CN104008261B - The method of information processing and electronic equipment - Google Patents
The method of information processing and electronic equipment Download PDFInfo
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- CN104008261B CN104008261B CN201310062191.XA CN201310062191A CN104008261B CN 104008261 B CN104008261 B CN 104008261B CN 201310062191 A CN201310062191 A CN 201310062191A CN 104008261 B CN104008261 B CN 104008261B
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Abstract
The invention discloses a kind of method of information processing and electronic equipment, obtain described electronic equipment storage has first group of data of N number of first data and the second group data with M second data corresponding with described first group of data, pre-conditioned based on related to first and second parameter described first, include at least two group two tuple-set of the one or two tuple-set and the two or two tuple-set from described first group of data and described second group of extracting data, based on preset rules, obtain first group of two tuple-set from described at least two group two tuple-set, wherein, each of described first group of two tuple-set two tuples are different from；The first data in each of described first group of two tuple-set two tuples and the second data are carried out with Similarity Measure, obtains multiple first Similarity value corresponding with described first group of two tuple-set.
Description
Technical field
The present invention relates to field of computer technology, more particularly, to a kind of method of information processing and electronic equipment.
Background technology
With the development of electronic device technology and computer technology, the processing data of the CPU in existing electronic equipment
Speed is increasingly sooner so that described electronic equipment can be completed in a relatively short time data calculating task, and then makes user
Easy to use, the experience of user is also more preferable.
Present inventor, during realizing the embodiment of the present application technical scheme, at least finds exist in prior art
Following technical problem：
Existing electronic equipment, when carrying out a large amount of two tuple data Similarity Measure, exists computationally intensive, calculates the time
Long technical problem, this is because existing electronic equipment, when for similarity in two groups of data M and N, needs in M
Each of each element and N element is matched one by one, obtains multiple two tuple data, is calculated the plurality of two
The similarity between two data in each of tuple data two tuple, when M and N all ratios are larger, this is a calculating
Measure very big process, such as：4,600,000 user models and 220,000 information models are carried out by during to calculating, need into
Row about 1 TFlops calculates, thus existing computationally intensive, calculates the technical problem of time length, so that user is using not side
Just so that the experience of user is also bad.
Content of the invention
The embodiment of the present application is passed through to provide a kind of method of information processing and electronic equipment, sets in order to solve existing electronics
The standby technical problem existing computationally intensive when carrying out a large amount of two tuple data Similarity Measure, calculating time length.
The embodiment of the present application provides a kind of method of information processing, is applied in electronic equipment, methods described includes：
Obtain the storage of described electronic equipment have N number of first data first group of data and with described first group of data pair
The second group of data with M the second data answered, wherein, each of described N number of first data the first data is at least wrapped
Include first parameter value corresponding with the first parameter and second parameter value corresponding with the second parameter, in described M the second data
Each second data at least includes threeth parameter value corresponding with described first parameter and corresponding with described second parameter
Four parameter values, N and M is the integer not less than 2；
Pre-conditioned based on related to first and second parameter described first, from described first group of data and described second
Group extracting data includes at least two group two tuple-set of the one or two tuple-set and the two or two tuple-set, wherein, institute
Stating the one or two tuple-set is will to have K first of fisrt feature corresponding with described first parameter in described first group of data
Have each in L the second data of described fisrt feature in each of data first data and described second group of data
The set of two tuples that individual second data is compared one by one, described two or two tuple-set is that will have in described first group of data
There are each of Q the first data of second feature corresponding with described second parameter the first data and described second group of data
In there is the set of two tuples that each of P second data of described second feature the second data is compared one by one,
K, L, Q and P are the integer not less than 1；
Based on preset rules, from described at least two group two tuple-set, obtain first group of two tuple-set, wherein, institute
State each of first group of two tuple-set two tuple to be different from；
The first data in each of described first group of two tuple-set two tuples and the second data are carried out similar
Degree calculates, and obtains multiple first Similarity value corresponding with described first group of two tuple-set.
Optionally, described pre-conditioned based on related to first and second parameter described first, from described first group of number
According at least two group two tuple including the one or two tuple-set and the two or two tuple-set with described second group of extracting data
Set, specifically includes：Sub- condition is preset based on the described first first related to described first parameter in pre-conditioned, from institute
State first group of data and the one or two tuple-set described in described second group of extracting data；Based on described first pre-conditioned in
Second related to described second parameter presets sub- condition, from described in described first group of data and described second group of extracting data
Two or two tuple-set.
Optionally, when described first parameter is the first axle in the first coordinate system, described based on the described first default bar
First related to described first parameter in part presets sub- condition, carries from described first group of data and described second group of data
Take described one or two tuple-set, specially：Based on each of described first group of data the first data in described first axle
On numerical value when being zero, obtain described K first that the numerical value in described first axle in described first group of data is non-zero
Data, wherein, described numerical value in described first axle is non-zero as described fisrt feature；And it is based on described second group
When numerical value in described first axle for each of data second data is zero, obtain described second group of data in described
Numerical value in first axle is described L the second data of non-zero；Based on described K the first data and described L the second data, obtain
Take described one or two tuple-set, wherein, described one or two tuple-set is by each of described K first data first
The set of two tuples that data is compared one by one with each of described L the second data the second data.
Optionally, when described second parameter is different from described first axle the second axle in described first coordinate system,
Described second related to described second parameter based on described first in pre-conditioned presets sub- condition, from described first group of number
According to the one or two tuple-set described in described second group of extracting data, specially：Based on each in described first group of data
When numerical value on described second axle for individual first data is zero, obtain the number on described second axle in described first group of data
It is worth described Q the first data for non-zero, wherein, described numerical value on described second axle is that non-zero is special as described second
Levy；And when the numerical value on described second axle is zero based on each of described second group of data the second data, obtain institute
State described P the second data that the numerical value on described second axle in second group of data is non-zero；Based on described Q first number
According to second data individual with described P, obtain described two or two tuple-set, wherein, described two or two tuple-set is by described Q
Each of each of first data first data and described P the second data the second data compared one by one two
The set of tuple.
Optionally, described obtain described in the first data at least in each of two groups of binary set two tuple and the second number
According to multiple first Similarity value, specifically include：Based on preset rules, obtain the from described at least two group two tuple-set
One group of two tuple-set, wherein, each of described first group of two tuple-set two tuples are different from；To described first group
The first data in each of two tuple-sets two tuple and the second data carry out Similarity Measure, obtain and described first
Organize corresponding multiple first Similarity value of two tuple-sets.
