CN106484844A - Big data method for digging and system - Google Patents
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Abstract
The present invention relates to data analysis technique, particularly a kind of big data method for digging, including the target data set extracting data mining from data base；Pretreatment is carried out to described target data set；Data mining is carried out to the target data set through pretreatment according to the function type data feature of data, obtains data mining results；Described data mining results are explained and evaluates, generate data mining report.The present invention have the characteristics that easy-to-use, be easy to extension, easily implement, can safeguard, performance high and safe and reliable.Additionally, the present invention also provides a kind of big data digging system.
Description
Technical field
The present invention relates to data analysis technique, particularly to a kind of big data method for digging and system.
Background technology
Big data is commonly used to describe a large amount of destructurings and the semi-structured data that a company creates, these data exist
Downloading to can overspending time and money when relevant database is used for analyzing.If can be in a large amount of destructurings and half structure
Change in data and gather effective information, greatly improve the accuracy of information gathering beyond doubt, thus lifting the effect of people's work
Rate, the accurate assurance to market.Information required for how fast and accurately excavating in big data, day by day becomes people and is concerned about
Problem.
By the end of 2012, data volume rose to as PB (1024TB=1PB), EB from TB (1024GB=1TB) rank
(1024PB=1EB) or even ZB (1024EB=1ZB) rank.The result of study of International Data Corporation (IDC) (IDC) shows, 2008 complete
The data volume that ball produces is 0.49ZB, and the data volume of 2009 is 0.8ZB, increases within 2010 as 1.2ZB, the quantity of 2011 is more
It is up to 1.82ZB, everyone produces the data of more than 200GB to be equivalent to the whole world.And to 2012, human being's production all
The data volume of printing material is 200PB, and all data volumes that the whole mankind said in history are about 5EB.The research of IBM
Claim, in the total data that whole human civilization is obtained, have 90% to produce in two years in the past.And arrived the year two thousand twenty, full generation
Data scale produced by boundary is up to 44 times of today.
Being continuously increased of data scale, proposes requirements at the higher level to data processing, in the big data epoch, traditional data processing
Method is inapplicable.
1) data processing needs under big data environment
Under big data environment, Data Source is very abundant and data type is various, and the data volume of storage and analysis mining is huge
Greatly, the requirement to data exhibiting is higher, and values very much high efficiency and the availability of data processing.
2) deficiency of traditional data processing method
Traditional data acquisition source is single, and storage, management and analytical data amount are also relatively small, mostly adopts relation
Type data base and parallel data warehouse can be processed.For relying on parallel computation lifting data processing speed aspect, traditional
Parallel database technology pursues high consistency and fault-tolerance, according to CAP theory it is difficult to ensure its availability and autgmentability.
Traditional data processing method is centered on processor, and under big data environment, needs are taken in data being
The pattern of the heart, reduces the expense that data movement brings.Therefore, traditional data processing method, has not adapted to big data
Demand.
Content of the invention
For overcoming the defect of prior art, the present invention provides a kind of big data method for digging and system.
The present invention adopts technical scheme as follows：
A kind of big data method for digging, including：
The target data set of data mining is extracted from data base；
Pretreatment is carried out to described target data set；
Data mining is carried out to the target data set through pretreatment according to the function type data feature of data, obtains
Data mining results；
Described data mining results are explained and evaluates, generate data mining report.
Preferably, described pretreatment is carried out to target data set, including：
Check that target data concentrates integrity and the concordance of each data；
Each data is carried out with Denoising disposal, fills up disappearance domain and delete invalid data.
Preferably, the described function type data feature according to data enters line number to the target data set through pretreatment
According to excavation, obtain data mining results, including：
Target data set through pretreatment is associated analyze, related information content is counted according to semantic, repertorie,
And carry out distributed taxonomic clustering, and distributed burst calculating is carried out to data, result is collected and carries out parallel processing, simultaneously
Will be stored in data base the common feature of one group of data object and be divided into different classes according to classification mode, and pass through
The classification that information classification algorithm gives the maps data items in data base to certain, and event classification type, feature are carried out
Packet, and carry out multi dimensional analysis, count substantive information data.
