CN104537008B - Item collection ability value extracting method and device based on matching degree - Google Patents

Item collection ability value extracting method and device based on matching degree Download PDF

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CN104537008B
CN104537008B CN201410781235.9A CN201410781235A CN104537008B CN 104537008 B CN104537008 B CN 104537008B CN 201410781235 A CN201410781235 A CN 201410781235A CN 104537008 B CN104537008 B CN 104537008B
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mrow
msub
matched
mtd
value
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CN104537008A (en
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江潮
张芃
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Wuhan Transn Information Technology Co., Ltd.
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Language Network (wuhan) Information Technology Co Ltd
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Abstract

The invention belongs to data processing field, more particularly to a kind of item collection ability value extracting method and device based on matching degree, wherein, this method includes the deviation for obtaining the data item occurrence of the data item occurrence of object to be matched and standard object, and the matching degree of object and standard object to be matched is iterated to calculate according to the deviation of acquisition；Object to be matched is determined according to the matching degree of iterative calculation.The device includes matching degree computing module, for obtaining the deviation of the data item occurrence of object to be matched and the data item occurrence of standard object, and according to the matching degree of the deviation of acquisition iterative calculation object to be matched and the standard object；Object determining module to be matched, for determining object to be matched according to the matching degree of iterative calculation.The present invention determines object to be matched by using the data item occurrence of object to be matched and the deviation iteration matching degree asked for of data item occurrence of standard object, reduces the mistake recovery rate of ability item collection object.

Description

Item collection ability value extracting method and device based on matching degree
Technical field
The invention belongs to data processing field, in particular to a kind of item collection ability value extraction side based on matching degree Method and device.
Background technology
In actual production process, people generally require to choose some item collection objects for meeting certain ability value, related skill In art, typically by the item collection ability value of intrinsic weight method extracting object, the item collection ability value extracted using this method, carry by mistake Take rate height.It is not easy to extract the item collection object for meeting standard conditions, not only results in the waste of object resource, and be unfavorable for providing The reasonable distribution in source and utilization.
The content of the invention
It is an object of the invention to provide a kind of item collection ability value extracting method and device based on matching degree, with solution The problem of stating.
A kind of item collection ability value extracting method based on matching degree is provided in an embodiment of the present invention, including：
The deviation of the data item occurrence of object to be matched and the data item occurrence of standard object is obtained, and is changed according to the deviation of acquisition In generation, calculates the matching degree of object and standard object to be matched；Wherein, standard object is：Include the item of default ability item standard value Collection；
Object to be matched is determined according to the matching degree of iterative calculation.
Further, the deviation of the data item occurrence of object to be matched and the data item occurrence of standard object is obtained and according to acquisition Deviation also includes before iterating to calculate the matching degree of object and standard object to be matched：To object to be matched and the number of standard object It is normalized according to entry value.
Further, the data item occurrence of object to be matched and standard object is normalized including：
Data item occurrence is mapped to nor_low to nor_high from the minimum value min of preset range between maximum max Between, mapping equation is：
Wherein, nor_low and nor_high is respectively the upper and lower section after normalizing, and x and y are variable, and x is normalizing Value before change, interval range min-max, y are the value after normalization, interval range nor_low-nor_high, formula (1-1) It is positive condition for occurrence, formula (1-2) is negative sense condition for occurrence, and min-max default span is data The number range of entry value.
Further, the deviation of the data item occurrence of object to be matched and the data item occurrence of standard object is obtained and according to acquisition The matching degree that deviation iterates to calculate the object to be matched and standard object includes：
Bias div_left and lower bias div_right, calculation formula are in calculating：
Div_left=cnor_i-nor_low；Div_right=nor_high-cnor_i；
In formula, cnor_iFor the matched value after normalization；
By matched value mnor_iBe converted to standard matched value m'nor_i, conversion formula is：
Matching amplification coefficient amp, calculation formula are determined according to upper bias div_left and lower bias div_right For：
According to the standard matched value m' of acquisitionnor_iAnd matching amplification coefficient amp, ask for matching using cycloid Equation Iterative Spend matiApproximate solution, wherein, the accuracy acc of iterative is set smaller than or equal to 10-3, π is pi, i 1 ... k, K is positive integer.