Optionally, described to the first data and second in each of described first group of two tuple-set two tuples
Data carries out Similarity Measure, after obtaining multiple first Similarity value corresponding with described first group of two tuple-set, described
Method includes：Based on the plurality of first Similarity value, each of described second group of data the second data is pressed default plan
Slightly it is ranked up with each of described first group of data the first data.
The application one embodiment provides a kind of electronic equipment, and described electronic equipment includes：
Acquiring unit, for obtain the storage of described electronic equipment have N number of first data first group of data and with institute
State the corresponding second group of data with M the second data of first group of data, wherein, each of described N number of first data
First data at least includes first parameter value corresponding with the first parameter and second parameter value corresponding with the second parameter, described M
Each of individual second data the second data at least includes threeth parameter value corresponding with described first parameter and with described
Corresponding 4th parameter value of two parameters, N and M is the integer not less than 2；
Extraction unit, pre-conditioned based on related to first and second parameter described first, for from described first group
Data and described second group of extracting data include at least two groups binary of the one or two tuple-set and the two or two tuple-set
Group set, wherein, described one or two tuple-set is that will have corresponding with described first parameter the in described first group of data
There is in each of K the first data of one feature the first data and described second group of data L of described fisrt feature
The set of two tuples that each of second data second data is compared one by one, described two or two tuple-set is by institute
State and there is in first group of data each of Q the first data of second feature corresponding with described second parameter the first data
Compared one by one with each of the P in described second group of data with described second feature the second data the second data
Two tuples set, K, L, Q and P are the integer not less than 1；
Screening unit, based on preset rules, for obtaining first group of binary from described at least two group two tuple-set
Group set, wherein, each of described first group of two tuple-set two tuples are different from；
Computing unit, the first data at least in each of two groups of binary set two tuple and the second data described in acquisition
Multiple first Similarity value.
Optionally, described extraction unit, specifically for：Based on described first in pre-conditioned with described first parameter phase
First closing presets sub- condition, for from described first group of data and the one or two tuple set described in described second group of extracting data
Close, based on the default sub- condition of the described first second related to described second parameter in pre-conditioned, for from described first
Group data and the two or two tuple-set described in described second group of extracting data.
Optionally, described extraction unit includes the first extraction subelement, is in the first coordinate system in described first parameter
During first axle, when being zero based on each of described first group of data numerical value in described first axle for first data, it is used for
Obtain described K the first data that the numerical value in described first axle in described first group of data is non-zero, wherein, will be described
Numerical value in described first axle be non-zero as described fisrt feature, and based on each of described second group of data the
When numerical value in described first axle for two data is zero, for obtaining the number in described first axle in described second group of data
It is worth described L the second data for non-zero, based on described K the first data and described L the second data, for obtaining described the
One or two tuple-sets, wherein, described one or two tuple-set is by each of described K the first data the first data and institute
State the set of two tuples that each of L the second data the second data is compared one by one.
Optionally, described extraction unit includes the second extraction subelement, is described first coordinate system in described second parameter
In different from described first axle the second axle when, based on each of described first group of data the first data described second
When numerical value on axle is zero, for obtaining the described Q that the numerical value on described second axle in described first group of data is non-zero
Individual first data, wherein, using described numerical value on described second axle be non-zero as described second feature, and based on described
When numerical value on described second axle for each of second group of data second data is zero, for obtaining described second group of data
In the numerical value on described second axle be non-zero described P the second data, based on described Q the first data and described P
Second data, for obtaining described two or two tuple-set, wherein, described two or two tuple-set is by described Q first number
According to each of each of the first data and described P the second data the second data two tuples of being compared one by one
Set.
Optionally, described electronic equipment also includes sequencing unit, described to every in described first group of two tuple-set
The first data in one two tuple and the second data carry out Similarity Measure, obtain corresponding with described first group of two tuple-set
Multiple first Similarity value after, based on the plurality of first Similarity value, for will be each in described second group of data
Individual second data is ranked up with each of described first group of data the first data by preset strategy.
The one or more technical schemes providing in the embodiment of the present application, at least have the following technical effect that or advantage：
One, due to the embodiment of the present application be pre-conditioned based on related to first and second parameter described first,
Include the one or two tuple-set and the two or two tuple-set from described first group of data and described second group of extracting data
At least two group two tuple-set, based on preset rules, obtains first group of two tuple from described at least two group two tuple-set
Set, wherein, each of described first group of two tuple-set two tuples are different from, then based at least two groups described in acquisition
The first data in each of binary set two tuple and multiple first Similarity value of the second data, obtain described first group
Each of data first data and each of described second group of data the second data and the plurality of first similarity
It is worth corresponding multiple first matching value, because described one or two tuple-set is described first group of data and described second group of data
In there is the first data of same characteristic features and set that the second data is compared one by one is so that many in described first group of data
Multiple second data in individual first data and described second group of data when not possessing same characteristic features, that is, show the plurality of the
The similarity of one data and the plurality of second data is 0, thus need not the plurality of first data and the plurality of second number
According to being calculated, thus solving existing electronic equipment when carrying out a large amount of two tuple data Similarity Measure, there is calculating
Measure the technical problem calculating greatly time length, and then achieve described electronic equipment and carry out a large amount of two tuple data similarity meters
During calculation, effectively reduce amount of calculation so that the technique effect that reduces of the time of calculating, and then be user-friendly to the body so that user
Test more preferably.
Two, because the embodiment of the present application is based on preset rules, obtain from described at least two group two tuple-set
First group of two tuple-set, wherein, each of described first group of two tuple-set two tuples are different from, then again to institute
State the first data in each of first group of two tuple-set two tuple and the second data carry out Similarity Measure, obtain with
Corresponding multiple first similarities of described first group of two tuple-set are so as at least two group two tuple set described in effective removal
Identical two tuple in conjunction, reduces the quantity of calculative two tuples, reduces amount of calculation so that the calculating time enters further
The minimizing of one step, and then be user-friendly to so that the experience of user is more preferable.
Three, because the embodiment of the present application is after obtaining the plurality of first matching value, based on the plurality of first
Join value, each of described second group of data the second data is pressed each of preset strategy and described first group of data the
One data is ranked up, such that it is able to by each of described second group of data the second data and described first group of data
Each first data according to matching value from big to small in being sorted successively so that user has more intuitive impression, thus side
Just user checked so that the experience of user more preferable.
Brief description
Fig. 1 is the flow chart of the method for information processing in the embodiment of the present application；
Fig. 2 is the structural representation of electronic equipment in the embodiment of the present application.
