CN107909097A - The update method and device of sample in sample storehouse - Google Patents

The update method and device of sample in sample storehouse Download PDF

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CN107909097A
CN107909097A CN201711093134.2A CN201711093134A CN107909097A CN 107909097 A CN107909097 A CN 107909097A CN 201711093134 A CN201711093134 A CN 201711093134A CN 107909097 A CN107909097 A CN 107909097A
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sample
rate
value
storehouse
threshold
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CN107909097B (en
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周书恒
祝慧佳
赵智源
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Advanced New Technologies Co Ltd
Advantageous New Technologies Co Ltd
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Alibaba Group Holding Ltd
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    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
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Abstract

This specification embodiment provides the update method and device of sample in a kind of sample storehouse, in sample storehouse in the update method of sample, obtains the sample to be updated to sample storehouse.Calculate the similarity value of the sample and multiple default samples for having added sample label.According to similarity value and multiple threshold values, determine and the corresponding prediction label of each threshold value.To the corresponding prediction label of each threshold value, according to the prediction label and sample label, determine corresponding accuracy rate and recall rate, may thereby determine that out multiple accuracys rate and recall rate.According to definite multiple accuracys rate and recall rate, the Average Accuracy AP of the sample is calculated.If AP meets preset condition, by the Sample Refreshment into sample storehouse.

Description

The update method and device of sample in sample storehouse
Technical field
This specification one or more embodiment is related to sample in field of computer technology, more particularly to a kind of sample storehouse Update method and device.
Background technology
At present, similarity searching has been widely used for the numerous areas such as information retrieval, multimedia and machine vision.Phase The effect searched for like property is mainly based on the quality of sample in sample storehouse, and in conventional art, the quality of sample in sample storehouse Control depend on artificial test and appraisal.Accordingly, it is desirable to provide in a kind of more reliable control sample storehouse the quality of sample side Case.
The content of the invention
This specification one or more embodiment describes the update method and device of sample in a kind of sample storehouse, Ke Yigeng Reliably in control sample storehouse sample quality.
First aspect, there is provided the update method of sample in a kind of sample storehouse, including：
Obtain the first sample to be updated to sample storehouse；
Calculate the similarity value of the first sample and multiple default samples for having added sample label；
According to the similarity value and multiple threshold values, determine and the corresponding prediction label of each threshold value；
To the corresponding prediction label of each threshold value, according to the prediction label and the sample label, determine corresponding Accuracy rate and recall rate, so that it is determined that going out multiple accuracys rate and recall rate；
According to definite multiple accuracys rate and recall rate, the Average Accuracy AP of the first sample is calculated；
If AP meets preset condition, by first sample renewal into the sample storehouse.
Second aspect, there is provided the updating device of sample in a kind of sample storehouse, including：
Acquiring unit, for obtaining the first sample to be updated to sample storehouse；
Computing unit, for calculating the first sample that the acquiring unit obtains and multiple sample labels of having added The similarity value of default sample；
Determination unit, for the similarity value calculated according to the computing unit and multiple threshold values, determines and each A corresponding prediction label of threshold value；
The determination unit, is additionally operable to the corresponding prediction label of each threshold value, according to the prediction label with it is described Sample label, determines corresponding accuracy rate and recall rate, so that it is determined that going out multiple accuracys rate and recall rate；
The computing unit, is additionally operable to the multiple accuracys rate and recall rate determined according to the determination unit, described in calculating The Average Accuracy AP of first sample；
Updating block, when the AP for being calculated when the computing unit meets preset condition, by the first sample Update in the sample storehouse.
The update method and device of sample in the sample storehouse that this specification one or more embodiment provides, obtain to be updated To the sample of sample storehouse.Calculate the similarity value of the sample and multiple default samples for having added sample label.According to similarity Value and multiple threshold values, determine and the corresponding prediction label of each threshold value.To the corresponding prediction label of each threshold value, according to The prediction label and sample label, determine corresponding accuracy rate and recall rate, may thereby determine that out multiple accuracys rate and recall Rate.According to definite multiple accuracys rate and recall rate, the Average Accuracy AP of the sample is calculated.If AP meets preset condition, By the Sample Refreshment into sample storehouse.Thus, it is possible to more reliably in control sample database sample quality.
Brief description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, required use in being described below to embodiment Attached drawing be briefly described, it should be apparent that, drawings in the following description are only some embodiments of the present invention, for this For the those of ordinary skill of field, without creative efforts, it can also be obtained according to these attached drawings other Attached drawing.