Further, determine that object to be matched includes according to the matching degree of iterative calculation：
According to matching degree matiAsk for matching score value mscore, matching score value mscore calculation formula is：
In formula, { w1,w2,…,wkBe each ability item of object intrinsic weight, k is that ability item number is natural number, mati For matching degree；
Height order according to the matching score value mscore asked for selects object to be matched.
Present invention also offers a kind of item collection ability value extraction element based on matching degree, including：
Matching degree computing module, for obtaining the inclined of the data item occurrence of object to be matched and the data item occurrence of standard object Difference, and according to the matching degree of the deviation of acquisition iterative calculation object to be matched and standard object；Wherein, standard object is：Comprising The item collection of default ability item standard value；
Object determining module to be matched, for selecting object to be matched according to the matching degree of iterative calculation.
Further, the device also includes：
Normalized module, for the data item occurrence of object to be matched and standard object to be normalized.
Further, the normalized module is specifically used for：
Data item occurrence is mapped to nor_low to nor_high from the minimum value min of preset range between maximum max Between, mapping equation is：
Wherein, nor_low and nor_high is respectively the upper and lower section after normalizing, and x and y are variable, and x is normalizing Value before change, interval range min-max, y are the value after normalization, interval range nor_low-nor_high, formula (1-1) It is positive condition for occurrence, formula (1-2) is negative sense condition for occurrence, and min-max default span is data The number range of entry value.
Further, matching degree computing module is specifically used for：
Bias div_left and lower bias div_right, calculation formula are in calculating：
Div_left=cnor_i-nor_low；Div_right=nor_high-cnor_i；
In formula, cnor_iFor the matched value after normalization；
By matched value mnor_iBe converted to standard matched value m'nor_i, conversion formula is：
Matching amplification coefficient amp, calculation formula are determined according to upper bias div_left and lower bias div_right For：
According to the standard matched value m' of acquisitionnor_iAnd matching amplification coefficient amp, ask for matching using cycloid Equation Iterative Spend matiApproximate solution, wherein, the accuracy acc of iterative is set smaller than or equal to 10-3, π is pi, i 1 ... k, K is positive integer.
Further, object determining module to be matched is specifically used for：
According to matching degree matiAsk for matching score value mscore, matching score value mscore calculation formula is：
In formula, { w1,w2,…,wkBe each ability item of object intrinsic weight, k is that ability item number is natural number, mati For matching degree；
Height order according to the matching score value mscore asked for selects object to be matched.
Item collection ability value extracting method and device provided in an embodiment of the present invention based on matching degree compared with prior art, Extracted by using the data item occurrence of object to be matched and the deviation iteration matching degree asked for of data item occurrence of standard object Object to be matched, the mistake recovery rate of ability item collection object is reduced, ensure that reasonable distribution and the utilization of resource
Brief description of the drawings
Accompanying drawing described herein is used for providing a further understanding of the present invention, forms the part of the application, this hair Bright schematic description and description is used to explain the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings：
Fig. 1 shows the flow chart of the item collection ability value extracting method first embodiment of the invention based on matching degree；
Fig. 2 shows the flow chart of the item collection ability value extracting method second embodiment of the invention based on matching degree；
Fig. 3 shows the structured flowchart of the item collection ability value extraction element first embodiment of the invention based on matching degree；
Fig. 4 shows the structured flowchart of the item collection ability value extraction element second embodiment of the invention based on matching degree.
Embodiment
In the following detailed description, a large amount of specific details are proposed, in order to provide thorough understanding of the present invention.But It will be understood by those within the art that it can also implement the present invention even if without these specific details.In other cases, without detailed Well-known method, process, component and circuit are carefully described, in order to avoid influence the understanding of the present invention.
In order to be better understood from the illustrative embodiment in the present invention, below to some in illustrative embodiment of the present invention Term is briefly described.
The present invention is described in further detail below by specific examples of the implementation and with reference to accompanying drawing.