Specific embodiment
The embodiment of the present application is passed through to provide a kind of method of information processing and electronic equipment, sets in order to solve existing electronics
The standby technical problem existing computationally intensive when carrying out a large amount of two tuple data Similarity Measure, calculating time length.The application is real
The technical scheme applying example is to solve the problems, such as above-mentioned technology, and general thought is as follows：
Because the embodiment of the present application is pre-conditioned based on related to first and second parameter described first, from described
First group of data and described second group of extracting data include at least the two of the one or two tuple-set and the two or two tuple-set
Organize two tuple-sets, based on preset rules, from described at least two group two tuple-set, obtain first group of two tuple-set, its
In, each of described first group of two tuple-set two tuples are different from, then based at least two group two metaset described in acquisition
The first data in each of conjunction two tuples and multiple first Similarity value of the second data, obtain in described first group of data
Each first data is corresponding with the plurality of first Similarity value with each of described second group of data the second data
Multiple first matching values, because described one or two tuple-set is that have in described first group of data and described second group of data
Set that first data of same characteristic features and the second data are compared one by one so that in described first group of data multiple first
Multiple second data in data and described second group of data when not possessing same characteristic features, that is, show the plurality of first data
It is 0 with the similarity of the plurality of second data, thus need not the plurality of first data and the plurality of second data carry out
Calculating, thus solving existing electronic equipment when carrying out a large amount of two tuple data Similarity Measure, existing computationally intensive, meter
The technical problem of evaluation time length, and then achieve described electronic equipment when carrying out a large amount of two tuple data Similarity Measure, have
Effect reduces amount of calculation so that the technique effect that reduces of the time of calculating, and then is user-friendly to so that the experience of user is more preferable.
In order to be better understood from technique scheme, below in conjunction with Figure of description and specific embodiment to upper
State technical scheme to be described in detail.
The application one embodiment provides a kind of method of information processing, is applied in electronic equipment, described electronic equipment
The e.g. electronic equipment such as panel computer, smart mobile phone, notebook computer.
Refer to Fig. 1, methods described includes：
Step 101：Obtain the storage of described electronic equipment has first group of data of N number of first data and with described first
The corresponding second group of data with M the second data of group data, wherein, each of described N number of first data first number
According at least including first parameter value corresponding with the first parameter and second parameter value corresponding with the second parameter, described M second
Each of data second data at least include threeth parameter value corresponding with described first parameter and with described second parameter
Corresponding 4th parameter value, N and M is the integer not less than 2；
Step 102：Pre-conditioned based on related to first and second parameter described first, from described first group of data and
Described second group of extracting data includes at least two group two tuple-set of the one or two tuple-set and the two or two tuple-set,
Wherein, described one or two tuple-set is that will have fisrt feature corresponding with described first parameter in described first group of data
There is in each of K the first data the first data and described second group of data L the second data of described fisrt feature
Each of the set of two tuples compared one by one of the second data, described two or two tuple-set is by described first group
There is in data each of Q first data of second feature corresponding with described second parameter the first data and described the
There are in two groups of data two tuples that each of P the second data of described second feature the second data is compared one by one
Set, K, L, Q and P are the integer not less than 1；
Step 103：Based on preset rules, from described at least two group two tuple-set, obtain first group of two tuple set
Close, wherein, each of described first group of two tuple-set two tuples are different from；
Step 104：The first data at least in each of two groups of binary set two tuple and the second data described in acquisition
Multiple first Similarity value.
Wherein, in a step 101, obtain the storage of described electronic equipment have N number of first data first group of data and
The second group data with M second data corresponding with described first group of data, wherein, every in described N number of first data
One the first data at least includes first parameter value corresponding with the first parameter and second parameter value corresponding with the second parameter, institute
State each of M the second data the second data at least include threeth parameter value corresponding with described first parameter and with described
Corresponding 4th parameter value of second parameter, N and M is the integer not less than 2.
In specific implementation process, need to being stored in described electronic equipment or the outer storage connecting in described electronic equipment
When first group of data in unit and second group of data are calculated, obtain described first group of data in N number of first data and
Obtain M the second data in described second group of data.
In actual application, it is stored with two in the hard disk of described notebook computer taking notebook computer as a example
First group of data of dimension coordinate system mark and second group of data, so so that described first parameter is X-axis, described second parameter
For Y-axis, obtain N number of first data in described first group of data be（0,1）,（1,2）,（3,0）,（2,0）, obtain described the
M in two groups of data the second data be（Isosorbide-5-Nitrae）,（0,3）,（5,0）,（0,4）}；In addition, described first parameter can also be
The first-level class of commodity, described second parameter is the secondary classification of commodity, for example：N number of first number in described first group of data
According to for（Electronics, mobile phone）,（Electronics, panel computer）,（Electronics, desktop computer）,（Clothing, cold-proof underwear）, described second group
In data, M the second data is（Electronics, flat panel TV）,（Electronics, water heater）,（Electronics, refrigerator）,（Clothing, down jackets）}.
Next execution step 102, in this step, based on the related to first and second parameter described first default bar
Part, includes the one or two tuple-set and the two or two tuple-set from described first group of data and described second group of extracting data
At least two group two tuple-set, wherein, described one or two tuple-set is that to have in described first group of data and described
Have described in each of K the first data of the corresponding fisrt feature of one parameter the first data and described second group of data
The set of two tuples that each of L the second data of fisrt feature the second data is compared one by one, the described 2nd 2
Tuple-set is by Q first data in described first group of data with second feature corresponding with described second parameter
In each first data and described second group of data, there is each of P second data of described second feature second number
According to the set of two tuples being compared one by one, K, L, Q and P are the integer not less than 1.
Wherein, because described K the first data is to obtain from described first group of data, therefore, K is no more than N
Integer；Because described L the second data is to obtain from described second group of data, therefore, L is the no more than integer of M；With
Reason, Q is the no more than integer of N, and P is the no more than integer of M.
In specific implementation process, described pre-conditioned based on related to first and second parameter described first, from institute
State first group of data and described second group of extracting data includes the one or two tuple-set and the two or two tuple-set at least
Two group of two tuple-set, specifically includes：Preset based on the described first first related to described first parameter in pre-conditioned
Sub- condition, from described first group of data and the one or two tuple-set described in described second group of extracting data；Based on described first
Second related to described second parameter in pre-conditioned presets sub- condition, from described first group of data and described second group of number
According to described two or two tuple-set of middle extraction.
Specifically, preset sub- condition based on described first, have described first from described N number of first extracting data special
K the first data levied, and there is L the second data of described fisrt feature from described M the second extracting data, by institute
State each of K the first data the first data to be matched with each of described L the second data the second data respectively,
Will obtain thus pairing be indicated in the way of two tuples, thus obtaining the one or two tuple-set.
