CN110457359A - A kind of association analysis method - Google Patents
A kind of association analysis method Download PDFInfo
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- CN110457359A CN110457359A CN201810420847.3A CN201810420847A CN110457359A CN 110457359 A CN110457359 A CN 110457359A CN 201810420847 A CN201810420847 A CN 201810420847A CN 110457359 A CN110457359 A CN 110457359A
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- 238000012097 association analysis method Methods 0.000 title claims abstract description 16
- 238000012098 association analyses Methods 0.000 claims abstract description 23
- 238000004458 analytical method Methods 0.000 claims abstract description 8
- 238000003306 harvesting Methods 0.000 claims description 16
- 238000012545 processing Methods 0.000 claims description 7
- 238000000034 method Methods 0.000 claims description 5
- 230000011218 segmentation Effects 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 abstract description 7
- 238000011282 treatment Methods 0.000 abstract description 5
- 238000012217 deletion Methods 0.000 description 2
- 230000037430 deletion Effects 0.000 description 2
- 235000013399 edible fruits Nutrition 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
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Abstract
The present invention relates to a kind of association analysis methods, which comprises S1: analyzing the being associated property of acquisition data；S2: acquisition data are handled based on association analysis result.The present invention can be acquired the preliminary treatment of data by the analysis to collected data and being associated property of corresponding requests, and the complexity of the association analysis is low；Reduce the transmission of hash by the preliminary treatment, to improve the efficiency of data acquisition, saved the expense of data transmission, improves understanding and receiving efficiency of the user to data.
Description
[technical field]
The invention belongs to data collecting field more particularly to a kind of association analysis methods.
[background technique]
Data acquisition refers to the process of the acquisition data-signal from sensor and other equipment under tests, answers extensively in computer
Today, data acquire the bridge connecting as computer with the external physical world, and importance is very significant.Data acquisition
Purpose be to measure the physical phenomenons such as voltage, electric current, temperature, humidity, pressure or sound, accurate DATA REASONING is several
According to the basis of acquisition.But the temperature of equipment itself is affected by environment larger, thus is facing small-signal or data variation amplitude
When smaller, the precision of acquired data will affect.And in currently available technology, it is existing can acquisition time be multiple tested sets
The data acquisition equipment of standby data is mostly single structure, thus data acquisition cost is higher and sensitivity is not high.In addition, to institute
The real-time monitoring of acquisition data and acquisition and transmission understand that efficiency is also the problem of data collecting field.It many is asked based on above-mentioned
Topic, needs a kind of new association analysis method now, and the present invention can be by carrying out collected data and corresponding requests
To be acquired the preliminary treatments of data, the complexity of the association analysis is low for the analysis of relevance；Pass through the preliminary place
Reason reduces the transmission of hash, to improve the efficiency of data acquisition, has saved the expense of data transmission, has improved user couple
The understanding of data and receiving efficiency.
[summary of the invention]
In order to solve the above problem in the prior art, the invention proposes a kind of association analysis method, this method packets
Include following steps:
S1: the being associated property of acquisition data is analyzed；
S2: acquisition data are handled based on association analysis result.
Further, the step S1 is specifically, by acquisition data and the analysis of being associated property of data harvesting request to obtain
Take association analysis result；
Further, the step S2 based on the association analysis result specifically, determine the need for re-starting
Acquire the acquisition of data；Acquisition data are handled based on the association analysis result.
Further, described to analyze acquisition data and being associated property of data harvesting request to obtain association analysis knot
Fruit, specifically: syntax and semantics analysis is carried out to obtain the classification of the data harvesting request to the data harvesting request；It is right
The data harvesting request carries out word segmentation processing to obtain one or more descriptors；By one or more of descriptors and institute
Acquisition data are stated to be matched to obtain the degree of association of the acquisition data；Using the degree of association as the association analysis knot
Fruit.
Further, described to match one or more of descriptors and the acquisition data to adopt described in acquisition
Collect the degree of association of data, specifically: the data in the descriptor and the acquisition data are matched, the description is calculated
The accumulative matching times of word；Obtain acquisition data average length；By accumulative matching times divided by acquisition data average length to obtain
To the degree of association.
Further, the accumulative matching times for calculating the descriptor, specifically: by the matching of all descriptors time
Number carries out accumulative as accumulative matching times.
Further, the acquisition acquires data average length, specifically: descriptor average length is calculated, is adopted described
The length of collection data obtains acquisition data average length divided by descriptor average length.
Further, the data harvesting request indicates the classification of the requested acquisition data of user.
The beneficial effect comprise that the analysis to collected data and being associated property of corresponding requests can be passed through
To be acquired the preliminary treatment of data, the complexity of the association analysis is low；Reduced by the preliminary treatment useless
The transmission of data has saved the expense of data transmission to improve the efficiency of data acquisition, improve user to the understanding of data and
Receiving efficiency.