Preferably, before the target data set of described extraction data mining from data base, also include：
Collection internet information, using described internet information as data is activation to be analyzed to data base.
Preferably, described described data mining results are explained and evaluate, generate data mining report after, also wrap
Include：
Described data mining report is sent to user terminal.
Correspondingly, the present invention also provides a kind of big data digging system, including：
Extraction unit, for extracting the target data set of data mining from data base；
Pretreatment unit, for carrying out pretreatment to described target data set；
Data mining unit, for according to the function type data feature of data to the target data set through pretreatment
Carry out data mining, obtain data mining results；
Signal generating unit, for explaining to described data mining results and evaluating, generates data mining report.
Preferably, described pretreatment unit includes：
Check module, for checking integrity and the concordance of the target data each data of concentration；
Processing module, for carrying out Denoising disposal, filling up disappearance domain and deleting invalid data to each data.
Preferably, described data mining unit, specifically for：
Target data set through pretreatment is associated analyze, related information content is counted according to semantic, repertorie,
And carry out distributed taxonomic clustering, and distributed burst calculating is carried out to data, result is collected and carries out parallel processing, simultaneously
Will be stored in data base the common feature of one group of data object and be divided into different classes according to classification mode, and pass through
The classification that information classification algorithm gives the maps data items in data base to certain, and event classification type, feature are carried out
Packet, and carry out multi dimensional analysis, count substantive information data.
Preferably, described system also includes：
Collecting unit, for gathering internet information, using described internet information as data is activation to be analyzed to data
Storehouse.
Preferably, described system also includes：
Transmitting element, for sending described data mining report to user terminal.
The invention has the beneficial effects as follows：
The present invention adopts advanced data processing technique and algorithm, carries out distributed data digging to big data, it is main
It is that web page excavation, words and phrases feature, the meaning of a word, artistic conception variance analyses are carried out to big data, word segmentation processing is carried out to words and phrases, in conjunction with
Artistic conception associates statistical analysiss to info web, analyzes and seems disunity, incoherent word, finds out the language of event between artistic conception
The contact of the essence of sentence, directly counts and seems not associated data and be analyzed, obtain the hiding information of data behind, and logarithm
According to being predicted analyzing, decision tree is generated according to historical data, finds out potential valuable data message.Have easy-to-use, be easy to
Extension, easily implement, can safeguard, feature that performance is high and safe and reliable.
Brief description
In order to be illustrated more clearly that technical scheme, below will be to required in embodiment or description of the prior art
Use accompanying drawing be briefly described it should be apparent that, drawings in the following description are only some embodiments of the present invention, right
For those of ordinary skill in the art, on the premise of not paying creative work, it can also be obtained according to these accompanying drawings
Its accompanying drawing.
Fig. 1 is the schematic flow sheet of the big data method for digging that the embodiment of the present invention one provides；
Fig. 2 is the schematic flow sheet of the big data method for digging that the embodiment of the present invention two provides；
Fig. 3 is the structural representation of the big data digging system that the embodiment of the present invention three provides；
Fig. 4 is the structural representation of the big data digging system that the embodiment of the present invention four provides.
Specific embodiment
In order that those skilled in the art more fully understand the present invention program, below in conjunction with the embodiment of the present invention
Accompanying drawing, is clearly and completely described to the technical scheme in the embodiment of the present invention it is clear that described embodiment is only
The embodiment of a present invention part, rather than whole embodiments.Based on the embodiment in the present invention, ordinary skill people
The every other embodiment that member is obtained under the premise of not making creative work, all should belong to the model of present invention protection
Enclose.
It should be noted that term " first " in description and claims of this specification and above-mentioned accompanying drawing, "
Two " it is etc. for distinguishing similar object, without for describing specific order or precedence.It should be appreciated that such use
Data can exchange in the appropriate case so that embodiments of the invention described herein can with except here diagram or
Order beyond those of description is implemented.Additionally, term " comprising " and " having " and their any deformation are it is intended that cover
Cover non-exclusive comprising, for example, contain series of steps or process, method, system, product or the equipment of unit are not necessarily limited to
Those steps clearly listed or unit, but may include clearly not listing or for these processes, method, product
Or the intrinsic other steps of equipment or unit.
