CN109657069A - The generation method and its device of knowledge mapping - Google Patents
The generation method and its device of knowledge mapping Download PDFInfo
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- CN109657069A CN109657069A CN201811507679.8A CN201811507679A CN109657069A CN 109657069 A CN109657069 A CN 109657069A CN 201811507679 A CN201811507679 A CN 201811507679A CN 109657069 A CN109657069 A CN 109657069A
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Abstract
The invention discloses a kind of generation method of knowledge mapping and its devices.Wherein, method includes: the theme for obtaining knowledge mapping to be generated, obtains multiple initial data from multiple data sources according to theme.Multiple initial data are merged, to obtain fused data.According to fused data, knowledge mapping is generated.The embodiment of the present invention realizes the initial data for making full use of different data sources as a result, avoids when individual data source occurs abnormal and has an impact to knowledge mapping, improves the reliability of knowledge mapping, while also enriching the content of knowledge mapping.It solves in the prior art that data source is single, once data source is abnormal, the knowledge mapping generated is resulted in abnormal technical problem also occur.
Description
Technical field
The present invention relates to technical field of data processing more particularly to the generation methods and its device of a kind of knowledge mapping.
Background technique
Knowledge mapping describes knowledge resource and its carrier with visualization technique, excavates, analysis, constructs, drawing and display is known
Knowledge and connecting each other between them.Along with the development of informationization technology, different knowledge resources are used to the side of knowledge mapping
Formula, which is supplied to user, becomes a kind of new knowledge offer scheme.Realize that the program first has to obtain data information from data source,
Generate knowledge mapping.
In the related technology, data information can be obtained from individual data source and generate knowledge mapping, such as from some than calibrated
True source generates knowledge mapping.But in the prior art, it since data source is single, if the data source is abnormal, will lead to
There is exception in the knowledge mapping of generation, therefore there are hidden danger.Also, the data source in individual data source is limited, also limits and knows
Know the rich of map.
Summary of the invention
The present invention is directed to solve at least some of the technical problems in related technologies.
For this purpose, the first purpose of this invention is to propose a kind of generation method of knowledge mapping, made full use of with realizing
The initial data of different data sources avoids individual data source from having an impact when occurring abnormal to knowledge mapping, improves knowledge graph
The reliability of spectrum enriches the content of knowledge mapping.
Second object of the present invention is to propose a kind of generating means of knowledge mapping.
Third object of the present invention is to propose a kind of computer program product.
Fourth object of the present invention is to propose a kind of non-transitorycomputer readable storage medium.
In order to achieve the above object, first aspect present invention embodiment proposes a kind of generation method of knowledge mapping, comprising: obtain
Take the theme of knowledge mapping to be generated；Multiple initial data are obtained from multiple data sources according to the theme；To the multiple original
Beginning data are merged, to obtain fused data；According to the fused data, the knowledge mapping is generated.
Compared to the prior art, the embodiment of the present invention obtains multiple originals from multiple data sources according to the theme of knowledge mapping
Beginning data enrich the content of knowledge mapping.Multiple initial data are merged, to obtain fused data, and are generated with this
Knowledge mapping.The initial data for taking full advantage of different data sources as a result, avoids when individual data source occurs abnormal to knowledge
Map has an impact, and improves the reliability of knowledge mapping, while also enriching the content of knowledge mapping.
In addition, the generation method of the knowledge mapping of the embodiment of the present invention, also has following additional technical characteristic:
Optionally, described that multiple initial data are obtained from multiple data sources according to the theme, comprising: according to the master
Topic determines data attribute relevant to the theme；Multiple originals comprising the data attribute are obtained from the multiple data source
Beginning data.
Optionally, described that the multiple initial data is merged, to obtain fused data, comprising: from the multiple
Multiple raw values of the data attribute are obtained in initial data respectively；The multiple raw value is merged,
To obtain the fused data value of data attribute described in the fused data；According to the data attribute and the fused data
Value, generates the fused data.
Optionally, described that the multiple raw value is merged, to obtain data described in the fused data
The fused data value of attribute, comprising: judge the multiple raw values obtained from the multiple initial data whether phase
Deng；If the multiple raw values obtained from the multiple initial data are equal, the raw value is arranged
For the fused data value；If the multiple raw values obtained from the multiple initial data are unequal, basis
The data source of the initial data determines accuracy rate corresponding to the raw value of each data source respectively；According to institute
It states accuracy rate corresponding to the raw value of each data source and the fused data value is set.
Optionally, the data source according to the initial data determines the initial data of each data source respectively
The corresponding accuracy rate of value, comprising: the accuracy rate of each raw value is determined according to priori knowledge；According to the data
The feature of attribute judges whether the data attribute belongs to dynamic attribute, wherein the dynamic attribute refers to the data attribute
It can dynamic change；If the data attribute belongs to dynamic attribute, further judge the data attribute dynamic change whether
It is legal；If the dynamic change is legal, the accuracy rate of the raw value is modified according to the dynamic change.