Fig. 1 is the application scenarios schematic diagram of the update method of sample in the sample storehouse that this specification one embodiment provides；
Fig. 2 is the update method flow chart of sample in the sample storehouse that this specification one embodiment provides；
Fig. 3 is the update method schematic diagram that this illustrates sample in the sample storehouse that another embodiment provides；
Fig. 4 is the updating device schematic diagram of sample in the sample storehouse that this specification one embodiment provides.
Embodiment
Below in conjunction with the accompanying drawings, the scheme provided this specification is described.
The update method of sample can be applied to field as shown in Figure 1 in the sample storehouse that this specification one embodiment provides In Jing Zhong, Fig. 1, the sample in sample storehouse can be by artificially being collected in advance from the background data base of server.The sample storehouse In sample can have corresponding sample label (e.g., 1 and 0).Specifically, if the sample label of sample is：" 1 ", the then sample This is positive sample；And if the sample label of sample is：" 0 ", then the sample is negative sample.
In Fig. 1, similarity searching system can search for and the most like or most different sample of current sample from sample storehouse This.
Certainly, in practical applications, the update method of sample can also answer in the sample storehouse that this specification embodiment provides For in other scenes.This specification is not construed as limiting this.
Fig. 2 is the update method flow chart of sample in the sample storehouse that this specification one embodiment provides.The method Executive agent can be the equipment with disposal ability：Server either system or device.As shown in Fig. 2, the method has Body can include：
Step 210, the first sample to be updated to sample storehouse is obtained.
First sample herein can be any sample to be updated that will update sample storehouse.
Step 220, first sample and the similarity value of multiple default samples for having added sample label are calculated.
In one implementation, first sample and multiple default samples for having added sample label are calculated in step 220 Similarity value can be implemented by the following steps：
Step A, determines the sampling feature vectors of first sample, and determines the sampling feature vectors of each default sample.
With first sample：For exemplified by B, it can be expressed as：B=(b1,b2,...,bn), then b1,b2,...,bnI.e. For first sample：The sampling feature vectors of B.Above-mentioned n is used for the number for representing the sampling feature vectors of sample B.Further, it is also possible to Assuming that there are m default samples：X1,X2,...,Xm, the m default samples can be expressed as：
Wherein, x1,1,x1,2,...,x1,nTo preset sample：X1N sampling feature vectors, x2,1,x2,2,...,x2,nFor Default sample：X2N sampling feature vectors, and so on.
Step B, according to the sampling feature vectors of first sample and the sampling feature vectors of each default sample, calculates the The distance value of one sample and each default sample.
With i-th of default sample (Xi) exemplified by for, first sample：B and XiDistance value can be expressed as formula：
di=| | Xi-B||2, i=1,2,3 ..., m (formula 1)
Wherein, diFor first sample and the distance value of i-th of default sample, m is the number of default sample.
Step C, value of adjusting the distance are normalized.
Step D, according to the distance value after normalized, determines similarity value.
For exemplified by i-th of distance value to be normalized, the formula of its normalized can be as follows：
Simi=1-di/ 100, i=1,2 ..., m (formula 2)
Wherein, simiFor first sample and the similarity value of i-th of default sample, diFor first sample and i-th of default sample This distance value.
Certainly, in practical applications, first sample and the phase of each default sample can also be calculated in other ways Like angle value, e.g., the different value of first sample and default sample can be calculated.Similarity value is determined according to different value afterwards Deng this specification does not repeat this again.
Step 230, according to similarity value and multiple threshold values, determine and the corresponding prediction label of each threshold value.
Multiple threshold values herein can rule of thumb be set, and in different application scenarios, the plurality of threshold value can be with There is different values.
In addition, above-mentioned prediction label is identical with the definition of above-mentioned sample label, you can with including：" 0 " and " 1 ", this explanation Book does not repeat again herein.
In one implementation, can be by the similarity value of each default sample compared with threshold value, if some is pre- If the similarity value of sample exceedes threshold value, then the prediction label that this can be preset to sample is determined as：" 1 " (or " 0 "), otherwise The prediction label that this can be preset to sample is determined as：" 0 " (or " 1 ").It is understood that sample is preset according to said one The determination mode of this prediction label, it may be determined that go out the prediction label of each default sample.
It should be noted that the setting means (being set as " 1 " or " 0 ") of the prediction label of above-mentioned default sample can root Determined according to the setting means of sample label.
Step 240, to the corresponding prediction label of each threshold value, according to the prediction label and sample label, determine corresponding Accuracy rate and recall rate, so that it is determined that going out multiple accuracys rate and recall rate.