Join shown in Fig. 1, Fig. 1 shows the stream of the item collection ability value extracting method first embodiment of the invention based on matching degree Cheng Tu.
A kind of item collection ability value extracting method based on matching degree is present embodiments provided, including：
Step S102, obtains the deviation of the data item occurrence of object to be matched and the data item occurrence of standard object, and according to obtaining The deviation taken iterates to calculate the matching degree of object and standard object to be matched；Wherein, standard object is：Include default ability item mark The item collection of quasi- value；
Standard object ability item collection is expressed as C={ c1,c2,…,ck, object ability item collection M={ m to be matched1,m2,…, mk}。
Step S104, object to be matched is determined according to the matching degree of iterative calculation.
The present embodiment is asked by using the data item occurrence of object to be matched and the deviation iteration of data item occurrence of standard object The matching degree taken extracts object to be matched, reduces the mistake recovery rate of ability item collection object, ensure that the reasonable distribution of resource And utilize.
Join shown in Fig. 2, Fig. 2 shows the stream of the item collection ability value extracting method second embodiment of the invention based on matching degree Cheng Tu.
In the present embodiment, possess in order that obtaining between the data item occurrence of object to be matched and the data item occurrence of standard object Comparativity, it can be uniformly processed in identical quantity, in the data item occurrence and the number of standard object for obtaining object to be matched Deviation according to entry value and the deviation according to acquisition can also wrap before iterating to calculate the matching degree of object and standard object to be matched Include：
Step S101, the data item occurrence of object to be matched and standard object is normalized.
The detailed process of above-mentioned normalized includes：
Data item occurrence is mapped to nor_low to nor_high from the minimum value min of preset range between maximum max Between, mapping equation is：
Wherein, nor_low and nor_high is respectively the upper and lower section after normalizing, and x and y are variable, and x is normalizing Value before change, interval range min-max, y are the value after normalization, interval range nor_low-nor_high, formula (1-1) It is positive condition for occurrence, formula (1-2) is negative sense condition for occurrence, and min-max default span is data The number range of entry value.
In the present embodiment, the deviation and basis of the data item occurrence of object to be matched and the data item occurrence of standard object are obtained The matching degree that the deviation of acquisition iterates to calculate object and standard object to be matched specifically includes：
Bias div_left and lower bias div_right, calculation formula are in calculating：
Div_left=cnor_i-nor_low；Div_right=nor_high-cnor_i；
In formula, cnor_iFor the matched value after normalization；
By matched value mnor_iBe converted to standard matched value m'nor_i, conversion formula is：
Matching amplification coefficient amp, calculation formula are determined according to upper bias div_left and lower bias div_right For：
According to the standard matched value m' of acquisitionnor_iAnd matching amplification coefficient amp, ask for matching using cycloid Equation Iterative Spend matiApproximate solution, wherein, the accuracy acc of iterative is set smaller than or equal to 10-3, π is pi, i 1 ... k, K is positive integer.Specific iterative algorithm is as follows：
Begin
Acc is set smaller than 10-3Value；X_low=0；X_high=2 π；X=(x_low+x_high)/2；
while(|m'nor_i- x-sinx | ＞ acc)
if(m'nor_i＞ (x-sinx))
X_low=(x_low+x_high)/2；X=(x_low+x_high)/2；}
else{
X_high=(x_low+x_high)/2；X=(x_low+x_high)/2；}
}
mati=(amp* (1-cosx)/2+1)/(amp+1)；
End
Wherein, acc is accuracy, and x is the value in data item occurrence preset range, and x_low is in data item occurrence preset range Minimum value, x_high be data item occurrence preset range in maximum, mati is matching degree.
The present embodiment solves of standard object and object ability item collection to be matched using the characteristic of cycloid (cycloid) With problem.
