CN108038228A - A kind of method for digging and device based on database - Google Patents
A kind of method for digging and device based on database Download PDFInfo
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- CN108038228A CN108038228A CN201711422034.XA CN201711422034A CN108038228A CN 108038228 A CN108038228 A CN 108038228A CN 201711422034 A CN201711422034 A CN 201711422034A CN 108038228 A CN108038228 A CN 108038228A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2465—Query processing support for facilitating data mining operations in structured databases
Abstract
The object of the present invention is to provide a kind of method for digging and device based on database, it is closed in relative to the information in prior art database in respective subsystem, it cannot be interacted between subsystem database, information cannot be shared, simple inquiry, addition, modification, deletion and statistical function can only be provided, become qualified information island, using isolated island, caused resource serious waste, cannot get effective reasonable utilization.Method for digging and device provided by the invention based on database, including determine the target of data mining；Prepare data；Establish data mining model：Data mining；Interpretation of result, explanation are simultaneously assessed；Six steps such as working knowledge, it is possible to achieve information can be used interchangeably between subsystem database, shared information, avoided resource serious waste, make resource obtain effective reasonable utilization.
Description
Technical field
The present invention relates to network data technical field, more particularly to a kind of method for digging and device based on database.
Background technology
The rapid development of computer science, the particularly rapid progress of database technology and network technology so that people obtain
Win the confidence breath and propagate information approach it is more and more extensive, speed is getting faster, mode is more and more diversified, bar codes technique and letter
A large amount of with card use, and cause the IT application process of the association areas such as business, insurance, finance to accelerate, All Around The World seemingly night
Between enter an entirely different fresh information epoch.
In this more than ten years for entering 21st century, information content accelerated growth in the database is stored.For example, China
Independent research, Global Satellite Navigation System-Beidou satellite navigation system of independent operating can be sent out to National Airspace center per hour
Return the image data amount of up to 50GB；The Intranet trade company of only state of China Unionpay just has 1,570,000, it needs the friendship preserved daily
Easy data are well imagined；The data of different industries different field are stored in respective database, and the scale of database is gradual
Expand, much have arrived at the scale of tens of G, or even bigger.The continuous development of computer hardware, high access speed, large capacity,
The storage medium of low price is come out one after another, and the data that data base management system and data warehouse have been able to deal with such scale need
Ask.These relatively independent databases can only provide simple addition, inquiry, deletion and statistical function, by these operations only
It can obtain the very little fraction of whole database information amount.The data volume of these explosive growths brings facility
While, the problem of many itself is also produced, in terms of mainly having following four：First, information content is excessive, considerably beyond people's
Grasp, digestion power, cause the mismatch between the growth of information content and digestion power；It is second, very one big in the information of magnanimity
It is insignificant false junk information to divide, and causes correctly using for information relatively difficult；Third, network information security is difficult
To obtain effective guarantee；Fourth, the organizational form and Store form of information are not sought unity of standard, information is set to be difficult to be uniformly processed.For
These complicated situations are tackled, excite a new research direction：Knowledge Discovery and relevant number based on database
According to the application study of method for digging and technology.
At present, each individually subsystem has the storage database of oneself.Information in database is closed in each
Subsystem in, cannot be interacted between subsystem database, information cannot be shared, and can only provide and simply inquire about, add, repairing
Change, delete and statistical function, become qualified information island, using isolated island, caused resource serious waste cannot
Effective reasonable utilization.
The content of the invention
The object of the present invention is to provide a kind of method for digging and device based on database, to solve in current database
Information is closed in respective subsystem, cannot be interacted between subsystem database, and information cannot be shared, and can only be provided simple
Inquiry, addition, modification, deletion and statistical function, become qualified information island, using isolated island, caused resource
Serious waste, cannot get effective reasonable utilization.
In a first aspect, the embodiment of the present application provides a kind of method for digging based on database, the described method includes：
Step S101：Determine the target of data mining, object is clearly excavated in definition；
Step S102：Prepare data, including selection data, processing data and data integration；
Step S103：Data mining model is established, including suitable variable is selected for model；In the base of analysis initial data
On plinth, new predicted value is built；Choose a part of data after data processing and establish model as sample data；To becoming
Amount is changed, and it is consistent with the algorithm for establishing model；
Step S104：Data mining, including data mining is carried out to the existing data being converted；
Step S105：Interpretation of result, explanation are simultaneously assessed；
Step S106：Working knowledge.
With reference to the application's in a first aspect, in second of embodiment of the application first aspect, step S102：It is accurate
Standby data, including selection data, processing data and data integration；
The object that the selection data include data mining is decided all related to business object it is necessary to start to collect
External data and internal data, therefrom filter out the data for meeting data mining requirement.