Embodiment one：
A kind of big data method for digging providing referring to Fig. 1, the present embodiment, including：
S101：The target data set of data mining is extracted from data base；
S102：Pretreatment is carried out to described target data set；
S103：Carry out data according to the function type data feature of data to the target data set through pretreatment to dig
Pick, obtains data mining results；
S104：Described data mining results are explained and evaluates, generate data mining report.
Further, described pretreatment is carried out to target data set, including：
Check that target data concentrates integrity and the concordance of each data；
Each data is carried out with Denoising disposal, fills up disappearance domain and delete invalid data.
Preferably, the described function type data feature according to data enters line number to the target data set through pretreatment
According to excavation, obtain data mining results, including：
Target data set through pretreatment is associated analyze, related information content is counted according to semantic, repertorie,
And carry out distributed taxonomic clustering, and distributed burst calculating is carried out to data, result is collected and carries out parallel processing, simultaneously
Will be stored in data base the common feature of one group of data object and be divided into different classes according to classification mode, and pass through
The classification that information classification algorithm gives the maps data items in data base to certain, and event classification type, feature are carried out
Packet, and carry out multi dimensional analysis, count substantive information data.
Embodiment two：
A kind of big data method for digging providing referring to Fig. 2, the present embodiment, including：
S201：Collection internet information, using described internet information as data is activation to be analyzed to data base.
S202：The target data set of data mining is extracted from data base；
S203：Pretreatment is carried out to described target data set；
S204：Carry out data according to the function type data feature of data to the target data set through pretreatment to dig
Pick, obtains data mining results；
S205：Described data mining results are explained and evaluates, generate data mining report；
S206：Described data mining report is sent to user terminal.
Further, described pretreatment is carried out to target data set, including：
Check that target data concentrates integrity and the concordance of each data；
Each data is carried out with Denoising disposal, fills up disappearance domain and delete invalid data.
Preferably, the described function type data feature according to data enters line number to the target data set through pretreatment
According to excavation, obtain data mining results, including：
Target data set through pretreatment is associated analyze, related information content is counted according to semantic, repertorie,
And carry out distributed taxonomic clustering, and distributed burst calculating is carried out to data, result is collected and carries out parallel processing, simultaneously
Will be stored in data base the common feature of one group of data object and be divided into different classes according to classification mode, and pass through
The classification that information classification algorithm gives the maps data items in data base to certain, and event classification type, feature are carried out
Packet, and carry out multi dimensional analysis, count substantive information data.
The present invention adopts advanced data processing technique and algorithm, carries out distributed data digging to big data, it is main
It is that web page excavation, words and phrases feature, the meaning of a word, artistic conception variance analyses are carried out to big data, word segmentation processing is carried out to words and phrases, in conjunction with
Artistic conception associates statistical analysiss to info web, analyzes and seems disunity, incoherent word, finds out the language of event between artistic conception
The contact of the essence of sentence, directly counts and seems not associated data and be analyzed, obtain the hiding information of data behind, and logarithm
According to being predicted analyzing, decision tree is generated according to historical data, finds out potential valuable data message.Have easy-to-use, be easy to
Extension, easily implement, can safeguard, feature that performance is high and safe and reliable.
Embodiment three：
Fig. 3 is the schematic diagram of big data digging system provided in an embodiment of the present invention, referring to Fig. 3, the present invention provide one
Plant big data digging system to include：
Extraction unit 301, for extracting the target data set of data mining from data base；
Pretreatment unit 302, for carrying out pretreatment to described target data set；
Data mining unit 303, for according to the function type data feature of data to the number of targets through pretreatment
Carry out data mining according to collection, obtain data mining results；
Signal generating unit 304, for explaining to described data mining results and evaluating, generates data mining report.
Further, described pretreatment unit 302 includes：
Check module, for checking integrity and the concordance of the target data each data of concentration；
Processing module, for carrying out Denoising disposal, filling up disappearance domain and deleting invalid data to each data.