In specific implementation process, when described first parameter is the first axle in the first coordinate system, described based on described
First pre-conditioned in first related to described first parameter preset sub- condition, from described first group of data and described second
One or two tuple-set described in group extracting data, specially：Existed based on each of described first group of data the first data
When numerical value in described first axle is zero, obtain the institute for non-zero for the numerical value in described first axle in described first group of data
State K the first data, wherein, described numerical value in described first axle is non-zero as described fisrt feature；And be based on
When each of described second group of data numerical value in described first axle for second data is zero, obtain described second group of data
In the numerical value in described first axle be non-zero described L the second data；Based on described K the first data and described L
Second data, obtains described one or two tuple-set, and wherein, described one or two tuple-set is by described K the first data
The collection of two tuples that compared one by one of each of each first data and described L the second data the second data
Close.
Specifically, each of described first group of data number in described first axle for first data can be obtained first
Value is zero A the first data, and wherein, A is the integer not less than 0, then gets rid of described A from described N number of first data is red
First data it is possible to obtain described K the first data, wherein, A+K=N, such as：In described first group of data N number of first
Data be（0,1）,（1,2）,（3,0）,（2,0）, then described A the first data be（0,1）, then from described N number of first number
According in get rid of described A the first data be obtained with described K the first data be（1,2）,（3,0）,（2,0）}；Certainly
Can also directly by described N number of first data, the numerical value in described first axle be that 0 at least one first data is carried
Take, then will extract described at least one first data as described K the first data.
In the same manner it is also possible to obtain each of described second group of data numerical value in described first axle for second data first
It is zero B the second data, wherein, B is the integer not less than 0, then get rid of described B the from described M the second data is red
Two data it is possible to obtain described L the first data, wherein, B+K=M, such as：M the second data in described second group of data
For（Isosorbide-5-Nitrae）,（0,3）,（5,0）,（0,4）, then described B the second data be（0,3）,（0,4）, then from described M second
Get rid of in data described B the second data be obtained with described L the second data be（Isosorbide-5-Nitrae）,（5,0）}；Certainly also may be used
Directly to be extracted at least one second data that individual for described M numerical value in described first axle for second data is not 0, then
Described in extracting, at least one second data is as described L the second data.
In actual application, with above-mentioned two-dimensional coordinate system mark first group of data and second group of data instance, by
It is X-axis in described first parameter, then described first axle is X-axis, obtain each of described first group of data the first data in X
Numerical value on axle be zero data be（0,1）, obtaining the numerical value in X-axis in described first group of data is described in non-zero
K the first data be（1,2）,（3,0）,（2,0）}；In the same manner, based on each of described second group of data the second data in X
When on axle, numerical value is zero, described L the second data be（Isosorbide-5-Nitrae）,（5,0）, based on described K the first data and described L the
Two data, then described one or two tuple-set be [（1,2）,（Isosorbide-5-Nitrae）], [（1,2）,（5,0）], [（3,0）,（Isosorbide-5-Nitrae）], [（3,
0）,（5,0）], [（2,0）,（Isosorbide-5-Nitrae）], [（2,0）,（5,0）]}.
In specific implementation process, it is different from described first axle in described first coordinate system in described second parameter
During the second axle, described second related to described second parameter based on described first in pre-conditioned presets sub- condition, from institute
State first group of data and the one or two tuple-set described in described second group of extracting data, specially：Based on described first group of number
According to each of numerical value on described second axle for first data be zero when, obtain in described first group of data described the
Numerical value on two axles is described Q first data of non-zero, wherein, described numerical value on described second axle is non-zero as
Described second feature；And the numerical value on described second axle is zero based on each of described second group of data the second data
When, obtain described P the second data that the numerical value on described second axle in described second group of data is non-zero；Based on described
Q the first data and described P the second data, obtain described two or two tuple-set, wherein, described two or two tuple-set is
Each of described Q the first data the first data is carried out one with each of described P the second data the second data
The set of one two tuples comparing.
Specifically, number on described second axle for each of described first group of data the first data can be obtained first
Value is zero C the first data, and wherein, C is the integer not less than 0, then gets rid of described C from described N number of first data is red
First data it is possible to obtain described Q the first data, wherein, C+Q=N, such as：In described first group of data N number of first
Data be（0,1）,（1,2）,（3,0）,（2,0）, then described C the first data be（3,0）,（2,0）, then from described N number of
Get rid of in first data described C the first data be obtained with described Q the first data be（0,1）,（1,2）}；Certainly
Can also directly by described N number of first data, the numerical value on described second axle be that 0 at least one first data is carried
Take, then will extract described at least one first data as described Q the first data.
In the same manner it is also possible to obtain numerical value on described second axle for each of described second group of data the second data first
It is zero D the second data, wherein, D is the integer not less than 0, then get rid of described D the from described M the second data is red
Two data it is possible to obtain described P the first data, wherein, D+P=M, such as：M the second data in described second group of data
For（Isosorbide-5-Nitrae）,（0,3）,（5,0）,（0,4）, then described B the second data be（5,0）, then from described M the second data
Get rid of described D the second data be obtained with described P the second data be（Isosorbide-5-Nitrae）,（0,3）,（0,4）}；Certainly also may be used
Directly to be extracted at least one second data that individual for described M numerical value in described first axle for second data is not 0, then
Described in extracting, at least one second data is as described P the second data.
In actual application, with above-mentioned two-dimensional coordinate system mark first group of data and second group of data instance, by
It is Y-axis in described second parameter, then described second axle is Y-axis, obtain each of described first group of data the first data in Y
Numerical value on axle be zero data be（3,0）,（2,0）, obtaining the numerical value in Y-axis in described first group of data is non-zero
Described Q the first data be（0,1）,（1,2）}；In the same manner, based on each of described second group of data the second data in Y
When on axle, numerical value is zero, described P the second data be（Isosorbide-5-Nitrae）,（0,3）,（0,4）, based on described Q the first data and described
P the second data, then described two or two tuple-set be [（0,1）,（Isosorbide-5-Nitrae）], [（0,1）,（0,3）], [（0,1）,（0,4）],
[（1,2）,（Isosorbide-5-Nitrae）], [（1,2）,（0,3）], [（1,2）,（0,4）]}.