Optionally, it is described judge whether the data attribute belongs to dynamic attribute after, further includes: if the data category
Property is not belonging to dynamic attribute, then keeps the accuracy rate of the raw value constant.
Optionally, after whether the dynamic change for judging the data attribute is legal, further includes: if the data
The dynamic change of attribute is illegal, then keeps the accuracy rate of the raw value constant.
Optionally, melt described in the setting of the accuracy rate according to corresponding to the raw value of each data source
Close data value, comprising: select the maximum raw value of the accuracy rate as institute from multiple raw values
State fused data value.
Second aspect of the present invention embodiment proposes a kind of generating means of knowledge mapping, comprising: first obtains module, uses
In the theme for obtaining knowledge mapping to be generated；Second obtains module, multiple for being obtained according to the theme from multiple data sources
Initial data；Fusion Module, for being merged to the multiple initial data, to obtain fused data；Generation module is used for
According to the fused data, the knowledge mapping is generated.
In addition, the generating means of the knowledge mapping of the embodiment of the present invention, also have following additional technical characteristic:
Optionally, described second module is obtained, comprising: submodule is determined, for according to the theme, the determining and master
Inscribe relevant data attribute；First acquisition submodule is more comprising the data attribute for obtaining from the multiple data source
A initial data.
Optionally, the Fusion Module, comprising: the second acquisition submodule, for distinguishing from the multiple initial data
Obtain multiple raw values of the data attribute；Submodule is merged, for being merged to the multiple raw value,
To obtain the fused data value of data attribute described in the fused data；Submodule is generated, for according to the data attribute
With the fused data value, the fused data is generated.
Optionally, the fusion submodule, comprising: judging unit is obtained from the multiple initial data for judging
Multiple raw values it is whether equal；First setting unit, for determining when the judging unit from the multiple original
When the multiple raw values obtained in beginning data are equal, the fused data value is set by the raw value；
Determination unit, for determining the multiple raw values obtained from the multiple initial data not when the judging unit
When equal, according to the data source of the initial data, standard corresponding to the raw value of each data source is determined respectively
True rate；Institute is arranged for the accuracy rate according to corresponding to the raw value of each data source in second setting unit
State fused data value.
Optionally, the determination unit, comprising: determine subelement, it is each described original for being determined according to priori knowledge
The accuracy rate of data value；First judgment sub-unit, for whether judging the data attribute according to the feature of the data attribute
Belong to dynamic attribute, wherein the dynamic attribute refers to that the data attribute can dynamic change；Second judgment sub-unit, is used for
When first judgment sub-unit determines that the data attribute belongs to dynamic attribute, the dynamic of the data attribute is further judged
Whether state variation is legal；Subelement is modified, for when second judgment sub-unit determines that the dynamic change is legal, according to
The dynamic change modifies the accuracy rate of the raw value.
Optionally, the determination unit, further includes: first keeps subelement, true for working as first judgment sub-unit
When the fixed data attribute is not belonging to dynamic attribute, keep the accuracy rate of the raw value constant.
Optionally, the determination unit, further includes: second keeps subelement, true for working as second judgment sub-unit
When the dynamic change of the fixed data attribute is illegal, keep the accuracy rate of the raw value constant.
Optionally, second setting unit, specifically for selecting the accuracy rate from multiple raw values
The maximum raw value is as the fused data value.
Third aspect present invention embodiment proposes a kind of computer program product, when in the computer program product
The generation method of the knowledge mapping as described in preceding method embodiment is realized when instruction processing unit executes.
Fourth aspect present invention embodiment proposes a kind of non-transitorycomputer readable storage medium, is stored thereon with meter
Calculation machine program realizes the generation of the knowledge mapping as described in preceding method embodiment when the computer program is executed by processor
Method.
The additional aspect of the present invention and advantage will be set forth in part in the description, and will partially become from the following description
Obviously, or practice through the invention is recognized.
Detailed description of the invention
Fig. 1 is a kind of flow diagram of the generation method of knowledge mapping provided by the embodiment of the present invention；
Fig. 2 is an exemplary schematic diagram of the generation method of knowledge mapping provided by the embodiment of the present invention；
Fig. 3 is the flow diagram of the generation method of another kind knowledge mapping provided by the embodiment of the present invention；
Fig. 4 is the flow diagram of the generation method of another knowledge mapping provided by the embodiment of the present invention；
Fig. 5 is exemplary schematic diagram when data attribute provided by the embodiment of the present invention is not belonging to dynamic attribute；
Fig. 6 is exemplary schematic diagram when data attribute provided by the embodiment of the present invention belongs to dynamic attribute；
Fig. 7 is exemplary flow chart when data attribute provided by the embodiment of the present invention belongs to dynamic attribute；
Fig. 8 is a kind of structural schematic diagram of the generating means of knowledge mapping provided by the embodiment of the present invention；
Fig. 9 is the structural schematic diagram of the generating means of another kind knowledge mapping provided by the embodiment of the present invention；And
Figure 10 is the structural schematic diagram of the generating means of another knowledge mapping provided by the embodiment of the present invention.