The parametric equation of cycloid is：
Wherein r is the radius of circle, and θ is that the radius of circle rolls one week angle with vertical curve.Cycloid has a key property, its During y values gradually decrease from peak 2r to minimum point 0, its rate of descent is more and more faster.Using this characteristic, will mark The value of each ability item of quasi- object is set in peak, and its matching degree is set to 1, and object ability item to be matched is with being matched ability The value difference of item is smaller, and its matching degree is closer to 1, and the bigger matching degree of difference is smaller, and diminishing for this matching degree is not even Speed is reduced, but as the increase matching degree of difference can accelerate to reduce, this ensures that more meeting the ability value of standard object Object to be matched it is selected probability it is bigger.
In the present embodiment, selected according to the matching degree of iterative calculation and determine that matching object specifically includes：
According to matching degree matiAsk for matching score value mscore, matching score value mscore calculation formula is：
In formula, { w1,w2,…,wkBe each ability item of object intrinsic weight, k is that ability item number is natural number, mati For matching degree；
Height order according to the matching score value mscore asked for selects object to be matched.
Join shown in Fig. 3, Fig. 3 shows the knot of the item collection ability value extraction element first embodiment of the invention based on matching degree Structure block diagram.
Embodiments of the invention additionally provide a kind of item collection ability value extraction element based on matching degree, including：
Matching degree computing module 32, for obtaining the inclined of the data item occurrence of object to be matched and the data item occurrence of standard object Difference, and according to the matching degree of the deviation of acquisition iterative calculation object to be matched and standard object；Wherein, standard object is：Comprising The item collection of default ability item standard value；
Object Selection module 34 to be matched, for determining object to be matched according to the matching degree of iterative calculation.
The present embodiment utilizes the data item occurrence of object to be matched and the data of standard object by matching degree computing module 32 The matching degree that the deviation iteration of entry value is asked for, by the selective extraction of object determining module 34 to be matched object to be matched, reduce The mistake recovery rate of ability item collection object, it ensure that reasonable distribution and the utilization of resource.
Join shown in Fig. 4, Fig. 4 shows the knot of the item collection ability value extraction element second embodiment of the invention based on matching degree Structure block diagram.
In the present embodiment, possess in order that obtaining between the data item occurrence of object to be matched and the data item occurrence of standard object Comparativity, it can be uniformly processed in identical quantity, the device can also include：Normalized module 31, for pair The data item occurrence of object and standard object to be matched is normalized.
The normalized module 31 is specifically used for：
Data item occurrence is mapped to nor_low to nor_high from the minimum value min of preset range between maximum max Between, mapping equation is：
Wherein, nor_low and nor_high is respectively the upper and lower section after normalizing, and x and y are variable, and x is normalizing Value before change, interval range min-max, y are the value after normalization, interval range nor_low-nor_high, formula (1-1) It is positive condition for occurrence, formula (1-2) is negative sense condition for occurrence, and min-max default span is data The number range of entry value.
In the present embodiment, the matching degree computing module 32 is specifically used for：
Bias div_left and lower bias div_right, calculation formula are in calculating：
Div_left=cnor_i-nor_low；Div_right=nor_high-cnor_i；
In formula, cnor_iFor the matched value after normalization；
By matched value mnor_iBe converted to standard matched value m'nor_i, conversion formula is：
Matching amplification coefficient amp, calculation formula are determined according to upper bias div_left and lower bias div_right For：
According to the standard matched value m' of acquisitionnor_iAnd matching amplification coefficient amp, ask for matching using cycloid Equation Iterative Spend matiApproximate solution, wherein, the accuracy acc of iterative is set smaller than or equal to 10-3, π is pi, i 1 ... k, K is positive integer.Specific iterative algorithm is as follows：
Begin
Acc is set smaller than 10-3Value；X_low=0；X_high=2 π；X=(x_low+x_high)/2；
while(|m'nor_i- x-sinx | ＞ acc)
if(m'nor_i＞ (x-sinx))
X_low=(x_low+x_high)/2；X=(x_low+x_high)/2；}
else{
X_high=(x_low+x_high)/2；X=(x_low+x_high)/2；}
}
mati=(amp* (1-cosx)/2+1)/(amp+1)；
End
Wherein, acc is accuracy, and x is the value in data item occurrence preset range, and x_low is in data item occurrence preset range Minimum value, x_high be data item occurrence preset range in maximum, mati is matching degree.