Preferably, described data mining unit 303, specifically for：
Target data set through pretreatment is associated analyze, related information content is counted according to semantic, repertorie,
And carry out distributed taxonomic clustering, and distributed burst calculating is carried out to data, result is collected and carries out parallel processing, simultaneously
Will be stored in data base the common feature of one group of data object and be divided into different classes according to classification mode, and pass through
The classification that information classification algorithm gives the maps data items in data base to certain, and event classification type, feature are carried out
Packet, and carry out multi dimensional analysis, count substantive information data.
Example IV：
Referring to Fig. 4, the big data digging system that the present embodiment provides includes：
Collecting unit 401, for gathering internet information, using described internet information as data is activation to be analyzed to number
According to storehouse；
Extraction unit 402, for extracting the target data set of data mining from data base；
Pretreatment unit 403, for carrying out pretreatment to described target data set；
Data mining unit 404, for according to the function type data feature of data to the number of targets through pretreatment
Carry out data mining according to collection, obtain data mining results；
Signal generating unit 405, for explaining to described data mining results and evaluating, generates data mining report；
Transmitting element 406, for sending described data mining report to user terminal.
Further, described pretreatment unit 403 includes：
Check module, for checking integrity and the concordance of the target data each data of concentration；
Processing module, for carrying out Denoising disposal, filling up disappearance domain and deleting invalid data to each data.
Preferably, described data mining unit 404, specifically for：
Target data set through pretreatment is associated analyze, related information content is counted according to semantic, repertorie,
And carry out distributed taxonomic clustering, and distributed burst calculating is carried out to data, result is collected and carries out parallel processing, simultaneously
Will be stored in data base the common feature of one group of data object and be divided into different classes according to classification mode, and pass through
The classification that information classification algorithm gives the maps data items in data base to certain, and event classification type, feature are carried out
Packet, and carry out multi dimensional analysis, count substantive information data.
The present invention adopts advanced data processing technique and algorithm, carries out distributed data digging to big data, it is main
It is that web page excavation, words and phrases feature, the meaning of a word, artistic conception variance analyses are carried out to big data, word segmentation processing is carried out to words and phrases, in conjunction with
Artistic conception associates statistical analysiss to info web, analyzes and seems disunity, incoherent word, finds out the language of event between artistic conception
The contact of the essence of sentence, directly counts and seems not associated data and be analyzed, obtain the hiding information of data behind, and logarithm
According to being predicted analyzing, decision tree is generated according to historical data, finds out potential valuable data message.Have easy-to-use, be easy to
Extension, easily implement, can safeguard, feature that performance is high and safe and reliable.
The above is only the preferred embodiment of the present invention it is noted that ordinary skill people for the art
For member, under the premise without departing from the principles of the invention, some improvements and modifications can also be made, these improvements and modifications also should
It is considered as protection scope of the present invention.
Claims (10)
1. a kind of big data method for digging is it is characterised in that methods described includes：
The target data set of data mining is extracted from data base；
Pretreatment is carried out to described target data set；
Data mining is carried out to the target data set through pretreatment according to the function type data feature of data, obtains data
Result；
Described data mining results are explained and evaluates, generate data mining report.
2. method according to claim 1 is it is characterised in that described carry out pretreatment to target data set, including：
Check that target data concentrates integrity and the concordance of each data；
Each data is carried out with Denoising disposal, fills up disappearance domain and delete invalid data.
3. method according to claim 1 is it is characterised in that the described function type data feature according to data is to warp
The target data set crossing pretreatment carries out data mining, obtains data mining results, including：
Target data set through pretreatment is associated analyze, related information content is counted according to semantic, repertorie, goes forward side by side
The distributed taxonomic clustering of row, and distributed burst calculating is carried out to data, result is collected and carries out parallel processing, will deposit simultaneously
Storage common feature of one group of data object be divided into different classes according to classification mode in data base, and pass through information
The classification that sorting algorithm gives the maps data items in data base to certain, and event classification type, feature are grouped,
And carry out multi dimensional analysis, count substantive information data.