Specific embodiment
The embodiment of the present invention is described below in detail, examples of the embodiments are shown in the accompanying drawings, wherein from beginning to end
Same or similar label indicates same or similar element or element with the same or similar functions.Below with reference to attached
The embodiment of figure description is exemplary, it is intended to is used to explain the present invention, and is not considered as limiting the invention.
Below with reference to the accompanying drawings the generation method and its device of the knowledge mapping of the embodiment of the present invention are described.
Description based on the above-mentioned prior art is it is recognised that in the related technology, since data source is single, if the data source
It is abnormal, exception occurs in the knowledge mapping that will lead to generation, therefore there are hidden danger.Also, the data source in individual data source
It is limited, also limit the rich of knowledge mapping.
For this problem, the embodiment of the invention provides a kind of generation methods of knowledge mapping.It is obtained from multiple data sources
Multiple initial data are taken, multiple initial data are merged, to obtain fused data, and knowledge mapping are generated with this.It improves
The reliability of knowledge mapping, while also enriching the content of knowledge mapping.
Fig. 1 is a kind of flow diagram of the generation method of knowledge mapping provided by the embodiment of the present invention.Such as Fig. 1 institute
Show, method includes the following steps:
S101 obtains the theme of knowledge mapping to be generated.
It is appreciated that knowledge mapping describes data information and its carrier with visualization technique, excavates, analysis, building, draws
And show data and connecting each other between them.Data information in knowledge mapping is shown around a theme
, data information only relevant to the theme can just be put among knowledge mapping.
S102 obtains multiple initial data from multiple data sources according to theme.
Wherein, data source can be communique, topical news, blog, microblogging, public platform.
It is appreciated that the data information substantial amounts that data source generates, only relevant to the theme of knowledge mapping original
Data can just be used to generate knowledge mapping.
For the original number needed for filtering out generation knowledge mapping in the data information for the substantial amounts that data source generates
According to one kind is possible to be achieved in that, according to theme, is determined data attribute relevant to theme, is obtained and wrap from multiple data sources
Multiple initial data containing data attribute.
It should be strongly noted that the data resource in knowledge mapping is shown in the form of data attribute.Such as: know
The theme for knowing map is the personal information of a star, then the height of this star is exactly a number in this knowledge mapping
According to attribute.
It, can also be with it should be understood that the data source in the embodiment of the present invention can be pre-set multiple data sources
It is the multiple data sources automatically determined according to the theme of knowledge mapping by retrieval, screening.
S103 merges multiple initial data, to obtain fused data.
It is appreciated that different initial data same data attribute in different data source, different initial data
Data value may be different, and the data value of data attribute is only in the knowledge mapping generated, it is therefore desirable to original number
According to being merged.
One kind is possible to be achieved in that, is merged according to following steps to multiple initial data:
S1031 obtains multiple raw values of data attribute, S1032, to multiple originals respectively from multiple initial data
Beginning data value is merged, and to obtain the fused data value of data attribute in fused data, S1033 is according to data attribute and fusion
Data value generates fused data.
S104 generates knowledge mapping according to fused data.
It is appreciated that fused data is that multiple initial data fusions obtain later, contain needed for generating knowledge mapping
Different data attribute and its corresponding fused data value, data attribute and its corresponding fused data value are inserted into knowledge graph
Spectrum, to generate knowledge mapping.
In order to clearly illustrate the generation method of knowledge mapping provided by the embodiment of the present invention, illustrate below
Explanation.As shown in Fig. 2, first according to the theme of knowledge mapping to be generated, it is determined that data attribute a, b, c relevant to theme,
D has data source A comprising data attribute a, the initial data of B, C include number in data source A, B, C, the initial data of D, E
There is data source B according to attribute b, the initial data of D, the initial data for having data source D comprising data attribute c includes data category
Property d's has data source D, the initial data of E.
To data source A, the initial data of B, C carry out data fusion to determine the fused data value of data attribute a, to data
The initial data of source B, D carries out data fusion to determine the fused data value of data attribute b, will be in the initial data of data source D
Fused data value of the data value as data attribute c, to data source D, the initial data of E carries out data fusion to determine data
The fused data value of attribute d.By data attribute a, b, c, d and its corresponding fused data value insert knowledge mapping, to generate
Knowledge mapping.