In the present embodiment, the object determining module 34 to be matched is specifically used for：
According to matching degree matiAsk for matching score value mscore, matching score value mscore calculation formula is：
In formula, { w1,w2,…,wkBe each ability item of object intrinsic weight, k is that ability item number is natural number, mati For matching degree；
Height order according to the matching score value mscore asked for selects object to be matched.
In order to more intuitively describe method provided by the invention, it is described further below with specific data.
(1) input data is handled
1st, Standard object data is referring to table 1
The Standard object data of table 1
Standard object Ability item 1 Ability item 2 Ability item 3
C 85 4000 110
2nd, object data to be matched is referring to table 2
2 object data to be matched of table
3rd, normalized
According to following formula：
Each item data of ability item is mapped between nor_low-nor_high between min-max so that these Possess comparativity with item data, can be handled in identical quantity.
Nor_low=50, nor_high=100 are taken, ability item 1, ability item 2, ability item 3 this 3 are normalized：
1) ability item 1 is the data in 50-100, without processing.
2) ability item 2 is positive condition, is with formula (1-1), preset range 1000-6000, mapping equation：Y=x/100 +40。
3) ability item 3 is negative sense condition, is with formula (1-2), preset range 80-130, mapping equation：Y=180-x.
After normalized, referring to table 3.
Object data to be matched after the normalized of table 3
(2) object to be matched is determined by matching degree
Weight setting：Ability item 1：0.5；Ability item 2：0.2；Ability item 3：0.3.
Because M2 and M5 ability item 3 does not meet imposing a condition less than 110, M2 and M5 are excluded.
According to the data of object to be matched, according to foregoing iterative algorithm, the object to be matched matching degree of each is calculated, is obtained To object matching degrees of data to be matched, 4 are shown in Table.
The object matching degrees of data to be matched of table 4
According to the weight of setting, object score to be matched is calculated according to foregoing matching score value mscore calculation formula：
M1 scores：90*0.962*0.5+91*0.77*0.2+70*0.3=78.304
M3 scores：85*0.5+82*0.995*0.2+77*0.963*0.3=81.063
M4 scores：88*0.987*0.5+84*0.969*0.2+71*0.998=80.965
According to score, according to the height (preparatory condition) of matching score value determine the order of object to be matched for M3 → M4 → M1。
(3) object to be matched is determined by intrinsic weight
M1 scores：90*0.5+91*0.2+70*0.3=84.2
M2 scores：95*0.5+95*0.2+62*0.3=85.1
M3 scores：85*0.5+82*0.2+77*0.3=82
M4 scores：88*0.5+84*0.2+71*0.3=82.1
M5 scores：99*0.5+99*0.2+60*0.3=87.3
Because M2 and M5 ability item 3 does not meet the requirement less than 110, exclude M2 and M5, according to successively ranking, The order of preference of object so to be matched is：M1→M4→M3.
By (three) although it can be seen from object M1 every capacity index it is all very high, by the method for intrinsic weight first Meeting selecting object M1, but it is small with the matching degree ratio M3 and M4 of each data item of standard object, and implemented according to the present invention What example provided determine that the method for object to be matched can be chosen by matching degree more conforms to the object to be matched of standard object, carries High matching accuracy rate, the wasting of resources avoided.
The preferred embodiments of the present invention are the foregoing is only, are not intended to limit the invention, for the skill of this area For art personnel, the present invention can have various modifications and variations.Within the spirit and principles of the invention, that is made any repaiies Change, equivalent substitution, improvement etc., should be included in the scope of the protection.