[Detailed description of the invention]
Described herein the drawings are intended to provide a further understanding of the invention, constitutes part of this application, but
It does not constitute improper limitations of the present invention, in the accompanying drawings:
Fig. 1 is the flow chart of association analysis method of the invention.
[specific embodiment]
Come that the present invention will be described in detail below in conjunction with attached drawing and specific embodiment, illustrative examples therein and says
It is bright to be only used to explain the present invention but not as a limitation of the invention.
A kind of association analysis method applied by the present invention is described in detail, the method includes following step:
S1: the acquisition data from one or more acquisition units are received；
Wherein the acquisition unit is sensing unit perhaps level-one acquisition or overall receipts of the data warehouse to carry out data
Collection and storage；
The acquisition data are the acquisition request based on user terminal；
Preferred: the acquisition data are based on domain classification；Such as: heat supply acquires data etc.；
S2: analyzing the being associated property of acquisition data, is handled based on association analysis result acquisition data
Data are acquired after handling with acquisition；It is specific: acquisition data being analyzed with being associated property of data harvesting request and are associated with obtaining
Property analysis result；Determine the need for re-starting the acquisition of acquisition data based on the association analysis result；Based on described
Association analysis result handles acquisition data；
It is described to analyze acquisition data and being associated property of data harvesting request to obtain association analysis as a result, specific
Are as follows: syntax and semantics analysis is carried out to obtain the classification of the data harvesting request to the data harvesting request；To the number
Request to carry out word segmentation processing according to acquisition to obtain one or more descriptors；By one or more of descriptors and the acquisition
Data are matched to obtain the degree of association of the acquisition data；Using the degree of association as the association analysis result；
It is described to match one or more of descriptors to obtain the acquisition data with the acquisition data
The degree of association, specifically: the data in the descriptor and the acquisition data are matched, the accumulative of the descriptor is calculated
Matching times；Obtain acquisition data average length；By accumulative matching times divided by acquisition data average length to obtain the degree of association；
It is preferred: the step further include: to record matching position of all descriptors in acquisition data；And the matching position is pressed
It is stored in matching queue according to matched sequence；
The accumulative matching times for calculating the descriptor, specifically: the matching times of all descriptors are carried out tired
It is counted as to add up matching times；
The acquisition acquires data average length, specifically: descriptor average length is calculated, by the length of the acquisition data
Degree obtains acquisition data average length divided by descriptor average length；
Preferred: the data harvesting request indicates the classification of the requested acquisition data of user；
Preferred: the classification includes the classification of classification, the user demand of product, industrial circle classification etc.；
The acquisition for determining the need for re-starting acquisition data based on the association analysis result, specifically,
If it is more than criticality threshold value that the degree of association, which is less than or equal to the first degree of association threshold value and the criticality of the acquisition data, weigh
Newly it is acquired the acquisition of data；If the degree of association is too small, then it represents that the degree of association of data is too low, is needed at this time from acquisition unit
It sets out and carries out Resolving probiems；
The criticality is to acquire the corresponding criticality for obtaining acquisition unit of data；
It is described that acquisition data are handled based on the association analysis result, specifically: if the degree of association is small
In the second degree of association threshold value and it is greater than the first degree of association threshold value, is determined in the acquisition data based on the matching queue and do not sent out
Raw matched acquisition data segment, if the acquisition data segment, length is more than the first length threshold, described in the deletion of selectivity
The data in data segment are acquired, and the remaining data of the acquisition data are sequentially connected and are adopted as treated
Collect data；
Data in the selective deletion acquisition data segment, specifically: it deletes in the acquisition data segment
All partial data sections；
It is preferred: if the degree of association is more than or equal to the second degree of association threshold value, it is determined that the acquisition data, which exist, closes
Connection property；No longer the acquisition data are handled；Described unprocessed and processed acquisition data are merged into conduct
Data are acquired after processing；
Preferred: first degree of association threshold value is much small with the second degree of association threshold value；
It is preferred: the classification phase of the value and the acquisition data of first degree of association threshold value and the second degree of association threshold value
It closes；
S3: user terminal is sent to by data are acquired after the processing；It is specific: to be sent to data are acquired after the processing
User terminal, and data are acquired after the processing is presented in the user terminal；
It is preferred: the presentation of the acquisition data is carried out based on the characteristics of acquisition data；Specifically: more for picture
Acquisition data use the first presentation mode, the second presentation mode is used for the acquisition data more than data；
Wherein: the first presentation mode is the presentation outstanding for carrying out picture；Second presentation mode is by emphasis data
It is highlighted；
The above description is only a preferred embodiment of the present invention, thus it is all according to the configuration described in the scope of the patent application of the present invention,
The equivalent change or modification that feature and principle are done, is included in the scope of the patent application of the present invention.