With reference to the application's in a first aspect, in the third embodiment of the application first aspect, step S102：It is accurate
Standby data, including selection data, processing data and data integration；
The processing data include cleaning inconsistent, the out-of-date junk data that defines of data.
With reference to the application's in a first aspect, in the 4th kind of embodiment of the application first aspect, step S102：
Prepare data, including selection data, processing data and data integration；
The data integration includes processing data redundancy, numerical value conflict and Mode integrating.
With reference to the application's in a first aspect, in the 5th kind of embodiment of the application first aspect, step S103：Build
Vertical data mining model, including select suitable variable for model；On the basis of initial data is analyzed, new prediction is built
Value；Choose a part of data after data processing and establish model as sample data；Variable is changed, make it and
The algorithm for establishing model is consistent, including establishes analysis model using suitable data mining algorithm according to data characteristics.
Second aspect, a kind of excavating gear based on database, described device include：
Determine data cell：For determining the target of data mining, object is clearly excavated in definition；
Prepare data cell：For preparing data, including selection data, processing data and data integration；
Establish model unit：Suitable variable is selected for establishing data mining model, including for model；It is original analyzing
On the basis of data, new predicted value is built；A part of data after data processing are chosen to establish as sample data
Model；Variable is changed, it is consistent with the algorithm for establishing model；
Dig office data unit：Data mining is carried out for data mining, including to the existing data being converted；
Interpretation of result unit：For interpretation of result, explanation and assess；
Working knowledge unit：For working knowledge.
With reference to the second aspect of the application, in second of embodiment of the application first aspect, prepare data sheet
Member：For preparing data, including selection data, processing data and data integration；The selection data include being used for data digging
The object of pick is decided it is necessary to start to collect all and the relevant external data of business object and internal data, is therefrom sieved
Select the data for meeting data mining requirement.
With reference to the second aspect of the application, in the third embodiment of the application first aspect, prepare data sheet
Member：For preparing data, including selection data, processing data and data integration；The processing data include being used for data
Inconsistent, the out-of-date junk data of defining cleaned.
With reference to the second aspect of the application, in the 4th kind of embodiment of the application first aspect, prepare data sheet
Member：For preparing data, including selection data, processing data and data integration；The data integration includes being used to handle number
According to redundancy, numerical value conflict and Mode integrating.
With reference to the second aspect of the application, in the 5th kind of embodiment of the application first aspect, model list is established
Member：For establishing data mining model, including for selecting suitable variable for model；On the basis of initial data is analyzed,
For building new predicted value；Model is established for choosing a part of data after data processing as sample data；
For being changed to variable, it is consistent with the algorithm for establishing model, further include and closed for being used according to data characteristics
Suitable data mining algorithm establishes analysis model
From above technical scheme：The object of the present invention is to provide a kind of method for digging and device based on database,
It is closed in respective subsystem relative to the information in prior art database, cannot be interacted between subsystem database,
Information cannot be shared, and can only provide simple inquiry, addition, modification, deletion and statistical function, become qualified information
Isolated island, using isolated island, caused resource serious waste, cannot get effective reasonable utilization.It is provided by the invention to be based on database
Method for digging and device, information can be used interchangeably between subsystem database, share information, avoid resource seriously unrestrained
Take, resource is obtained effective reasonable utilization.
Brief description of the drawings
Some specific embodiments of detailed description of the present invention by way of example, and not by way of limitation with reference to the accompanying drawings hereinafter.
Identical reference numeral denotes same or similar component or part in attached drawing.It should be appreciated by those skilled in the art that these
What attached drawing was not necessarily drawn to scale.In attached drawing：
Fig. 1 is a kind of method for digging flow chart based on database provided by the embodiments of the present application.
Embodiment
This below in conjunction with the attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out it is clear,
Complete description, it is clear that described embodiment is only part of the embodiment of the present invention, instead of all the embodiments.Base
Embodiment in the present invention, those of ordinary skill in the art obtained without making creative work it is all its
His embodiment, belongs to the scope of protection of the invention.
A kind of as shown in Figure 1, method for digging flow chart based on database provided by the embodiments of the present application.
In a first aspect, the embodiment of the present application provides a kind of method for digging based on database, the described method includes：
Step S101：Determine the target of data mining, object is clearly excavated in definition；
The first step of data mining is to determine the target of data mining, and definition is clearly excavated object, is very important
One step.The real demand of understanding user reported as precisely as possible is the successful precondition of data mining.The most termination of data mining
Fruit is usually unpredictable, but data mining will solve the problems, such as to be true, having prediction, autotelic.