, can be according to the sample of each default sample for exemplified by determining the corresponding accuracy rate of a threshold value and recall rate This label and prediction label, (are denoted as to count the number for the default sample that prediction label is " 1 " and sample label is " 1 "： TP)；And the number for counting the default sample that prediction label is " 1 " and sample label is " 0 " (is denoted as：) and prediction label FP Number for " 0 " and default sample that sample label is " 1 " (is denoted as：FN).Afterwards can be according to formula：TP/ (TP+FP) comes true Accuracy rate is determined, according to formula：TP/ (TP+FN) determines recall rate.
It should be noted that when threshold value is different, the prediction label of each default sample will be different, so that statistics TP, FP and FN will be inconsistent, and the accuracy rate and recall rate thereby determined that out is with regard to inconsistent.Therefore, the standard in this specification True rate and recall rate are corresponding with threshold value.
Above-mentioned steps a to step c is repeated, until determining corresponding with each threshold value accuracy rate and recall rate.
Step 250, according to definite multiple accuracys rate and recall rate, the Average Accuracy AP of first sample is calculated.
In one implementation, after corresponding with multiple threshold values accuracy rate and recall rate is determined, with it is each The corresponding recall rate of threshold value is x coordinate, and accuracy rate is y-coordinate, and accuracy rate-recall rate is drawn in plane right-angle coordinate (Precision-Recall, P-R) curve.Determine first quartile of the accuracy rate-recall rate curve in plane right-angle coordinate The area surrounded with x-axis and y-axis.According to the area, Average Accuracy (Average Precis ion, AP) is determined.
Certainly, in practical applications, AP can also be determined otherwise, e.g., take the average value of all accuracys rate, This specification does not repeat again herein.
Step 260, when AP meets preset condition, by first sample renewal into sample storehouse.
In one implementation, can be with preset threshold value, which can set based on experience value.When AP is more than upper When stating threshold value, by first sample renewal into sample storehouse.Thus, it is possible to finer judge is carried out to sample.
In other implementations, the first threshold that corresponding accuracy rate is preset value can also be chosen from multiple threshold values Value.In one example, which can be 90%.Namely the threshold that corresponding accuracy rate is 90% is chosen from multiple threshold values Value.Afterwards, the correspondence of first sample, first threshold and AP are updated into sample storehouse.Such as, the content in sample storehouse can With as shown in table 1.
Table 1
Sample First threshold AP
Sample 1 0.8 0.9
Sample 2 0.6 0.9
... ... ...
First threshold in table 1 can also be searched for as the similarity threshold of sample according to the first threshold The similar sample or different sample of the sample.For exemplified by searching for similar sample, its detailed process can be：It can calculate The matching angle value of the sample and candidate samples.If matching angle value exceedes the corresponding first threshold of the sample, can be by candidate's sample Originally it is chosen for the similar sample of the sample.For by taking 90% corresponding first threshold as an example, above-mentioned selection matching angle value is more than the The candidate samples of one threshold value are that the principle of the similar sample of the sample is：When the matching angle value of candidate samples and the sample is more than the During one threshold value, the confidence level for having 90% thinks that candidate samples can fall into the sample storehouse of the sample.
It should be noted that after the similar sample to first sample is chosen, which can also also be updated Into sample storehouse.
It should also be noted that, table 1 is only to facilitate the exemplary illustration for understanding the present embodiment and providing, is not intended as The limitation of the present embodiment.It can also include other contents, e.g., sample label etc. in table 1.
To sum up, the method provided by this specification above-described embodiment, can more accurately and rapidly realize sample storehouse Cleaning, renewal.Further, since this method is automatically performed, so as to meet the application demand of big data.Furthermore due to The threshold value of sample is have updated in sample storehouse at the same time, this can to realize the recalling of particular type sample, comprehensive grading provides basis.
Fig. 3 is the update method schematic diagram that this illustrates sample in the sample storehouse that another embodiment provides, can be with Fig. 3 The distance of sample to be updated and default sample is calculated based on sampling feature vectors, and using the distance after normalization as similarity Value.(it is expressed as according to the sample label of similarity value, default sample：Y=(y1,y2,...,ym),yi∈ { 0,1 }, i=1, 2 ..., m) and multiple threshold values, to generate accuracy rate-recall rate curve.It is 0.9 corresponding threshold that accuracy rate can be chosen afterwards It is worth (simt), the area that accuracy rate-recall rate curve is surrounded with x-axis is calculated, and using the area as AP values.Finally, if AP values More than threshold value, then by the sample, s imtAnd AP renewals are into sample storehouse.Thus, it is possible to it is more effective, rapidly improve sample The quality and generalization ability of sample in this storehouse.