Claims (8)
1. a kind of association analysis method, which is characterized in that this method comprises the following steps:
S1: the being associated property of acquisition data is analyzed；
S2: acquisition data are handled based on association analysis result.
2. association analysis method according to claim 1, which is characterized in that the step S1 is specifically, number will be acquired
It analyzes according to being associated property of data harvesting request to obtain association analysis result.
3. association analysis method according to claim 2, which is characterized in that the step S2 is specifically, based on described
Association analysis result determines the need for re-starting the acquisition of acquisition data；Based on the association analysis result to acquisition
Data are handled.
4. association analysis method according to claim 3, which is characterized in that described to ask acquisition data and data acquisition
Ask being associated property analysis to obtain association analysis as a result, specifically: to the data harvesting request carry out syntax and semantics
It analyzes to obtain the classification of the data harvesting request；Word segmentation processing is carried out to obtain one or more to the data harvesting request
A descriptor；One or more of descriptors and the acquisition data are matched to obtain the association of the acquisition data
Degree；Using the degree of association as the association analysis result.
5. association analysis method according to claim 4, which is characterized in that described by one or more of descriptors
It is matched with the acquisition data to obtain the degree of association of the acquisition data, specifically: by the descriptor and described adopt
Data in collection data are matched, and the accumulative matching times of the descriptor are calculated；Obtain acquisition data average length；It will tire out
Matching times are counted divided by acquisition data average length to obtain the degree of association.
6. association analysis method according to claim 5, which is characterized in that accumulative for calculating the descriptor
With number, specifically: the matching times of all descriptors are carried out accumulative as accumulative matching times.
7. association analysis method according to claim 6, which is characterized in that the acquisition acquires data average length,
Specifically: descriptor average length is calculated, the length of the acquisition data is obtained into acquisition number divided by descriptor average length
According to average length.
8. association analysis method according to claim 7, which is characterized in that the data harvesting request indicates user
The classification of requested acquisition data.
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| CN201810420847.3A CN110457359B (en) | 2018-05-04 | 2018-05-04 | Correlation analysis method |
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| CN201810420847.3A CN110457359B (en) | 2018-05-04 | 2018-05-04 | Correlation analysis method |
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| CN110457359B CN110457359B (en) | 2024-03-08 |
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102035678A (en) * | 2010-12-16 | 2011-04-27 | 中国电子科技集团公司第三十研究所 | Multidimensional comprehensive situation display system based on degree of association |
| CN103729420A (en) * | 2013-12-20 | 2014-04-16 | 潘大庆 | Microblog hotspot tracking system and method |
| CN106202514A (en) * | 2016-07-21 | 2016-12-07 | 北京邮电大学 | Accident based on Agent is across the search method of media information and system |
| WO2017114290A1 (en) * | 2015-12-31 | 2017-07-06 | 武汉安天信息技术有限责任公司 | Method and system for detecting sample relevance, electronic device and storage medium |
| CN107346329A (en) * | 2017-06-19 | 2017-11-14 | 上海德启信息科技有限公司 | A kind of data processing method and device |
| CN107704586A (en) * | 2017-10-09 | 2018-02-16 | 陈包容 | A kind of methods, devices and systems of user's portrait based on User Activity address |
| CN107885831A (en) * | 2017-11-09 | 2018-04-06 | 北京中电普华信息技术有限公司 | A kind of collection and analysis method and system of field data |
| CN107951496A (en) * | 2017-11-27 | 2018-04-24 | 新绎健康科技有限公司 | Method and system based on multi-scale entropy analysis psychosoma relevance |
-
2018
- 2018-05-04 CN CN201810420847.3A patent/CN110457359B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102035678A (en) * | 2010-12-16 | 2011-04-27 | 中国电子科技集团公司第三十研究所 | Multidimensional comprehensive situation display system based on degree of association |
| CN103729420A (en) * | 2013-12-20 | 2014-04-16 | 潘大庆 | Microblog hotspot tracking system and method |
| WO2017114290A1 (en) * | 2015-12-31 | 2017-07-06 | 武汉安天信息技术有限责任公司 | Method and system for detecting sample relevance, electronic device and storage medium |
| CN106202514A (en) * | 2016-07-21 | 2016-12-07 | 北京邮电大学 | Accident based on Agent is across the search method of media information and system |
| CN107346329A (en) * | 2017-06-19 | 2017-11-14 | 上海德启信息科技有限公司 | A kind of data processing method and device |
| CN107704586A (en) * | 2017-10-09 | 2018-02-16 | 陈包容 | A kind of methods, devices and systems of user's portrait based on User Activity address |
| CN107885831A (en) * | 2017-11-09 | 2018-04-06 | 北京中电普华信息技术有限公司 | A kind of collection and analysis method and system of field data |
| CN107951496A (en) * | 2017-11-27 | 2018-04-24 | 新绎健康科技有限公司 | Method and system based on multi-scale entropy analysis psychosoma relevance |
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