In definite data mining object, the problem of paying attention to these aspects is generally required：Start with from where, need that what number excavated
According to, need to use the scale of data, the last data mining degree to be proceeded to.In the first step of data mining, past contact
User is needed to provide some related prioris at the same time.So-called priori refer to customer service in terms of professional knowledge and with
Preliminary achievement early period that preceding data mining had obtained already.Data mining is a process to move in circles, this process may
The problem of various unpredictable is run into, it is necessary to attempting different methods carrys out inspection data, is carried out not in the subset of data
Disconnected checking research.
Step S102：Prepare data, including selection data, processing data and data integration；
Once the object of data mining decide it is necessary to start to collect it is all with the relevant external data of business object with
And internal data, therefrom filter out the data for meeting data mining requirement.If the data of data mining are stored in data bins
In storehouse, the selection of such data is just opposite can be very convenient, because the master data in data warehouse is exactly the object of data mining
Data.Not so, it is necessary to integrate the data needed in various data sources.Extremely easily there are data in data in multiple data sources
The different situation of value difference.It is significant to whole data mining process in data preparation stage, the processing different to data value difference.
After first step work has been carried out, it is also necessary to data are pre-processed, data are cleaned, are solved in data
Default, redundancy, data value it is inconsistent, it is data define inconsistent, out-of-date junk data etc., such data completely may be used
To be known as dirty data.It is that impossible set up an outstanding data mining model on the premise of dirty data is more.Such as
Contained assigning null data ratio is little in fruit data set, can use the method for directly deleting the record containing null value, simple and effective.
If the transaction item of the value containing null attribute is more, if directly deleting, and the effect of data mining can be influenced.To closing for null value
Physics and chemistry processing has following several method：Firstth, the average value of attribute column, then replaces sky with average value where calculating null value
Value；Secondth, according to the rule of association area, thus it is speculated that should numerical value, to replace null value；3rd, analyzed with conventional
To data directly replaced；4th, with data mining technology, possible data value is predicted, and be replaced.It is specific to use
Which kind of processing empty value method according to actual conditions, it is necessary to determine.In the stage to data prediction, the feelings having to packet
The difficulty for establishing data mining model can be reduced under condition, improves the final efficiency of data mining.
After the completion of data prediction, also need to establish a data mining storehouse sometimes, the number in this data mining storehouse
According to next in multiple scattered data sources.The main reason for establishing data mining storehouse is that the processing meaning of one's words obscures and unifies form,
The application of other systems is not interfered with thus.Data integration needs the problem of three aspects of processing：Firstth, data redundancy.
Scattered data source inevitably causes some data redundancies, for example some attribute columns repeat etc..Secondth, numerical value
Conflict.Because the stipulations of each scattered data source require it is different, same entity in different data sources may numerical value not
It is identical.3rd, Mode integrating.Different data sources, is all heterogeneous database mostly, data format extremely easily occurs and does not unite
First, the problems such as repeating storage, meaning of one's words ambiguity etc..The metadata of generally use data warehouse and database carries out pattern-recognition,
The integrated preceding same entity in different data sources is identified in data mining storehouse.Last procedure of data processing is
The quality of data is evaluated.The quality of data includes data integrity, data validity, data age, data consistency, number
According to correctness, Information Security.Good data could allow data mining results more accurate.
Step S103：Data mining model is established, including suitable variable is selected for model；In the base of analysis initial data
On plinth, new predicted value is built；Choose a part of data after data processing and establish model as sample data；To becoming
Amount is changed, and it is consistent with the algorithm for establishing model；
After data preparation finishes, it is necessary to establish analysis mould using suitable data mining algorithm according to data characteristics
Type, the selection of this data mining algorithm are the keys of whole Data Mining Project success or not.The foundation of model starts from data
Analysis.First, suitable variable is selected for model.Ideally all variables are all added in Data Mining Tools,
But this is unpractical in practical operation.Because a lot of variables may not have your required analysis result any association milli
It is uncorrelated, while add load.Secondly, on the basis of initial data is analyzed, new predicted value is built.Then, warp is chosen
A part of data crossed after data processing establish model as sample data.This is done because the data randomly selected not
Information can be caused insufficient.Finally, variable is changed, it is consistent with the algorithm for establishing model.
Step S104：Data mining, including data mining is carried out to the existing data being converted；
The existing data being converted are carried out with data mining, the work of data mining mainly has now under normal circumstances
Into Data Mining Tools be automatically performed, unless project have special demand to data mining, it is necessary to improve improve it is original existing
Algorithm.