With the update method of sample in above-mentioned sample storehouse accordingly, a kind of sample that this specification one embodiment also provides The updating device of sample in storehouse, as shown in figure 4, the device includes：
Acquiring unit 401, for obtaining the first sample to be updated to sample storehouse.
Computing unit 402, the first sample for calculating the acquisition of acquiring unit 401 have added the pre- of sample label with multiple If the similarity value of sample.
Alternatively, computing unit 402 specifically can be used for：
Determine the sampling feature vectors of first sample, and determine the sampling feature vectors of each default sample.
According to the sampling feature vectors of first sample and the sampling feature vectors of each default sample, first sample is calculated With the distance value of each default sample.
Value of adjusting the distance is normalized.
According to the distance value after normalized, similarity value is determined.
Determination unit 403, for the similarity value calculated according to computing unit 402 and multiple threshold values, determine with it is each The corresponding prediction label of threshold value.
Determination unit 403, is additionally operable to the corresponding prediction label of each threshold value, according to prediction label and sample label, Corresponding accuracy rate and recall rate are determined, so that it is determined that going out multiple accuracys rate and recall rate.
Computing unit 402, is additionally operable to the multiple accuracys rate and recall rate determined according to determination unit 403, calculates the first sample This Average Accuracy AP.
Alternatively, computing unit 402 specifically can be used for：
Using recall rate corresponding with each threshold value as x coordinate, accuracy rate is y-coordinate, is drawn in plane right-angle coordinate Accuracy rate-recall rate curve.
Determine the area that accuracy rate-recall rate curve is surrounded in the first quartile of plane right-angle coordinate with x-axis and y-axis.
According to area, AP is determined.
Updating block 404, when the AP for being calculated when computing unit 402 meets preset condition, first sample renewal is arrived In sample storehouse.
Alternatively, updating block 404 specifically can be used for：
The first threshold that corresponding accuracy rate is preset value is chosen from multiple threshold values.
The correspondence of first sample, first threshold and AP are updated into sample storehouse.
Alternatively, which can also include：Choose unit 405.
Computing unit 402, is additionally operable to calculate the matching angle value of first sample and candidate samples.
Unit 405 is chosen, if exceeding first threshold for the matching angle value that computing unit 402 calculates, by candidate samples It is chosen for the similar sample of first sample.
Alternatively, updating block 404, are additionally operable to the similar Sample Refreshment by first sample into sample storehouse.
The function of each function module of this specification above-described embodiment device, can pass through each step of above method embodiment Rapid to realize, therefore, the specific work process for the device that this specification one embodiment provides, does not repeat again herein.
The updating device of sample in the sample storehouse that this specification one embodiment provides, acquiring unit 401 obtains to be updated To the first sample of sample storehouse.Computing unit 402 calculates first sample and the phase of multiple default samples for having added sample label Like angle value.Determination unit 403 determines and the corresponding prediction label of each threshold value according to similarity value and multiple threshold values.It is right Each corresponding prediction label of threshold value, determination unit 403 according to prediction label and sample label, determine corresponding accuracy rate and Recall rate, so that it is determined that going out multiple accuracys rate and recall rate.Computing unit 402 calculates the according to multiple accuracys rate and recall rate The Average Accuracy AP of one sample.When AP meets preset condition, updating block 404 updates first sample into sample storehouse. Thus, it is possible to more reliably in control sample database sample quality.
Those skilled in the art are it will be appreciated that in said one or multiple examples, work(described in the invention It is able to can be realized with hardware, software, firmware or their any combination.When implemented in software, can be by these functions It is stored in computer-readable medium or is transmitted as one or more instructions on computer-readable medium or code.
Above-described embodiment, has carried out the purpose of the present invention, technical solution and beneficial effect further Describe in detail, it should be understood that the foregoing is merely the embodiment of the present invention, be not intended to limit the present invention Protection domain, all any modification, equivalent substitution, improvement and etc. on the basis of technical scheme, done should all It is included within protection scope of the present invention.