Claims (4)

  1. A kind of 1. item collection ability value extracting method based on matching degree, it is characterised in that including：
    The data item occurrence of object to be matched and standard object is normalized, including：
    The data item occurrence is mapped to nor_low to nor_high from the minimum value min of preset range between maximum max Between, mapping equation is：
    <mrow> <mi>y</mi> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <mo>(</mo> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>h</mi> <mi>i</mi> <mi>g</mi> <mi>h</mi> <mo>-</mo> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>l</mi> <mi>o</mi> <mi>w</mi> <mo>)</mo> <mo>&amp;CenterDot;</mo> <mfrac> <mrow> <mi>x</mi> <mo>-</mo> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> <mo>-</mo> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> </mfrac> <mo>+</mo> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>l</mi> <mi>o</mi> <mi>w</mi> </mrow> </mtd> <mtd> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>h</mi> <mi>i</mi> <mi>g</mi> <mi>h</mi> <mo>-</mo> <mrow> <mo>(</mo> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>h</mi> <mi>i</mi> <mi>g</mi> <mi>h</mi> <mo>-</mo> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>l</mi> <mi>o</mi> <mi>w</mi> <mo>)</mo> </mrow> <mo>&amp;CenterDot;</mo> <mfrac> <mrow> <mi>x</mi> <mo>-</mo> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> <mo>-</mo> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> </mfrac> </mrow> </mtd> <mtd> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> </mtd> </mtr> </mtable> </mfenced> </mrow>
    Wherein, nor_low and nor_high is respectively the upper and lower section after normalizing, and x and y are variable, before x is normalization Value, interval range min-max, y are the value after normalization, interval range nor_low-nor_high, and formula (1-1) is used for Occurrence is positive condition, and formula (1-2) is negative sense condition for occurrence, and min-max default span is the data The number range of entry value；
    The deviation of the data item occurrence of the object to be matched and the data item occurrence of the standard object is obtained, and according to the inclined of acquisition Difference iterates to calculate the matching degree of the object to be matched and the standard object, including：
    Bias div_left and lower bias div_right, calculation formula are in calculating：
    Div_left=cnor_i-nor_low；Div_right=nor_high-cnor_i；
    In formula, cnor_iFor the matched value after normalization；
    By matched value mnor_iBe converted to standard matched value m'nor_i, conversion formula is：
    <mrow> <msubsup> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> <mo>&amp;prime;</mo> </msubsup> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <mi>&amp;pi;</mi> <mo>&amp;CenterDot;</mo> <mfrac> <mrow> <msub> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>+</mo> <mi>d</mi> <mi>i</mi> <mi>v</mi> <mo>_</mo> <mi>r</mi> <mi>i</mi> <mi>g</mi> <mi>h</mi> <mi>t</mi> <mo>-</mo> <msub> <mi>c</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> </mrow> <mrow> <mi>d</mi> <mi>i</mi> <mi>v</mi> <mo>_</mo> <mi>r</mi> <mi>i</mi> <mi>g</mi> <mi>h</mi> <mi>t</mi> </mrow> </mfrac> <mo>,</mo> <msub> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>&amp;GreaterEqual;</mo> <msub> <mi>c</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>&amp;pi;</mi> <mo>&amp;CenterDot;</mo> <mfrac> <mrow> <msub> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>+</mo> <mi>d</mi> <mi>i</mi> <mi>v</mi> <mo>_</mo> <mi>l</mi> <mi>e</mi> <mi>f</mi> <mi>t</mi> <mo>-</mo> <msub> <mi>c</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> </mrow> <mrow> <mi>d</mi> <mi>i</mi> <mi>v</mi> <mo>_</mo> <mi>l</mi> <mi>e</mi> <mi>f</mi> <mi>t</mi> </mrow> </mfrac> <mo>,</mo> <msub> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>&lt;</mo> <msub> <mi>c</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> </mrow>
    Matching amplification coefficient amp, calculation formula are determined according to the upper bias div_left and lower bias div_right For：
    <mrow> <mi>a</mi> <mi>m</mi> <mi>p</mi> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <mi>d</mi> <mi>i</mi> <mi>v</mi> <mo>_</mo> <mi>r</mi> <mi>i</mi> <mi>g</mi> <mi>h</mi> <mi>t</mi> <mo>/</mo> <mn>10</mn> <mi>&amp;pi;</mi> <mo>,</mo> <msub> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>&amp;GreaterEqual;</mo> <msub> <mi>c</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>d</mi> <mi>i</mi> <mi>v</mi> <mo>_</mo> <mi>l</mi> <mi>e</mi> <mi>f</mi> <mi>t</mi> <mo>/</mo> <mn>10</mn> <mi>&amp;pi;</mi> <mo>,</mo> <msub> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>&lt;</mo> <msub> <mi>c</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> </mrow>
    According to the standard matched value m' of acquisitionnor_iAnd matching amplification coefficient amp, ask for matching degree using cycloid Equation Iterative matiApproximate solution, wherein, the accuracy acc of iterative is set smaller than or equal to 10-3, π is pi, i 1 ... k, k For positive integer；Wherein, the standard object is：Include the item collection of default ability item standard value；
    The object to be matched is determined according to the matching degree of iterative calculation.