Step S105：Interpretation of result, explanation are simultaneously assessed；
After Data Mining Tools are to data analysis, result is produced, it is necessary to acquired results are carried out with analysis interpretation and is commented
Estimate.The result that data mining obtains be probably it is skimble-skamble, it is even antipodal with reality.We just need pair
As a result analysis and evaluation is carried out.Specific appraisal procedure should generally be sentenced according to the decision strategy success or not that Result is formulated
It is fixed.But comparing contradiction, there is a expection in decision-making level using before Result to Result, it is desirable to protects whereby
Demonstrate,prove success rate of the data mining results in practice.Therefore, obtain result to excavation to evaluate, it is contemplated that following several
The problem of a aspect：First, carrying out the obtained result of data mining with the data set for establishing the model on set model will
Result than being obtained using different data set progress data minings is outstanding.Secondly, for model in a certain respect, data mining
Result beyond expected accurate.Finally, because the verification of model is carried out using sample data, then final actual result
Expection when may be than modeling is poor.In many cases, can become apparent from easily representing using visualization technique
Result.
Step S106：Working knowledge.
Data mining results are approved by the discussion of related service decision-maker, then can just be disposed, and final real
Border uses, and the final result and the professional knowledge of the sector that data mining is obtained merge at one piece, and forming one can allow not
The system that the personnel of same level skillfully use.Only by applying the knowledge excavated, could really determine to excavate
As a result whether effective.Data mining results are to formation practical application, it is necessary to which the Knowledge Integration excavated is integrated into management
In policy-making body, certain booster action is played administrative decision.
It should be noted that data mining technology takes full advantage of mutually oozing for various methodology under contemporary scientific system
Thoroughly, mutually merge, mutually extend, mutually promote.
The object of the present invention is to provide a kind of method for digging based on database, to solve the information quilt in current database
It is enclosed in respective subsystem, cannot be interacted between subsystem database, information cannot be shared, and can only provide and simply look into
Ask, addition, modification, delete and statistical function, become qualified information island, serious using isolated island, caused resource
Waste, cannot get effective reasonable utilization.
Further, step S102：Prepare data, including selection data, processing data and data integration；
The object that the selection data include data mining is decided all related to business object it is necessary to start to collect
External data and internal data, therefrom filter out the data for meeting data mining requirement.
Further, step S102：Prepare data, including selection data, processing data and data integration；
The processing data include cleaning inconsistent, the out-of-date junk data that defines of data.
Further, step S102：Prepare data, including selection data, processing data and data integration；
The data integration includes processing data redundancy, numerical value conflict and Mode integrating.
Further, step S103：Data mining model is established, including suitable variable is selected for model；It is former in analysis
On the basis of beginning data, new predicted value is built；A part of data after data processing are chosen to build as sample data
Formwork erection type；Variable is changed, it is consistent with the algorithm for establishing model, including according to data characteristics using suitable
Data mining algorithm establishes analysis model.
Second aspect, a kind of excavating gear based on database, described device include：
Determine data cell：For determining the target of data mining, object is clearly excavated in definition；
Prepare data cell：For preparing data, including selection data, processing data and data integration；
Establish model unit：Suitable variable is selected for establishing data mining model, including for model；It is original analyzing
On the basis of data, new predicted value is built；A part of data after data processing are chosen to establish as sample data
Model；Variable is changed, it is consistent with the algorithm for establishing model；
Dig office data unit：Data mining is carried out for data mining, including to the existing data being converted；
Interpretation of result unit：For interpretation of result, explanation and assess；
Working knowledge unit：For working knowledge.
The object of the present invention is to provide a kind of excavating gear based on database, to solve the information quilt in current database
It is enclosed in respective subsystem, cannot be interacted between subsystem database, information cannot be shared, and can only provide and simply look into
Ask, addition, modification, delete and statistical function, become qualified information island, serious using isolated island, caused resource
Waste, cannot get effective reasonable utilization.
Further, data cell is prepared：For preparing data, including selection data, processing data and data integration；
The selection data include deciding for the object of data mining all relevant outer with business object it is necessary to start to collect
Portion's data and internal data, therefrom filter out the data for meeting data mining requirement.
Further, data cell is prepared：For preparing data, including selection data, processing data and data integration；
The processing data include being used to clean inconsistent, the out-of-date junk data that defines of data.
Further, data cell is prepared：For preparing data, including selection data, processing data and data integration；
The data integration includes being used to handle data redundancy, numerical value conflict and Mode integrating.