For example, the theme of knowledge mapping to be generated is the personal information of a star, the personal information of the star
Have on website in Baidupedia, microblogging, Eight Diagrams, but content is not quite identical, Baidupedia, microblogging, Eight Diagrams website are exactly
Different data sources.The description of practical height in different data sources about the star is different, and height is exactly data category herein
Property, the height values obtained in different data sources are merged, determine a fused data value, it is bright as this in knowledge mapping
The height values of star.
In conclusion a kind of generation method of knowledge mapping of the embodiment of the present invention, obtains the master of knowledge mapping to be generated
Topic obtains multiple initial data from multiple data sources according to theme.Multiple initial data are merged, to obtain fusion number
According to.According to fused data, knowledge mapping is generated.The initial data for taking full advantage of different data sources as a result, avoids single number
Knowledge mapping is had an impact when occurring abnormal according to source, improves the reliability of knowledge mapping, while also enriching knowledge mapping
Content.
In order to clearly illustrate that how the generation method of knowledge mapping that the embodiment of the present invention is proposed is to multiple
What raw value was merged, the embodiment of the present invention also proposed the generation method of another knowledge mapping, and Fig. 3 is the present invention
The flow diagram of the generation method of another kind knowledge mapping provided by embodiment.As shown in figure 3, S1032, to multiple original
Data value is merged, to obtain the fused data value of data attribute in fused data, comprising:
S201 judges whether the multiple raw values obtained from multiple initial data are equal.
It is appreciated that the multiple raw values obtained from multiple initial data may be essentially equal, it is also possible to endless
It is complete equal, it needs separately to handle different situations.
S202 sets raw value to if the multiple raw values obtained from multiple initial data are equal
Fused data value.
It is appreciated that illustrating the original number of the data attribute from different initial data when multiple raw values are equal
It is identical according to being worth, therefore can be directly using raw value as fused data value.
S203, if the multiple raw values obtained from multiple initial data are unequal, according to the number of initial data
According to source, accuracy rate corresponding to the raw value of each data source is determined respectively.
It should be understood that the confidence level of different data sources is different, for example the confidence level of communique is higher than microblogging
Confidence level.Correspondingly, accuracy rate corresponding to the raw value of different data sources is not also identical.
Fused data value is arranged according to accuracy rate corresponding to the raw value of each data source in S204.
It is appreciated that accuracy rate corresponding to raw value is higher, it is more accurate as fused data value.Therefore,
One kind is possible to be achieved in that, selects the maximum raw value of accuracy rate as fused data from multiple raw values
Value.
It needs to be emphasized that although the multiple raw values obtained from multiple initial data are not completely equivalent,
But the situation equal there may be part raw value.It is needed at this time by the original of multiple raw values middle parts split-phase etc.
Accuracy rate corresponding to data value is added, the accuracy rate of the raw value equal as the part.
To realize and be merged to multiple raw values, to obtain fused data value.
In order to clearly illustrate when the multiple raw values obtained from multiple initial data are unequal, this hair
The generation method for the knowledge mapping that bright embodiment is proposed is to obtain each data respectively how according to the data source of initial data
Accuracy rate corresponding to the raw value in source, the embodiment of the present invention also proposed the generation method of another knowledge mapping,
Fig. 4 is the flow diagram of the generation method of another knowledge mapping provided by the embodiment of the present invention.As shown in figure 4, being based on
Method flow shown in Fig. 3, the data source according to initial data in S203, determines the raw value of each data source respectively
Corresponding accuracy rate, comprising:
S301 determines the accuracy rate of each raw value according to priori knowledge.
Wherein, priori knowledge is the accuracy rate of the raw value determined according to data source.Specifically according to data source
The accuracy rate of the historical data information of offer determines the accuracy rate of the raw value of the data source.
S302 judges whether data attribute belongs to dynamic attribute according to the feature of data attribute.
Wherein, dynamic attribute refers to that data attribute can dynamic change.The feature of data attribute refers to the easy of the data attribute
Denaturation.
It should be understood that dynamic change includes gradual change at any time and is mutated with event.Wherein, gradual change refers to this at any time
The accuracy rate of the raw value of data attribute can gradually change at any time, and a kind of possible situation is the original of the data attribute
The accuracy rate of beginning data value constantly reduces at any time, is finally reduced to a definite value and no longer changes.Such as: accuracy rate is at 0 moment
It is 80%, per after one minute, accuracy rate reduces by 1%, no longer changes when accuracy rate is reduced to 50%.
Refer to that the accuracy rate of the raw value of the data attribute can mutate with emergency event with event mutation.Than
Such as: accuracy rate is 80% at 0 moment, and per after one minute, accuracy rate reduces by 1%, and at 20 minutes, accuracy rate was reduced to
60%, data source obtains the data information of an emergency event related with data attribute at this time, so that accuracy rate becomes again
80%, hereafter, accuracy rate is still per reducing by 1% after one minute, until being reduced to 50%.