Claims (12)

  1. A kind of 1. update method of sample in sample storehouse, it is characterised in that including：
    Obtain the first sample to be updated to sample storehouse；
    Calculate the similarity value of the first sample and multiple default samples for having added sample label；
    According to the similarity value and multiple threshold values, determine and the corresponding prediction label of each threshold value；
    To the corresponding prediction label of each threshold value, according to the prediction label and the sample label, it is corresponding accurate to determine Rate and recall rate, so that it is determined that going out multiple accuracys rate and recall rate；
    According to definite multiple accuracys rate and recall rate, the Average Accuracy AP of the first sample is calculated；
    If AP meets preset condition, by first sample renewal into the sample storehouse.
  2. 2. according to the method described in right 1, it is characterised in that the calculating first sample has added sample label with multiple Default sample similarity value, including：
    Determine the sampling feature vectors of the first sample, and determine the sampling feature vectors of each default sample；
    According to the sampling feature vectors of the first sample and the sampling feature vectors of each default sample, described in calculating First sample and the distance value of each default sample；
    The distance value is normalized；
    According to the distance value after normalized, the similarity value is determined.
  3. 3. method according to claim 1 or 2, it is characterised in that the multiple accuracys rate and recall rate that the basis determines, The Average Accuracy AP of the first sample is calculated, including：
    Using recall rate corresponding with each threshold value as x coordinate, accuracy rate is y-coordinate, and it is accurate to be drawn in plane right-angle coordinate Rate-recall rate curve；
    Determine the accuracy rate-recall rate curve in the face that the first quartile of the plane right-angle coordinate is surrounded with x-axis and y-axis Product；
    According to the area, the AP is determined.
  4. It is 4. according to the method described in claim 1, it is characterized in that, described by first sample renewal to the sample storehouse In, including：
    The first threshold that corresponding accuracy rate is preset value is chosen from the multiple threshold value；
    The correspondence of the first sample, the first threshold and the AP is updated into the sample storehouse.
  5. 5. according to the method described in claim 4, it is characterized in that, further include：
    Calculate the matching angle value of the first sample and candidate samples；
    If the matching angle value exceedes the first threshold, the candidate samples are chosen for the similar sample of the first sample This.
  6. 6. according to the method described in claim 5, it is characterized in that, further include：
    By the similar Sample Refreshment of the first sample into the sample storehouse.
  7. A kind of 7. updating device of sample in sample storehouse, it is characterised in that including：
    Acquiring unit, for obtaining the first sample to be updated to sample storehouse；
    Computing unit, the default of sample label has been added for calculating the first sample that the acquiring unit obtains with multiple The similarity value of sample；
    Determination unit, for the similarity value calculated according to the computing unit and multiple threshold values, determines and each threshold It is worth corresponding prediction label；
    The determination unit, is additionally operable to the corresponding prediction label of each threshold value, according to the prediction label and the sample Label, determines corresponding accuracy rate and recall rate, so that it is determined that going out multiple accuracys rate and recall rate；
    The computing unit, is additionally operable to the multiple accuracys rate and recall rate determined according to the determination unit, calculates described first The Average Accuracy AP of sample；
    Updating block, when the AP for being calculated when the computing unit meets preset condition, the first sample is updated Into the sample storehouse.
  8. 8. according to the device described in right 7, it is characterised in that the computing unit is specifically used for：
    Determine the sampling feature vectors of the first sample, and determine the sampling feature vectors of each default sample；
    According to the sampling feature vectors of the first sample and the sampling feature vectors of each default sample, described in calculating First sample and the distance value of each default sample；
    The distance value is normalized；
    According to the distance value after normalized, the similarity value is determined.
  9. 9. the device according to claim 7 or 8, it is characterised in that the computing unit is specifically used for：
    Using recall rate corresponding with each threshold value as x coordinate, accuracy rate is y-coordinate, and it is accurate to be drawn in plane right-angle coordinate Rate-recall rate curve；
    Determine the accuracy rate-recall rate curve in the face that the first quartile of the plane right-angle coordinate is surrounded with x-axis and y-axis Product；
    According to the area, the AP is determined.
  10. 10. device according to claim 7, it is characterised in that the updating block is specifically used for：
    The first threshold that corresponding accuracy rate is preset value is chosen from the multiple threshold value；
    The correspondence of the first sample, the first threshold and the AP is updated into the sample storehouse.
  11. 11. device according to claim 10, it is characterised in that further include：Choose unit；
    The computing unit, is additionally operable to calculate the matching angle value of the first sample and candidate samples；
    The selection unit, if exceeding the first threshold for the matching angle value that the computing unit calculates, by institute State the similar sample that candidate samples are chosen for the first sample.
  12. 12. according to the devices described in claim 11, it is characterised in that
    The updating block, is additionally operable to the similar Sample Refreshment by the first sample into the sample storehouse.
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