienced do not have sufficient sharp insight on the abilities and personalities of the subjects; there may also be misjudgments that the interviewer is not well aware of the industry in which the interviewer is engaged. Therefore, the interviewer with insufficient capacity needs to be excluded in the interviewing process, and the result is returned to the interviewer to help the interviewer to increase the experience and adapt to the post.
Disclosure of Invention
Aiming at the existing problems, the invention provides a face test scoring method based on a compound disk, which realizes the storage, analysis, elimination and feedback of face test scores by forming application software.
The technical scheme adopted by the invention is as follows:
a face test scoring method based on double-disk compares the similarity of the score vector of each face test officer with the average scores given by other face test officers, and detects whether the scores are abnormal or not. The method specifically comprises the following steps:
(1) for the same test subject a, n trial officers give scores on their scoring terminals, and the scoring terminals upload the scores to a server;
(2) the server records the scores of n testers about m tested items of the same subject, and the matrix S is marked as n ma；
(3) Scoring the 1 st interviewer Sa(1, K) as a sample for investigation, i is 1, where K is 1 to K, and K is the number of scores of the interview;
(4) will SaThe ith row in (1) is excluded, and the remaining rows are averaged column by column to obtain a vector Ei；
(5) Investigation vector EiAnd Sa(i, k) similarity to obtain a similarity parameter LiWhere K is 1 to K, and K is the number of scoring items of the interview;
the similarity calculation method comprises an Euclidean distance calculation method, a cosine similarity algorithm, a method of taking the maximum value after subtracting the absolute value from the alignment, and the like;
(6) changing the value of i, and repeating the steps (4) to (5) until all i are traversed from 1 to n to obtain a reference value L1～LnA composed vector L;
(7) performing gross error detection on all elements in the vector L by adopting a gross error detection means, and detecting whether the result is abnormal, namely detecting whether a person with too small similarity exists;
the detection means comprises threshold judgment, a Leide criterion, a Gibbs criterion, a Dickson criterion or a Romanofsky criterion.
(8) If it is detected that there is really a gross error in L, the detection result is sent to the element LxTo the corresponding secondThe x position facial test organ (x is 1 to n) and the score is removed from the statistical result; if no gross error is detected, the scores of all interviewer officers are counted as the statistical result.
The invention has the beneficial effects that: the invention can improve the objectivity of the interview and can help improve the business quality of interviewers.
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FIG. 1 is a system workflow diagram.
Detailed Description
The present invention is further illustrated by the following specific examples.
The specific implementation process can be carried out according to the following steps:
(1) for the subject a, each interviewer gives scores on a scoring terminal of the interviewer, and the scoring terminal uploads the scores to the server;
(2) the server records the scoring conditions of n testers about m tested items, and the scoring conditions are recorded as n*matrix S of ma；
(3) Scoring the 1 st interviewer Sa(1, k) as a sample for investigation, i.e., let i equal to 1;
(4) will SaThe ith row in (1) is excluded, and the remaining rows are averaged column by column to obtain a vector Ei；
(5) Computing a survey vector E by euclidean distanceiAnd Sa(i, k) similarity to obtain a similarity parameter LiThe calculation formula is
Figure BDA0001836129680000031
(6) Changing the value of i, and repeating the steps 4 to 5 until all i are 1-n and all L are traversed1～LnA composed vector L;
(7) performing gross error detection on all elements in the vector L through threshold judgment, wherein the specific method is to use LiAnd a threshold;
(8) if it is detected that there is really a gross error in L, the detection result is sent to the elementHormone LxThe corresponding x-th trial officer and the score thereof is removed from the statistical result; if no gross error is detected, the scores of all interviewer officers are counted as the statistical result.
The above-mentioned embodiments only express the embodiments of the present invention, but not should be understood as the limitation of the scope of the invention patent, it should be noted that, for those skilled in the art, many variations and modifications can be made without departing from the concept of the present invention, and these all fall into the protection scope of the present invention.

Claims (3)

1. A counter test scoring method based on double-disk is characterized in that the method compares the score vector of each interviewer with the average scores given by other interviewers in similarity and detects whether the scores are abnormal or not; the method comprises the following steps:
(1) for the same test subject a, n trial officers give scores on their scoring terminals, and the scoring terminals upload the scores to a server;
(2) the server records the scoring of m tested items of the same subject by n testers, and the scoring is recorded as n*matrix S of ma；
(3) Scoring the 1 st interviewer Sa(1, K) as a sample for investigation, i is 1, where K is 1 to K, and K is the number of scores of the interview;
(4) will SaThe ith row in (1) is excluded, and the remaining rows are averaged column by column to obtain a vector Ei；
(5) Investigation vector EiAnd Sa(i, k) similarity to obtain a similarity parameter LiWhere K is 1 to K, and K is the number of scoring items of the interview;
(6) changing the value of i, and repeating the steps (4) to (5) until all i are traversed from 1 to n to obtain a reference value L1～LnA composed vector L;
(7) performing gross error detection on all elements in the vector L by adopting a gross error detection means, and detecting whether the result is abnormal, namely detecting whether a person with too small similarity exists;
(8) if it is detected that there is indeed a gross error in L, a detection conclusion is sent to element LxThe corresponding x-th interviewer, x is 1-n, and the score is removed from the statistical result; if no gross error is detected, the scores of all interviewer officers are counted as the statistical result.
2. The replica-based interview scoring method as claimed in claim 1, wherein the similarity calculation method in step (5) comprises an euclidean distance calculation method, a cosine similarity algorithm, and a method of taking the maximum value by subtracting the absolute value from the absolute value.
3. The method of claim 1 or 2, wherein the detecting means of step (7) comprises passing threshold judgment, Leide's criterion, Gibbs criterion, Dickson criterion or Romanofsky criterion.
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CN104504287A (en) * 2015-01-08 2015-04-08 广州列丰信息科技有限公司 Method for remotely monitoring data exception of mobile medical device and server and system thereof
CN107292575A (en) * 2016-03-31 2017-10-24 阿里巴巴集团控股有限公司 Data processing method and device
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主观评价中的评委水平评价模型;梁俊芝等;《重庆工学院学报（自然科学）》;20090331;第23卷(第3期);第89-91页 *
关于评委评分的评价模型;吕书龙等;《福州大学学报(自然科学版)》;20100630;第38卷(第3期);第358-362页 *

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