It should be noted that if data attribute belongs to dynamic attribute, then the standard of each raw value of the data attribute
True rate all can dynamic change, when needing that specific time point is combined to determine that this is specific when determining the accuracy rate of each raw value
Between when putting each raw value accuracy rate.
It further, can be to each in order to allow the sum of the accuracy rate of each raw value at the specific time point to be 1
The accuracy rate of raw value is normalized.
It should be strongly noted that data attribute can allow the accuracy rate of each raw value with number with event mutation
Constantly change according to the update of the data information in source, to meet the demand that the dynamic of the data information in knowledge mapping updates.Data
Attribute constantly reduces the anomalous variation to knowledge graph when gradual change can allow the data information of data source anomalous variation occur at any time
The influence of spectrum.
S303 further judges whether the dynamic change of data attribute is legal if data attribute belongs to dynamic attribute.
Alternatively possible situation is, if data attribute is not belonging to dynamic attribute, keeps the accuracy rate of raw value
It is constant.
It should be appreciated that mutability is not present in the data attribute for being not belonging to dynamic attribute, it will not be with time or burst thing
Part and change, such as: the light velocity.
S304 modifies the accuracy rate of raw value according to dynamic change if dynamic change is legal.
Another is it might be that keep the accurate of raw value if the dynamic change of data attribute is illegal
Rate is constant.
It should be noted that needing to further prevent the data information of data source anomalous variation occur to obvious different
Often, i.e., illegal dynamic change is filtered, and keeps the accuracy rate of raw value constant.When dynamic change is legal, press
According to the processing mode above-mentioned with event mutation to the accuracy rate of modification raw value.
To realize the feature of the data source and data attribute according to initial data, determine the original of each data source
Accuracy rate corresponding to data value.
In order to clearly illustrate that the generation method of knowledge mapping that the embodiment of the present invention is proposed is in data attribute
No difference when belonging to dynamic attribute, is said by taking the data attribute in the knowledge mapping that theme is team information as an example below
It is bright.
As shown in figure 5, the uniform number of sportsman is not belonging to dynamic attribute, the uniform number for the sportsman that data source 1 provides
Raw value is No. 10, and the raw value of the uniform number for the sportsman that data source 2 provides is No. 9, the ball that data source 3 provides
The raw value of the uniform number of member is No. 10.The accuracy rate for determining the raw value of data source 1 according to priori knowledge is
0.3, the accuracy rate of the raw value of data source 2 is 0.45, and the accuracy rate of the raw value of data source 3 is 0.25.Due to
The uniform number for the sportsman that data source 1 and data source 3 provide all is No. 10, therefore the accuracy rate that the uniform number of sportsman is No. 10
For 0.3+0.25=0.55, the uniform number of sportsman is that No. 9 accuracys rate are 0.45,0.55 > 0.45, and fused data value is 10
Number, i.e., the uniform number of sportsman is No. 10 in fused data.
As shown in fig. 6, must belong to dynamic attribute of the team in court, the raw value that data source 1,2,3 provides
Accuracy rate adds a timeliness weight on the basis of 0.3,0.45,0.25 respectively, which reduces at any time, eventually become
0。
Cause the data of data source to change as shown in fig. 7, once there is new score, then need to this score into
Row validity judgement, for example team's score increases 1 point after data variation, then judges that data variation is legal, to data source
Timeliness weight is weighted, while the accuracy rate size relation of the raw value of each data source is become after weighting
Change, needs to update fused data value, i.e., score of the team in court in update fused data.After updating fused data value, when
The weight continuation of effect property reduces at any time, eventually becomes 0.But if team's score increases 10 points after data variation, sentence
Disconnected data variation is illegal, does not update fused data value.
In order to realize above-described embodiment, the embodiment of the present invention also proposes a kind of generating means of knowledge mapping, and Fig. 8 is this hair
A kind of structural schematic diagram of the generating means of knowledge mapping provided by bright embodiment, as shown in figure 8, the device includes: first
Module 410 is obtained, second obtains module 420, Fusion Module 430, generation module 440.
First obtains module 410, for obtaining the theme of knowledge mapping to be generated.
Second obtains module 420, for obtaining multiple initial data from multiple data sources according to theme.
Fusion Module 430, for being merged to multiple initial data, to obtain fused data.
Generation module 440, for generating knowledge mapping according to fused data.
Further, in order to from filtered out in the data information for the substantial amounts that data source generates generate knowledge mapping needed for
Initial data, it is a kind of it is possible is achieved in that, second obtains module 420, comprising: submodule 421 is determined, for according to master
Topic determines data attribute relevant to theme.First acquisition submodule 422 includes data category for obtaining from multiple data sources
Multiple initial data of property.
Further, initial data being merged in order to realize, one kind is possible to be achieved in that, Fusion Module 440,
It include: the second acquisition submodule 441, for obtaining multiple raw values of data attribute respectively from multiple initial data.