  2. 2. the item collection ability value extracting method according to claim 1 based on matching degree, it is characterised in that according to iteration meter The matching degree of calculation determines that the object to be matched includes：
    According to the matching degree matiAsk for matching score value mscore, the calculation formula of the matching score value mscore is：
    <mrow> <mi>m</mi> <mi>s</mi> <mi>c</mi> <mi>o</mi> <mi>r</mi> <mi>e</mi> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>k</mi> </munderover> <msub> <mi>w</mi> <mi>i</mi> </msub> <mo>&amp;CenterDot;</mo> <msub> <mi>mat</mi> <mi>i</mi> </msub> <mo>&amp;CenterDot;</mo> <msub> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> </mrow>
    In formula, { w1,w2,…,wkBe each ability item of object intrinsic weight, k is that ability item number is natural number, matiFor matching Degree；
    Height order according to the matching score value mscore asked for selects object to be matched.
  3. A kind of 3. item collection ability value extraction element based on matching degree, it is characterised in that including：
    Normalized module, for the data item occurrence of object to be matched and standard object to be normalized；It is described to return One change processing module is specifically used for：
    The data item occurrence is mapped to nor_low to nor_high from the minimum value min of preset range between maximum max Between, mapping equation is：
    <mrow> <mi>y</mi> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <mo>(</mo> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>h</mi> <mi>i</mi> <mi>g</mi> <mi>h</mi> <mo>-</mo> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>l</mi> <mi>o</mi> <mi>w</mi> <mo>)</mo> <mo>&amp;CenterDot;</mo> <mfrac> <mrow> <mi>x</mi> <mo>-</mo> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> <mo>-</mo> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> </mfrac> <mo>+</mo> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>l</mi> <mi>o</mi> <mi>w</mi> </mrow> </mtd> <mtd> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>h</mi> <mi>i</mi> <mi>g</mi> <mi>h</mi> <mo>-</mo> <mrow> <mo>(</mo> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>h</mi> <mi>i</mi> <mi>g</mi> <mi>h</mi> <mo>-</mo> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>l</mi> <mi>o</mi> <mi>w</mi> <mo>)</mo> </mrow> <mo>&amp;CenterDot;</mo> <mfrac> <mrow> <mi>x</mi> <mo>-</mo> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> <mo>-</mo> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> </mfrac> </mrow> </mtd> <mtd> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mn>2</mn> <mo>)</mo> </mrow> </mtd> </mtr> </mtable> </mfenced> </mrow>
    Wherein, nor_low and nor_high is respectively the upper and lower section after normalizing, and x and y are variable, before x is normalization Value, interval range min-max, y are the value after normalization, interval range nor_low-nor_high, and formula (1-1) is used for Occurrence is positive condition, and formula (1-2) is negative sense condition for occurrence, and min-max default span is the data The number range of entry value；
    Matching degree computing module, for obtaining the data item occurrence of the object to be matched and the data item occurrence of the standard object Deviation, and according to the matching degree of the deviation of the acquisition iterative calculation object to be matched and the standard object；The matching degree Computing module is specifically used for：
    Bias div_left and lower bias div_right, calculation formula are in calculating：
    Div_left=cnor_i-nor_low；Div_right=nor_high-cnor_i；
    In formula, cnor_iFor the matched value after normalization；
    By matched value mnor_iBe converted to standard matched value m'nor_i, conversion formula is：