Next execution step 103, in this step, based on preset rules, from described at least two group two tuple-set
First group of two tuple-set of middle acquisition, wherein, each of described first group of two tuple-set two tuples are different from.In tool
In body implementation process, described at least each of two group of two tuple-set two tuple can be compared, such that it is able to go
Two tuples repeating at least two group two tuple-set described in removing；It is, of course, also possible to first take described at least two 2 tuple set
The three or two tuple-set in conjunction, in the residue removing described three or two tuple-set from described at least two second tuple-sets
Two tuple-sets in choose at least one two tuples different from each of described three or two tuple-set two tuples and add
Enter in described three or two tuple-set, thus obtaining described first group of two tuple-set, wherein, described three or two tuple can be
Described one or two tuple-set or described two or two tuple-set.
In actual application, with above-mentioned two-dimensional coordinate system mark first group of data and second group of data instance, by
It is described one or two tuple-set and described two or two tuple-set in described at least two 2 tuple-sets, the described 3rd 2
Tuple-set be described first tuple-set when, described first group of two tuple-set include [（1,2）,（Isosorbide-5-Nitrae）], [（1,2）,
（5,0）], [（3,0）,（Isosorbide-5-Nitrae）], [（3,0）,（5,0）], [（2,0）,（Isosorbide-5-Nitrae）], [（2,0）,（5,0）], due to described second
In binary set [（0,1）,（Isosorbide-5-Nitrae）], [（0,1）,（0,3）], [（0,1）,（0,4）], [（1,2）,（Isosorbide-5-Nitrae）], [（1,2）,（0,
3）], [（1,2）,（0,4）] at least one two tuple of being different from each of described one or two tuple-set two tuples
For [（0,1）,（Isosorbide-5-Nitrae）], [（0,1）,（0,3）], [（0,1）,（0,4）], [（1,2）,（0,3）], [（1,2）,（0,4）], then
Described first group of two tuple-set be [（1,2）,（Isosorbide-5-Nitrae）], [（1,2）,（5,0）], [（3,0）,（Isosorbide-5-Nitrae）], [（3,0）,（5,
0）], [（2,0）,（Isosorbide-5-Nitrae）], [（2,0）,（5,0）], [（0,1）,（Isosorbide-5-Nitrae）], [（0,1）,（0,3）], [（0,1）,（0,4）],
[（1,2）,（0,3）], [（1,2）,（0,4）]}.
Due to only identical by having in described first group of data and described second group of data in described one or two tuple-set
Multiple first data of feature and multiple second data are compared one by one, and not to described first group of data and described second group
There is no in data the first data of same characteristic features and the second data is compared, this is because not having the of same characteristic features
Similarity between one data and the second data is 0, such that it is able to without being calculated, compared with prior art such that it is able to
Effectively reduce amount of calculation, such as：With first group of data of above-mentioned two-dimensional coordinate system mark with during second group of data instance, described the
One group of two tuple-set only needs to 11 two tuples are calculated, and then needs to carry out to 16 two tuples by common practice
Calculated, when the data volume of M and N is big such that it is able to effectively reduce amount of calculation, shortened the time calculating, and then convenient use
Family is using so that the experience of user is more preferable.
Next execution step 104, in this step, in each of described first group of two tuple-set two tuples
The first data and the second data carry out Similarity Measure, obtain multiple first phases corresponding with described first group of two tuple-set
Like angle value.
In specific implementation process, after get described first group of two tuple-set by step 103, can adopt
The similarity algorithms such as included angle cosine come to the first data in each of described first group of two tuple-set two tuples and
Two data carry out Similarity Measure, thus obtaining corresponding multiple with each of described first group of two tuple-set two tuples
First Similarity value, wherein, the span of described first Similarity value can be determined based on described similarity algorithm, also
The span of described first Similarity value can be specified the numerical value between 0-1 or 0-100.
Specifically, with first group of data of above-mentioned two-dimensional coordinate system mark and second group of data instance, due to described the
One group of two tuple-set be [（1,2）,（Isosorbide-5-Nitrae）], [（1,2）,（5,0）], [（3,0）,（Isosorbide-5-Nitrae）], [（3,0）,（5,0）], [（2,
0）,（Isosorbide-5-Nitrae）], [（2,0）,（5,0）], [（0,1）,（Isosorbide-5-Nitrae）], [（0,1）,（0,3）], [（0,1）,（0,4）], [（1,2）,（0,
3）], [（1,2）,（0,4）], then need to carry out Similarity Measure to each of described first group of two tuple-set two tuples,
Quantity due to two tuples in described first group of two tuple is 11, then the plurality of first Similarity value is 11 the first phases
Like angle value, and prior art is due to there being 4 the first data in described first group of data, and described second group of data has 4 second
Data, then having 16 two tuples needs to carry out Similarity Measure, so that can be effective using presently filed embodiment
Reduce amount of calculation, and then reduce the calculating time, thus being user-friendly to so that the experience of user is more preferable.
In actual application, so that similarity algorithm is as included angle cosine as a example, in described first group of two tuple-set
[（1,2）,（Isosorbide-5-Nitrae）] first the first Similarity value be d=(1 × 1+2 × 4）/（sqrt(1×1+2×2)×sqrt(1×1+
4×4)）=0.976, [（1,2）,（5,0）] second the first Similarity value be d2=(1 × 5+2 × 0）/（sqrt(1×1+2×
2)×sqrt(5×5+0×0)）=0.447, [（2,0）,（Isosorbide-5-Nitrae）] the 3rd the first Similarity value be d3=(2 × 1+0 × 4）/
（sqrt(2×2+0×0)×sqrt(1×1+4×4)）=0.243 etc., because the bigger similarity of included angle cosine intermediate value is higher, because
This, in above-mentioned 3 two tuples [（1,2）,（Isosorbide-5-Nitrae）] similarity highest, [（1,2）,（5,0）] similarity be in second
Position, [（2,0）,（Isosorbide-5-Nitrae）] similarity minimum.
In another embodiment, described to the first number in each of described first group of two tuple-set two tuples
During according to carrying out Similarity Measure with the second data, being based on MapReduce or similar parallel computation frame, setting multiple respectively
Standby being above compared calculates such that it is able to effectively improve computational efficiency, reduces the calculating time further.
In another embodiment, described to the first number in each of described first group of two tuple-set two tuples
Carry out Similarity Measure according to the second data, obtain multiple first Similarity value corresponding with described first group of two tuple-set it
Afterwards, methods described includes：Based on the plurality of first Similarity value, each of described second group of data the second data is pressed
Preset strategy is ranked up with each of described first group of data the first data.
Specifically, so that similarity algorithm is as included angle cosine as a example, when span is -1-1, due in included angle cosine
Similarity value is higher, and the similarity between its corresponding two data is also higher, with specific reference to the embodiment of above-mentioned included angle cosine,
Succinct for description, here is not just repeating.