Submodule 442 is merged, for merging to multiple raw values, to obtain the fused data of data attribute in fused data
Value.Submodule 443 is generated, for generating fused data according to data attribute and fused data value.
It should be noted that the explanation of the aforementioned generation method embodiment to knowledge mapping is also applied for the embodiment
Knowledge mapping generating means, details are not described herein again.
In conclusion a kind of generating means of knowledge mapping of the embodiment of the present invention, obtain the master of knowledge mapping to be generated
Topic obtains multiple initial data from multiple data sources according to theme.Multiple initial data are merged, to obtain fusion number
According to.According to fused data, knowledge mapping is generated.The initial data for taking full advantage of different data sources as a result, avoids single number
Knowledge mapping is had an impact when occurring abnormal according to source, improves the reliability of knowledge mapping, while also enriching knowledge mapping
Content.
In order to realize above-described embodiment, the embodiment of the present invention also proposes the generating means of another knowledge mapping, and Fig. 9 is this
The structural schematic diagram of the generating means of another kind knowledge mapping provided by inventive embodiments, as shown in figure 9, fusion submodule
442, comprising: judging unit 4421, the first setting unit 4422, determination unit 4423, the second setting unit 4424.
Whether judging unit 4421, multiple raw values for judging to obtain from multiple initial data are equal.
First setting unit 4422, for when judging unit 4421 determine obtained from multiple initial data it is multiple original
When data value is equal, the fused data value is set by raw value.
Determination unit 4423, for determining the multiple initial data obtained from multiple initial data when judging unit 4421
When being worth unequal, according to the data source of initial data, accuracy rate corresponding to the raw value of each data source is determined respectively.
Second setting unit 4424 is arranged for the accuracy rate according to corresponding to the raw value of each data source and merges
Data value.
Further, in order to select most accurate raw value as fused data value, a kind of possible implementation
The second setting unit 4424, be specifically used for selected from multiple raw values the maximum raw value of accuracy rate as
Fused data value.
It should be noted that the explanation of the aforementioned generation method embodiment to knowledge mapping is also applied for the embodiment
Knowledge mapping generating means, details are not described herein again.
To realize and be merged to multiple raw values, to obtain fused data value.
In order to realize above-described embodiment, the embodiment of the present invention also proposes the generating means of another knowledge mapping, Tu10Wei
The structural schematic diagram of the generating means of another knowledge mapping provided by the embodiment of the present invention, as shown in Figure 10, determination unit
4423, comprising: determine subelement 44231, the first judgment sub-unit 44232, the second judgment sub-unit 44233 modifies subelement
44234。
Subelement 44231 is determined, for determining the accuracy rate of each raw value according to priori knowledge.
First judgment sub-unit 44232 judges whether data attribute belongs to dynamic and belong to for the feature according to data attribute
Property, wherein dynamic attribute refers to that data attribute can dynamic change.
Second judgment sub-unit 44233, for determining that data attribute belongs to dynamic attribute when the first judgment sub-unit 44232
When, further judge whether the dynamic change of data attribute is legal.
Subelement 44234 is modified, is used for when the second judgment sub-unit 44233 determines that dynamic change is legal, according to dynamic
The accuracy rate of variation modification raw value.
Further, alternatively possible situation is determination unit 4423, further includes: first keeps subelement 44235,
For keeping the accuracy rate of raw value when the first judgment sub-unit 44232 determines that data attribute is not belonging to dynamic attribute
It is constant.
Further, another is it might be that determination unit 4423, further includes: and second keeps subelement 44236,
When dynamic change for determining data attribute when the second judgment sub-unit 44233 is illegal, the accurate of raw value is kept
Rate is constant.
It should be noted that the explanation of the aforementioned generation method embodiment to knowledge mapping is also applied for the embodiment
Knowledge mapping generating means, details are not described herein again.
To realize the feature of the data source and data attribute according to initial data, determine the original of each data source
Accuracy rate corresponding to data value.
In order to realize above-described embodiment, the embodiment of the present invention also proposes a kind of computer program product, when the computer
Instruction processing unit in program product realizes the generation method of the knowledge mapping as described in preceding method embodiment when executing.
In order to realize above-described embodiment, embodiment also proposes a kind of non-transitorycomputer readable storage medium, deposits thereon
Computer program is contained, the knowledge mapping as described in preceding method embodiment is realized when the computer program is executed by processor
Generation method.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means specific features, structure, material or spy described in conjunction with this embodiment or example
Point is included at least one embodiment or example of the invention.In the present specification, schematic expression of the above terms are not
It must be directed to identical embodiment or example.Moreover, particular features, structures, materials, or characteristics described can be in office
It can be combined in any suitable manner in one or more embodiment or examples.In addition, without conflicting with each other, the skill of this field
Art personnel can tie the feature of different embodiments or examples described in this specification and different embodiments or examples
It closes and combines.