4. method according to claim 1 it is characterised in that described from data base extract data mining target data
Before collection, also include：
Collection internet information, using described internet information as data is activation to be analyzed to data base.
5. method according to claim 1 is it is characterised in that described explain to described data mining results and comment
Valency, after generating data mining report, also includes：
Described data mining report is sent to user terminal.
6. a kind of big data digging system is it is characterised in that described system includes：
Extraction unit, for extracting the target data set of data mining from data base；
Pretreatment unit, for carrying out pretreatment to described target data set；
Data mining unit, is carried out to the target data set through pretreatment for the function type data feature according to data
Data mining, obtains data mining results；
Signal generating unit, for explaining to described data mining results and evaluating, generates data mining report.
7. system according to claim 6 is it is characterised in that described pretreatment unit includes：
Check module, for checking integrity and the concordance of the target data each data of concentration；
Processing module, for carrying out Denoising disposal, filling up disappearance domain and deleting invalid data to each data.
8. system according to claim 6 is it is characterised in that described data mining unit, specifically for：
Target data set through pretreatment is associated analyze, related information content is counted according to semantic, repertorie, goes forward side by side
The distributed taxonomic clustering of row, and distributed burst calculating is carried out to data, result is collected and carries out parallel processing, will deposit simultaneously
Storage common feature of one group of data object be divided into different classes according to classification mode in data base, and pass through information
The classification that sorting algorithm gives the maps data items in data base to certain, and event classification type, feature are grouped,
And carry out multi dimensional analysis, count substantive information data.
9. system according to claim 6 is it is characterised in that described system also includes：
Collecting unit, for gathering internet information, using described internet information as data is activation to be analyzed to data base.
10. system according to claim 6 is it is characterised in that described system also includes：
Transmitting element, for sending described data mining report to user terminal.
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| CN107577771A (en) * | 2017-09-07 | 2018-01-12 | 北京海融兴通信息安全技术有限公司 | A kind of big data digging system |
| CN107967347A (en) * | 2017-12-07 | 2018-04-27 | 湖北三新文化传媒有限公司 | Batch data processing method, server, system and storage medium |
| CN109921514A (en) * | 2019-02-01 | 2019-06-21 | 国网浙江省电力有限公司金华供电公司 | Method for power quality controlling decision support |
| CN110109906A (en) * | 2019-05-08 | 2019-08-09 | 上海泰豪迈能能源科技有限公司 | Data-storage system and method |
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| CN111695588A (en) * | 2020-04-14 | 2020-09-22 | 北京迅达云成科技有限公司 | Distributed decision tree learning system based on cloud computing |
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| CN110442623B (en) * | 2019-08-08 | 2021-08-27 | 厦门久凌创新科技有限公司 | Big data mining method and device and data mining server |
| CN110442623A (en) * | 2019-08-08 | 2019-11-12 | 厦门久凌创新科技有限公司 | Big data method for digging, device and data mining server |
| CN111382329A (en) * | 2020-02-17 | 2020-07-07 | 山东外事职业大学 | Data mining method and system for big data analysis |
| CN111695588A (en) * | 2020-04-14 | 2020-09-22 | 北京迅达云成科技有限公司 | Distributed decision tree learning system based on cloud computing |
| CN111695588B (en) * | 2020-04-14 | 2021-03-23 | 北京迅达云成科技有限公司 | Distributed decision tree learning system based on cloud computing |
| CN113408207A (en) * | 2021-06-24 | 2021-09-17 | 上海硕恩网络科技股份有限公司 | Data mining method based on social network analysis technology |
| CN114116831A (en) * | 2021-10-28 | 2022-03-01 | 福州外语外贸学院 | Big data mining processing method and device |
| CN114116831B (en) * | 2021-10-28 | 2024-07-05 | 福州外语外贸学院 | Big data mining processing method and device |
| CN115718846A (en) * | 2022-12-22 | 2023-02-28 | 云南炳暖蔡网络科技有限公司 | Big data mining method and system for intelligent interactive network |
| CN115718846B (en) * | 2022-12-22 | 2023-10-27 | 北京国联视讯信息技术股份有限公司 | Big data mining method and system for intelligent interaction network |
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