In another embodiment, due to during obtaining described first group of two tuple-set, middle two tuples
Data volume is generally very big, and two tuples of described centre include described one or two tuple-set and described two or two tuple-set, are
Reduce the data volume of the loading in calculating process, two middle tuples are only retained to the ID of each data, and data is filled
It is loaded in external storage, only read in data in actual Similarity Measure step, to reduce the expense of I/O.
In actual application, such as described N number of first data is { a taking above-mentioned notebook computer as a example（0,1）, b
（1,2）, c（3,0）, d（2,0）, described M the second data is { e（Isosorbide-5-Nitrae）, f（0,3）, g（5,0）, h（0,4）, then described
One or two tuple-sets be [（1,2）,（Isosorbide-5-Nitrae）], [（1,2）,（5,0）], [（3,0）,（Isosorbide-5-Nitrae）], [（3,0）,（5,0）], [（2,
0）,（Isosorbide-5-Nitrae）], [（2,0）,（5,0）] when, when described one or two tuple-set is indicated with ID be（B, e）,（B, g）,（C,
e）,（C, g）,（D, e）,（D, g）, so that reducing the data volume of the loading in calculating process.
Below again for an embodiment, when described first group of data to be identified with three-dimensional coordinate, in described first group of data
N number of first data be（0,1,2）,（1,0,3）,（3,2,0）, M in described second group of data the second data be（0,3,
1）,（2,0,4）,（4,3,0）, during based on numerical value in X-axis for the described data for 0, then described K the first data is (1,0,3）
With（3,2,0）, described L the second data is（2,0,4）,（4,3,0）；During based on numerical value in Y-axis for the described data for 0, institute
Stating Q the first data is（0,1,2）,（3,2,0）, described P the second data is（0,3,1）,（4,3,0）；Based on described data
When numerical value on Z axis is 0, described W the first data is（0,1,2）,（1,0,3）, described S the second data is（0,3,1）,
（2,0,4）, then described at least two 2 tuple-sets include the one or two tuple-set and the two or two tuple-set and the 3rd binary
Group set, then it is based on described one or two tuple-set and described two or two tuple-set and described three or two tuple-set, extract
Described first group of two tuple-set, then corresponding with described first group of two tuple-set by similarity calculating method acquisition
Multiple first Similarity value.
The one or more technical schemes providing in the embodiment of the present application, at least have the following technical effect that or advantage：
One, due to the embodiment of the present application be pre-conditioned based on related to first and second parameter described first,
Include the one or two tuple-set and the two or two tuple-set from described first group of data and described second group of extracting data
At least two group two tuple-set, based on preset rules, obtains first group of two tuple from described at least two group two tuple-set
Set, wherein, each of described first group of two tuple-set two tuples are different from, then based at least two groups described in acquisition
The first data in each of binary set two tuple and multiple first Similarity value of the second data, obtain described first group
Each of data first data and each of described second group of data the second data and the plurality of first similarity
It is worth corresponding multiple first matching value, because described one or two tuple-set is described first group of data and described second group of data
In there is the first data of same characteristic features and set that the second data is compared one by one is so that many in described first group of data
Multiple second data in individual first data and described second group of data when not possessing same characteristic features, that is, show the plurality of the
The similarity of one data and the plurality of second data is 0, thus need not the plurality of first data and the plurality of second number
According to being calculated, thus solving existing electronic equipment when carrying out a large amount of two tuple data Similarity Measure, there is calculating
Measure the technical problem calculating greatly time length, and then achieve described electronic equipment and carry out a large amount of two tuple data similarity meters
During calculation, effectively reduce amount of calculation so that the technique effect that reduces of the time of calculating, and then be user-friendly to the body so that user
Test more preferably.
Two, because the embodiment of the present application is based on preset rules, obtain from described at least two group two tuple-set
First group of two tuple-set, wherein, each of described first group of two tuple-set two tuples are different from, then again to institute
State the first data in each of first group of two tuple-set two tuple and the second data carry out Similarity Measure, obtain with
Corresponding multiple first similarities of described first group of two tuple-set are so as at least two group two tuple set described in effective removal
Identical two tuple in conjunction, reduces the quantity of calculative two tuples, reduces amount of calculation so that the calculating time enters further
The minimizing of one step, and then be user-friendly to so that the experience of user is more preferable.
Three, because the embodiment of the present application is after obtaining the plurality of first matching value, based on the plurality of first
Join value, each of described second group of data the second data is pressed each of preset strategy and described first group of data the
One data is ranked up, such that it is able to by each of described second group of data the second data and described first group of data
Each first data according to matching value from big to small in being sorted successively so that user has more intuitive impression, thus side
Just user checked so that the experience of user more preferable.
The application one embodiment provides a kind of electronic equipment, described electronic equipment be, for example, panel computer, smart mobile phone,
Notebook computer, the electronic equipment such as desktop computer.
Referring to Fig. 2, this electronic equipment includes acquiring unit 201, has N number of for obtain the storage of described electronic equipment
First group of data of one data and the second group data with M second data corresponding with described first group of data, wherein, institute
State each of N number of first data the first data at least include first parameter value corresponding with the first parameter and with the second parameter
Corresponding second parameter value, each of described M second data the second data at least includes corresponding with described first parameter
The 3rd parameter value and fourth parameter value corresponding with described second parameter, N and M is the integer not less than 2；
Extraction unit 202, pre-conditioned based on related to first and second parameter described first, for from described first
Organize data and described second group of extracting data includes at least two group two of the one or two tuple-set and the two or two tuple-set
Tuple-set, wherein, described one or two tuple-set is corresponding with described first parameter by having in described first group of data
There is in each of K the first data of fisrt feature the first data and described second group of data the L of described fisrt feature
The set of two tuples that each of individual second data the second data is compared one by one, described two or two tuple-set be by
There is in described first group of data each of Q first data of second feature corresponding with described second parameter first number
According to described second group of data in have each of P second data of described second feature the second data one by one than
The set of two tuples relatively, K, L, Q and P are the integer not less than 1；
Screening unit 203, based on preset rules, for obtaining first group two from described at least two group two tuple-set
Tuple-set, wherein, each of described first group of two tuple-set two tuples are different from；
Computing unit 204, the first data and second at least in each of two groups of binary set two tuple described in acquisition
Multiple first Similarity value of data.