In addition, term " first ", " second " are used for descriptive purposes only and cannot be understood as indicating or suggesting relative importance
Or implicitly indicate the quantity of indicated technical characteristic.Define " first " as a result, the feature of " second " can be expressed or
Implicitly include at least one this feature.In the description of the present invention, the meaning of " plurality " is at least two, such as two, three
It is a etc., unless otherwise specifically defined.
Any process described otherwise above or method description are construed as in flow chart or herein, and expression includes
It is one or more for realizing custom logic function or process the step of executable instruction code module, segment or portion
Point, and the range of the preferred embodiment of the present invention includes other realization, wherein can not press shown or discussed suitable
Sequence, including according to related function by it is basic simultaneously in the way of or in the opposite order, Lai Zhihang function, this should be of the invention
Embodiment person of ordinary skill in the field understood.
Expression or logic and/or step described otherwise above herein in flow charts, for example, being considered use
In the order list for the executable instruction for realizing logic function, may be embodied in any computer-readable medium, for
Instruction execution system, device or equipment (such as computer based system, including the system of processor or other can be held from instruction
The instruction fetch of row system, device or equipment and the system executed instruction) it uses, or combine these instruction execution systems, device or set
It is standby and use.For the purpose of this specification, " computer-readable medium ", which can be, any may include, stores, communicates, propagates or pass
Defeated program is for instruction execution system, device or equipment or the dress used in conjunction with these instruction execution systems, device or equipment
It sets.The more specific example (non-exhaustive list) of computer-readable medium include the following: there is the electricity of one or more wirings
Interconnecting piece (electronic device), portable computer diskette box (magnetic device), random access memory (RAM), read-only memory
(ROM), erasable edit read-only storage (EPROM or flash memory), fiber device and portable optic disk is read-only deposits
Reservoir (CDROM).In addition, computer-readable medium can even is that the paper that can print described program on it or other are suitable
Medium, because can then be edited, be interpreted or when necessary with it for example by carrying out optical scanner to paper or other media
His suitable method is handled electronically to obtain described program, is then stored in computer storage.
It should be appreciated that each section of the invention can be realized with hardware, software, firmware or their combination.Above-mentioned
In embodiment, software that multiple steps or method can be executed in memory and by suitable instruction execution system with storage
Or firmware is realized.Such as, if realized with hardware in another embodiment, following skill well known in the art can be used
Any one of art or their combination are realized: have for data-signal is realized the logic gates of logic function from
Logic circuit is dissipated, the specific integrated circuit with suitable combinational logic gate circuit, programmable gate array (PGA), scene can compile
Journey gate array (FPGA) etc..
Those skilled in the art are understood that realize all or part of step that above-described embodiment method carries
It suddenly is that relevant hardware can be instructed to complete by program, the program can store in a kind of computer-readable storage medium
In matter, which when being executed, includes the steps that one or a combination set of embodiment of the method.
It, can also be in addition, each functional unit in each embodiment of the present invention can integrate in a processing module
It is that each unit physically exists alone, can also be integrated in two or more units in a module.Above-mentioned integrated mould
Block both can take the form of hardware realization, can also be realized in the form of software function module.The integrated module is such as
Fruit is realized and when sold or used as an independent product in the form of software function module, also can store in a computer
In read/write memory medium.
Storage medium mentioned above can be read-only memory, disk or CD etc..Although having been shown and retouching above
The embodiment of the present invention is stated, it is to be understood that above-described embodiment is exemplary, and should not be understood as to limit of the invention
System, those skilled in the art can be changed above-described embodiment, modify, replace and become within the scope of the invention
Type.
Claims (18)
1. a kind of generation method of knowledge mapping characterized by comprising
Obtain the theme of knowledge mapping to be generated；
Multiple initial data are obtained from multiple data sources according to the theme；
The multiple initial data is merged, to obtain fused data；And
According to the fused data, the knowledge mapping is generated.
2. the method as described in claim 1, which is characterized in that described to obtain multiple originals from multiple data sources according to the theme
Beginning data, comprising:
According to the theme, data attribute relevant to the theme is determined；
Multiple initial data comprising the data attribute are obtained from the multiple data source.
3. method according to claim 2, which is characterized in that it is described that the multiple initial data is merged, to obtain
Fused data, comprising:
Obtain multiple raw values of the data attribute respectively from the multiple initial data；
The multiple raw value is merged, to obtain the fused data of data attribute described in the fused data
Value；
According to the data attribute and the fused data value, the fused data is generated.