    <mrow> <msubsup> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> <mo>&amp;prime;</mo> </msubsup> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <mi>&amp;pi;</mi> <mo>&amp;CenterDot;</mo> <mfrac> <mrow> <msub> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>+</mo> <mi>d</mi> <mi>i</mi> <mi>v</mi> <mo>_</mo> <mi>r</mi> <mi>i</mi> <mi>g</mi> <mi>h</mi> <mi>t</mi> <mo>-</mo> <msub> <mi>c</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> </mrow> <mrow> <mi>d</mi> <mi>i</mi> <mi>v</mi> <mo>_</mo> <mi>r</mi> <mi>i</mi> <mi>g</mi> <mi>h</mi> <mi>t</mi> </mrow> </mfrac> <mo>,</mo> <msub> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>&amp;GreaterEqual;</mo> <msub> <mi>c</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>&amp;pi;</mi> <mo>&amp;CenterDot;</mo> <mfrac> <mrow> <msub> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>+</mo> <mi>d</mi> <mi>i</mi> <mi>v</mi> <mo>_</mo> <mi>l</mi> <mi>e</mi> <mi>f</mi> <mi>t</mi> <mo>-</mo> <msub> <mi>c</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> </mrow> <mrow> <mi>d</mi> <mi>i</mi> <mi>v</mi> <mo>_</mo> <mi>l</mi> <mi>e</mi> <mi>f</mi> <mi>t</mi> </mrow> </mfrac> <mo>,</mo> <msub> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>&lt;</mo> <msub> <mi>c</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> </mrow>
    Matching amplification coefficient amp, calculation formula are determined according to the upper bias div_left and lower bias div_right For：
    <mrow> <mi>a</mi> <mi>m</mi> <mi>p</mi> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <mi>d</mi> <mi>i</mi> <mi>v</mi> <mo>_</mo> <mi>r</mi> <mi>i</mi> <mi>g</mi> <mi>h</mi> <mi>t</mi> <mo>/</mo> <mn>10</mn> <mi>&amp;pi;</mi> <mo>,</mo> <msub> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>&amp;GreaterEqual;</mo> <msub> <mi>c</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>d</mi> <mi>i</mi> <mi>v</mi> <mo>_</mo> <mi>l</mi> <mi>e</mi> <mi>f</mi> <mi>t</mi> <mo>/</mo> <mn>10</mn> <mi>&amp;pi;</mi> <mo>,</mo> <msub> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> <mo>&lt;</mo> <msub> <mi>c</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> </mrow>
    According to the standard matched value m' of acquisitionnor_iAnd matching amplification coefficient amp, ask for matching degree using cycloid Equation Iterative matiApproximate solution, wherein, the accuracy acc of iterative is set smaller than or equal to 10-3, π is pi, i 1 ... k, k For positive integer；Wherein, the standard object is：Include the item collection of default ability item standard value；
    Object determining module to be matched, for determining object to be matched according to the matching degree of iterative calculation.
  4. 4. the item collection ability value extraction element according to claim 3 based on matching degree, it is characterised in that described to be matched Object determining module is specifically used for：
    According to the matching degree matiAsk for matching score value mscore, the calculation formula of the matching score value mscore is：
    <mrow> <mi>m</mi> <mi>s</mi> <mi>c</mi> <mi>o</mi> <mi>r</mi> <mi>e</mi> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>k</mi> </munderover> <msub> <mi>w</mi> <mi>i</mi> </msub> <mo>&amp;CenterDot;</mo> <msub> <mi>mat</mi> <mi>i</mi> </msub> <mo>&amp;CenterDot;</mo> <msub> <mi>m</mi> <mrow> <mi>n</mi> <mi>o</mi> <mi>r</mi> <mo>_</mo> <mi>i</mi> </mrow> </msub> </mrow>
    In formula, { w1,w2,…,wkBe each ability item of object intrinsic weight, k is that ability item number is natural number, matiFor matching Degree；
    Height order according to the matching score value mscore asked for selects object to be matched.
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