Further, extraction unit 202, specifically for：Based on described first in pre-conditioned with described first parameter
Related first presets sub- condition, for from described first group of data and the one or two tuple described in described second group of extracting data
Set, based on the default sub- condition of the described first second related to described second parameter in pre-conditioned, for from described the
One group of data and the two or two tuple-set described in described second group of extracting data.
Further, extraction unit 202 includes the first extraction subelement, is in the first coordinate system in described first parameter
During first axle, when being zero based on each of described first group of data numerical value in described first axle for first data, it is used for
Obtain described K the first data that the numerical value in described first axle in described first group of data is non-zero, wherein, will be described
Numerical value in described first axle be non-zero as described fisrt feature, and based on each of described second group of data the
When numerical value in described first axle for two data is zero, for obtaining the number in described first axle in described second group of data
It is worth described L the second data for non-zero, based on described K the first data and described L the second data, for obtaining described the
One or two tuple-sets, wherein, described one or two tuple-set is by each of described K the first data the first data and institute
State the set of two tuples that each of L the second data the second data is compared one by one.
Further, extraction unit 202 includes the second extraction subelement, is described first coordinate system in described second parameter
In different from described first axle the second axle when, based on each of described first group of data the first data described second
When numerical value on axle is zero, for obtaining the described Q that the numerical value on described second axle in described first group of data is non-zero
Individual first data, wherein, using described numerical value on described second axle be non-zero as described second feature, and based on described
When numerical value on described second axle for each of second group of data second data is zero, for obtaining described second group of data
In the numerical value on described second axle be non-zero described P the second data, based on described Q the first data and described P
Second data, for obtaining described two or two tuple-set, wherein, described two or two tuple-set is by described Q first number
According to each of each of the first data and described P the second data the second data two tuples of being compared one by one
Set.
In another embodiment, described electronic equipment also includes sequencing unit, described to described first group of two tuple set
The first data in each of conjunction two tuples and the second data carry out Similarity Measure, obtain and described first group of two tuple
After gathering corresponding multiple first Similarity value, based on the plurality of first Similarity value, for by described second group of data
Each of the second data be ranked up with each of described first group of data the first data by preset strategy.
The one or more technical schemes providing in the embodiment of the present application, at least have the following technical effect that or advantage：
One, due to the embodiment of the present application be pre-conditioned based on related to first and second parameter described first,
Include the one or two tuple-set and the two or two tuple-set from described first group of data and described second group of extracting data
At least two group two tuple-set, based on preset rules, obtains first group of two tuple from described at least two group two tuple-set
Set, wherein, each of described first group of two tuple-set two tuples are different from, then based at least two groups described in acquisition
The first data in each of binary set two tuple and multiple first Similarity value of the second data, obtain described first group
Each of data first data and each of described second group of data the second data and the plurality of first similarity
It is worth corresponding multiple first matching value, because described one or two tuple-set is described first group of data and described second group of data
In there is the first data of same characteristic features and set that the second data is compared one by one is so that many in described first group of data
Multiple second data in individual first data and described second group of data when not possessing same characteristic features, that is, show the plurality of the
The similarity of one data and the plurality of second data is 0, thus need not the plurality of first data and the plurality of second number
According to being calculated, thus solving existing electronic equipment when carrying out a large amount of two tuple data Similarity Measure, there is calculating
Measure the technical problem calculating greatly time length, and then achieve described electronic equipment and carry out a large amount of two tuple data similarity meters
During calculation, effectively reduce amount of calculation so that the technique effect that reduces of the time of calculating, and then be user-friendly to the body so that user
Test more preferably.
Two, because the embodiment of the present application is based on preset rules, obtain from described at least two group two tuple-set
First group of two tuple-set, wherein, each of described first group of two tuple-set two tuples are different from, then again to institute
State the first data in each of first group of two tuple-set two tuple and the second data carry out Similarity Measure, obtain with
Corresponding multiple first similarities of described first group of two tuple-set are so as at least two group two tuple set described in effective removal
Identical two tuple in conjunction, reduces the quantity of calculative two tuples, reduces amount of calculation so that the calculating time enters further
The minimizing of one step, and then be user-friendly to so that the experience of user is more preferable.
Three, because the embodiment of the present application is after obtaining the plurality of first matching value, based on the plurality of first
Join value, each of described second group of data the second data is pressed each of preset strategy and described first group of data the
One data is ranked up, such that it is able to by each of described second group of data the second data and described first group of data
Each first data according to matching value from big to small in being sorted successively so that user has more intuitive impression, thus side
Just user checked so that the experience of user more preferable.
Although preferred embodiments of the present invention have been described, but those skilled in the art once know basic creation
Property concept, then can make other change and modification to these embodiments.So, claims are intended to be construed to including excellent
Select embodiment and fall into being had altered and changing of the scope of the invention.
Obviously, those skilled in the art can carry out the various changes and modification essence without deviating from the present invention to the present invention
God and scope.So, if these modifications of the present invention and modification belong to the scope of the claims in the present invention and its equivalent technologies
Within, then the present invention is also intended to comprise these changes and modification.
Claims (10)
1. a kind of method of information processing, is applied in electronic equipment it is characterised in that methods described includes：
Obtain the storage of described electronic equipment has first group of data of N number of first data and corresponding with described first group of data
There is second group of data of M the second data, wherein, each of described N number of first data the first data at least include with
Corresponding first parameter value of first parameter and second parameter value corresponding with the second parameter, each in described M the second data
Individual second data at least includes threeth parameter value corresponding with described first parameter and fourth ginseng corresponding with described second parameter
Numerical value, N and M is the integer not less than 2；
Pre-conditioned based on related to first and second parameter described first, from described first group of data and described second group of number
Include at least two group two tuple-set of the one or two tuple-set and the two or two tuple-set according to middle extraction, wherein, described
One or two tuple-sets are that to have K the first data of fisrt feature corresponding with described first parameter in described first group of data
Each of there is in the first data and described second group of data each of L second data of described fisrt feature the
The set of two tuples that two data are compared one by one, described two or two tuple-set be by have in described first group of data with
Have in each of Q the first data of the corresponding second feature of described second parameter the first data and described second group of data
There are the set of two tuples that each of P second data of described second feature the second data compared one by one, K, L, Q
It is all the integer not less than 1 with P；
Based on preset rules, from described at least two group two tuple-set, obtain first group of two tuple-set, wherein, described
Each of one group of two tuple-set two tuple is different from；
Similarity meter is carried out to the first data in each of described first group of two tuple-set two tuples and the second data
Calculate, obtain multiple first Similarity value corresponding with described first group of two tuple-set.