4. method as claimed in claim 3, which is characterized in that it is described that the multiple raw value is merged, to obtain
Take the fused data value of data attribute described in the fused data, comprising:
Judge whether the multiple raw values obtained from the multiple initial data are equal；
If the multiple raw values obtained from the multiple initial data are equal, the raw value is arranged
For the fused data value；
If the multiple raw values obtained from the multiple initial data are unequal, according to the initial data
Data source determines accuracy rate corresponding to the raw value of each data source respectively；
According to accuracy rate corresponding to the raw value of each data source, the fused data value is set.
5. method as claimed in claim 4, which is characterized in that the data source according to the initial data determines respectively
Accuracy rate corresponding to the raw value of each data source, comprising:
The accuracy rate of each raw value is determined according to priori knowledge；
Judge whether the data attribute belongs to dynamic attribute according to the feature of the data attribute, wherein the dynamic attribute
Refer to that the data attribute can dynamic change；
If the data attribute belongs to dynamic attribute, further judge whether the dynamic change of the data attribute is legal；
If the dynamic change is legal, the accuracy rate of the raw value is modified according to the dynamic change.
6. method as claimed in claim 5, which is characterized in that judge whether the data attribute belongs to dynamic attribute described
Later, further includes:
If the data attribute is not belonging to dynamic attribute, keep the accuracy rate of the raw value constant.
7. method as claimed in claim 5, which is characterized in that whether closed in the dynamic change for judging the data attribute
After method, further includes:
If the dynamic change of the data attribute is illegal, keep the accuracy rate of the raw value constant.
8. the method as described in any one of claim 4-7, which is characterized in that described according to each data source
The fused data value is arranged in accuracy rate corresponding to raw value, comprising:
Select the maximum raw value of the accuracy rate as the fused data from multiple raw values
Value.
9. a kind of generating means of knowledge mapping, which is characterized in that described device includes:
First obtains module, for obtaining the theme of knowledge mapping to be generated；
Second obtains module, for obtaining multiple initial data from multiple data sources according to the theme；
Fusion Module, for being merged to the multiple initial data, to obtain fused data；
Generation module, for generating the knowledge mapping according to the fused data.
10. device as claimed in claim 9, which is characterized in that described second obtains module, comprising:
Submodule is determined, for determining data attribute relevant to the theme according to the theme；
First acquisition submodule, for obtaining multiple initial data comprising the data attribute from the multiple data source.
11. device as claimed in claim 10, which is characterized in that the Fusion Module, comprising:
Second acquisition submodule, for obtaining multiple initial data of the data attribute respectively from the multiple initial data
Value；
Submodule is merged, for merging to the multiple raw value, to obtain data described in the fused data
The fused data value of attribute；
Submodule is generated, for generating the fused data according to the data attribute and the fused data value.
12. device as claimed in claim 11, which is characterized in that the fusion submodule, comprising:
Whether judging unit, multiple raw values for judging to obtain from the multiple initial data are equal；
First setting unit, for when the judging unit determine obtained from the multiple initial data it is multiple described original
When data value is equal, the fused data value is set by the raw value；
Determination unit, for determining the multiple initial data obtained from the multiple initial data when the judging unit
When being worth unequal, according to the data source of the initial data, corresponding to the raw value that determines each data source respectively
Accuracy rate；
Second setting unit, for described in the setting of the accuracy rate according to corresponding to the raw value of each data source
Fused data value.
13. device as claimed in claim 12, which is characterized in that the determination unit, comprising:
Subelement is determined, for determining the accuracy rate of each raw value according to priori knowledge；
First judgment sub-unit, for judging whether the data attribute belongs to dynamic and belong to according to the feature of the data attribute
Property, wherein the dynamic attribute refers to that the data attribute can dynamic change；
Second judgment sub-unit, for when first judgment sub-unit determines that the data attribute belongs to dynamic attribute, into
One step judges whether the dynamic change of the data attribute is legal；
Subelement is modified, for becoming according to the dynamic when second judgment sub-unit determines that the dynamic change is legal
Change the accuracy rate for modifying the raw value.
14. device as claimed in claim 13, which is characterized in that the determination unit, further includes:
First keeps subelement, for when first judgment sub-unit determines that the data attribute is not belonging to dynamic attribute,
Keep the accuracy rate of the raw value constant.
15. device as claimed in claim 13, which is characterized in that the determination unit, further includes:
Second keeps subelement, for determining that the dynamic change of the data attribute is illegal when second judgment sub-unit
When, keep the accuracy rate of the raw value constant.
16. the device as described in any one of claim 12-15, which is characterized in that second setting unit is specifically used for
Select the maximum raw value of the accuracy rate as the fused data value from multiple raw values.
17. a kind of computer program product, which is characterized in that when the instruction processing unit in the computer program product executes
Realize the generation method such as knowledge mapping described in any one of claims 1-8.
18. a kind of non-transitorycomputer readable storage medium, is stored thereon with computer program, which is characterized in that the meter
The generation method such as knowledge mapping described in any one of claims 1-8 is realized when calculation machine program is executed by processor.
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