Further, model unit is established：For establishing data mining model, including for selecting suitable become for model
Amount；On the basis of initial data is analyzed, for building new predicted value；For choosing a part of number after data processing
Model is established according to as sample data；For being changed to variable, it is consistent with the algorithm for establishing model, also wrap
Include for establishing analysis model using suitable data mining algorithm according to data characteristics
From above technical scheme：The object of the present invention is to provide a kind of method for digging and device based on database,
It is closed in respective subsystem relative to the information in prior art database, cannot be interacted between subsystem database,
Information cannot be shared, and can only provide simple inquiry, addition, modification, deletion and statistical function, become qualified information
Isolated island, using isolated island, caused resource serious waste, cannot get effective reasonable utilization.It is provided by the invention to be based on database
Method for digging and device, information can be used interchangeably between subsystem database, share information, avoid resource seriously unrestrained
Take, resource is obtained effective reasonable utilization.
So far, although those skilled in the art will appreciate that detailed herein have shown and described multiple showing for the present invention
Example property embodiment, still, without departing from the spirit and scope of the present invention, still can according to the present invention disclosure it is direct
Determine or derive many other variations or modifications for meeting the principle of the invention.Therefore, the scope of the present invention is understood that and recognizes
It is set to and covers other all these variations or modifications.
Claims (10)
- A kind of 1. method for digging based on database, it is characterised in that the described method includes：Step S101：Determine the target of data mining, object is clearly excavated in definition；Step S102：Prepare data, including selection data, processing data and data integration；Step S103：Data mining model is established, including suitable variable is selected for model；On the basis of analysis initial data On, build new predicted value；Choose a part of data after data processing and establish model as sample data；To variable Changed, it is consistent with the algorithm for establishing model；Step S104：Data mining, including data mining is carried out to the existing data being converted；Step S105：Interpretation of result, explanation are simultaneously assessed；Step S106：Working knowledge.
- 2. according to the method described in claim 1, it is characterized in that, step S102：Prepare data, including selection data, processing Data and data integration；The object that the selection data include data mining is decided all relevant outer with business object it is necessary to start to collect Portion's data and internal data, therefrom filter out the data for meeting data mining requirement.
- 3. according to the method described in claim 1, it is characterized in that, step S102：Prepare data, including selection data, processing Data and data integration；The processing data include cleaning inconsistent, the out-of-date junk data that defines of data.
- 4. according to the method described in claim 1, it is characterized in that, step S102：Prepare data, including selection data, processing Data and data integration；The data integration includes processing data redundancy, numerical value conflict and Mode integrating.
- 5. according to the method described in claim 1, it is characterized in that, step S103：Data mining model is established, including is model Select suitable variable；On the basis of initial data is analyzed, new predicted value is built；Choose one after data processing Divided data establishes model as sample data；Variable is changed, it is consistent with the algorithm for establishing model, including Analysis model is established using suitable data mining algorithm according to data characteristics.
- 6. a kind of excavating gear based on database, it is characterised in that described device includes：Determine data cell：For determining the target of data mining, object is clearly excavated in definition；Prepare data cell：For preparing data, including selection data, processing data and data integration；Establish model unit：Suitable variable is selected for establishing data mining model, including for model；In analysis initial data On the basis of, build new predicted value；Choose a part of data after data processing and establish model as sample data； Variable is changed, it is consistent with the algorithm for establishing model；Dig office data unit：Data mining is carried out for data mining, including to the existing data being converted；Interpretation of result unit：For interpretation of result, explanation and assess；Working knowledge unit：For working knowledge.
- 7. device according to claim 6, it is characterised in that prepare data cell：For preparing data, including selection number According to, processing data and data integration；The selection data include deciding it is necessary to start to search for the object of data mining Collect all and the relevant external data of business object and internal data, therefrom filter out the data for meeting data mining requirement.
- 8. device according to claim 6, it is characterised in that prepare data cell：For preparing data, including selection number According to, processing data and data integration；The processing data include being used to define inconsistent, out-of-date junk data to data Cleaned.
- 9. device according to claim 6, it is characterised in that prepare data cell：For preparing data, including selection number According to, processing data and data integration；The data integration includes being used to handle data redundancy, numerical value conflict and set of patterns Into.
- 10. device according to claim 6, it is characterised in that establish model unit：For establishing data mining model, Including for selecting suitable variable for model；On the basis of initial data is analyzed, for building new predicted value；For selecting A part of data after data processing of learning from else's experience establish model as sample data；For being changed to variable, make it and The algorithm for establishing model is consistent, and is further included for establishing analysis using suitable data mining algorithm according to data characteristics Model.
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