2. the method for claim 1 it is characterised in that described based on related to first and second parameter described first
Pre-conditioned, include the one or two tuple-set and the second binary from described first group of data and described second group of extracting data
At least two group two tuple-set of group set, specifically includes：
Sub- condition is preset based on the described first first related to described first parameter in pre-conditioned, from described first group of number
According to the one or two tuple-set described in described second group of extracting data；
Sub- condition is preset based on the described first second related to described second parameter in pre-conditioned, from described first group of number
According to the two or two tuple-set described in described second group of extracting data.
3. method as claimed in claim 2 is it is characterised in that be the first axle in the first coordinate system in described first parameter
When, described first related to described first parameter based on described first in pre-conditioned presets sub- condition, from described first
Group data and the one or two tuple-set described in described second group of extracting data, specially：
When being zero based on each of described first group of data numerical value in described first axle for first data, obtain described the
The numerical value in described first axle in one group of data is described K the first data of non-zero, wherein, by described described first
Numerical value on axle is non-zero as described fisrt feature；And
When being zero based on each of described second group of data numerical value in described first axle for second data, obtain described the
The numerical value in described first axle in two groups of data is described L the second data of non-zero；
Based on described K the first data and described L the second data, obtain described one or two tuple-set, wherein, described first
Two tuple-sets are by each of each of described K the first data the first data and described L second data the
The set of two tuples that two data are compared one by one.
4. method as claimed in claim 2 is it is characterised in that be in the first coordinate system and first axle in described second parameter
During different second axle, described second related to described second parameter based on described first in pre-conditioned presets sub- bar
Part, from described first group of data and the two or two tuple-set described in described second group of extracting data, specially：
When being zero based on numerical value on described second axle for each of described first group of data the first data, obtain described the
The numerical value on described second axle in one group of data is described Q the first data of non-zero, wherein, by described described second
Numerical value on axle is non-zero as described second feature；And
When being zero based on numerical value on described second axle for each of described second group of data the second data, obtain described the
The numerical value on described second axle in two groups of data is described P the second data of non-zero；
Based on described Q the first data and described P the second data, obtain described two or two tuple-set, wherein, described second
Two tuple-sets are by each of each of described Q the first data the first data and described P second data the
The set of two tuples that two data are compared one by one.
5. the method for claim 1 is it is characterised in that described to each of described first group of two tuple-set
The first data in two tuples and the second data carry out Similarity Measure, obtain corresponding many with described first group of two tuple-set
After individual first Similarity value, methods described includes：
Based on the plurality of first Similarity value, each of described second group of data the second data is pressed preset strategy and institute
State each of first group of data first data to be ranked up.
6. a kind of electronic equipment is it is characterised in that described electronic equipment includes：
Acquiring unit, has first group of data of N number of first data and with described for obtain the storage of described electronic equipment
The corresponding second group of data with M the second data of one group of data, wherein, each of described N number of first data first
Data at least includes first parameter value corresponding with the first parameter and second parameter value corresponding with the second parameter, described M the
Each of two data second data at least includes threeth parameter value corresponding with described first parameter and joins with described second
Corresponding 4th parameter value of number, N and M is the integer not less than 2；
Extraction unit, pre-conditioned based on related to first and second parameter described first, for from described first group of data
Include at least two group two tuple set of the one or two tuple-set and the two or two tuple-set with described second group of extracting data
Close, wherein, described one or two tuple-set is special by having corresponding with described first parameter first in described first group of data
There is in each of K the first data levied the first data and described second group of data L second of described fisrt feature
The set of two tuples that each of data second data is compared one by one, described two or two tuple-set is by described
There is in one group of data each of Q the first data of second feature corresponding with described second parameter the first data and institute
State have in second group of data that each of P second data of described second feature the second data is compared one by one two
The set of tuple, K, L, Q and P are the integer not less than 1；
Screening unit, based on preset rules, for obtaining first group of two tuple set from described at least two group two tuple-set
Close, wherein, each of described first group of two tuple-set two tuples are different from；
Computing unit, is carried out to the first data in each of described first group of two tuple-set two tuples and the second data
Similarity Measure, obtains multiple first Similarity value corresponding with described first group of two tuple-set.
7. electronic equipment as claimed in claim 6 is it is characterised in that described extraction unit, specifically for：Based on described first
First related to described first parameter in pre-conditioned presets sub- condition, for from described first group of data and described second
One or two tuple-set described in group extracting data, based on described first in pre-conditioned related to described second parameter the
Two preset sub- condition, for from described first group of data and the two or two tuple-set described in described second group of extracting data.
8. electronic equipment as claimed in claim 7 is it is characterised in that described extraction unit includes the first extraction subelement,
When described first parameter is the first axle in the first coordinate system, based on each of described first group of data the first data in institute
When the numerical value stated in first axle is zero, it is non-zero for obtaining the numerical value in described first axle in described first group of data
Described K the first data, wherein, described numerical value in described first axle is non-zero as described fisrt feature, Yi Jiji
When each of described second group of data numerical value in described first axle for second data is zero, for obtaining described second
The numerical value in described first axle in group data is described L the second data of non-zero, based on described K the first data and institute
State L the second data, for obtaining described one or two tuple-set, wherein, described one or two tuple-set is by described K the
The binary that each of one data first data is compared one by one with each of described L the second data the second data
The set of group.
9. electronic equipment as claimed in claim 7 is it is characterised in that described extraction unit includes the second extraction subelement,
When described second parameter is different from first axle the second axle in the first coordinate system, based on each in described first group of data
When numerical value on described second axle for individual first data is zero, for obtain in described first group of data in described second axle
Numerical value be non-zero described Q the first data, wherein, described numerical value on described second axle is non-zero as described the
Two features, and when based on each of described second group of data the second data, the numerical value on described second axle is zero, use
In obtaining the described P that the numerical value on described second axle in described second group of data is non-zero the second data, based on described Q
Individual first data and described P the second data, for obtaining described two or two tuple-set, wherein, described two or two tuple set
It is combined into and each of described Q the first data the first data is entered with each of described P the second data the second data
The set of two tuples that row compares one by one.
10. electronic equipment as claimed in claim 6 is it is characterised in that described electronic equipment also includes sequencing unit, described
Similarity Measure is carried out to the first data in each of described first group of two tuple-set two tuples and the second data, obtains
After taking multiple first Similarity value corresponding with described first group of two tuple-set, based on the plurality of first Similarity value,
For each of described second group of data the second data is pressed each of preset strategy and described first group of data the
One data is ranked up.
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| CN102915295A (en) * | 2011-03-31 | 2013-02-06 | 百度在线网络技术（北京）有限公司 | Document detecting method and document detecting device |
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