CN112052279A - Data mining method and system based on big data - Google Patents
Data mining method and system based on big data Download PDFInfo
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- CN112052279A CN112052279A CN202010911330.1A CN202010911330A CN112052279A CN 112052279 A CN112052279 A CN 112052279A CN 202010911330 A CN202010911330 A CN 202010911330A CN 112052279 A CN112052279 A CN 112052279A
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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
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B15/00—Systems controlled by a computer
- G05B15/02—Systems controlled by a computer electric
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/4183—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/26—Pc applications
- G05B2219/2642—Domotique, domestic, home control, automation, smart house
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The embodiment of the invention provides a data mining method and system based on big data, for any linkage process, a linkage control element sequence included in an Internet of things linkage process set in linkage control of the linkage process in a set period is determined according to linkage members of the Internet of things linkage process in the minimum range, and if a first target linkage process and a second target linkage process including the same linkage control element sequence exist and the process duration interval difference of the Internet of things linkage processes corresponding to the same element in the first target linkage process and the second target linkage process in linkage control of the same linkage control element sequence is smaller than or equal to a preset process duration interval difference threshold value, the first target linkage process and the second target linkage process are determined to form a target linkage data mining combination. Therefore, linkage data mining processing can be carried out through the target linkage data mining combination, and the requirements of mining pertinence and accuracy in the linkage data mining process can be met.
Description
Technical Field
The invention relates to the technical field of data mining, in particular to a data mining method and system based on big data.
Background
At present, in the linkage data mining process, the requirements of mining pertinence and accuracy in the linkage data mining process are difficult to meet.
Disclosure of Invention
In view of this, an object of the embodiments of the present invention is to provide a data mining method and system based on big data, which can meet the requirements of mining pertinence and accuracy in a linkage data mining process.
According to an aspect of an embodiment of the present invention, a data mining method based on big data is provided, which is applied to a server, the server is in communication connection with a plurality of smart home linkage devices in an intelligent linkage network environment, the smart home linkage devices are used for performing smart home linkage control, and the method includes:
acquiring linkage response data of each linkage process of each intelligent home linkage device, and determining an internet of things linkage process of each linkage process in linkage control in a set period and linkage members of each internet of things linkage process in linkage control according to the linkage response data;
for any linkage process, determining a linkage control element sequence included in the linkage process set of the Internet of things which is in linkage control in the set period according to the linkage member of the linkage process of the Internet of things in the minimum range; the elements of each linkage control element sequence are internet of things linkage processes which are in linkage control in the set period in the linkage process, the sum of the elements in each linkage control element sequence is equal to the linkage member of the internet of things linkage process in the minimum range, and the same internet of things linkage processes which are in linkage control by different linkage members in the same linkage process belong to different process nodes;
judging whether a first target linkage process and a second target linkage process comprising the same linkage control element sequence exist or not, if the first target linkage process and the second target linkage process comprising the same linkage control element sequence exist, judging whether the process continuous interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence under linkage control of the first target linkage process and the second target linkage process are both smaller than or equal to a preset process continuous interval difference threshold value, if the process continuous interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence under linkage control of the first target linkage process and the second target linkage process are both smaller than or equal to a preset process continuous interval difference threshold value, determining that the first target linkage process and the second target linkage process form a target linkage data mining combination.
In a possible example, after the step of determining, according to the linkage response data, an internet of things linkage process in which each linkage process is in linkage control in a set period, and linkage members in each internet of things linkage process in linkage control, the method further includes:
determining the linkage process of the linkage member of the Internet of things linkage process with the number of times of linkage control of the Internet of things linkage process in the set period being more than or equal to the minimum range as a target linkage process;
for any linkage process, determining a linkage control element sequence included in the linkage control Internet of things linkage process set in the set period according to the linkage member of the linkage process of the Internet of things in the minimum range, wherein the linkage control element sequence includes:
and for any target linkage process, determining a linkage control element sequence included in the linkage control Internet of things linkage process set of the target linkage process in the set period according to the linkage member of the linkage process of the Internet of things in the minimum range.
In one possible example, the step of determining whether there are a first target linkage process and a second target linkage process of the same linkage control element sequence includes:
sequencing elements included in the linkage control element sequence of each linkage process according to the linkage member sequence of the linkage process of the linkage control Internet of things;
and if the elements included in the linkage control element sequences of different linkage processes are the same and the sequence of each element is consistent, determining that a first target linkage process and a second target linkage process including the same linkage control element sequence exist.
In a possible example, the step of determining whether the process duration interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence are both less than or equal to a preset process duration interval difference threshold value includes:
sequentially judging whether the process duration interval difference of the internet of things linkage process corresponding to each same element in the first target linkage process and the second target linkage process linkage control same linkage control element sequence is less than or equal to a preset process duration interval difference threshold value or not according to the linkage member sequence of the linkage control internet of things linkage process;
if the process continuous interval difference of the internet of things linkage processes corresponding to the same elements in the first target linkage process and the second target linkage process linkage control element sequence is smaller than or equal to a preset process continuous interval difference threshold, determining that the process continuous interval difference of the internet of things linkage processes corresponding to the same elements in the first target linkage process and the second target linkage process linkage control element sequence is smaller than or equal to a preset process continuous interval difference threshold.
In one possible example, the method further comprises:
if the first target linkage process and the second target linkage process comprising the same linkage control element sequence do not exist, determining that a target linkage data mining combination does not exist; and/or
And if the process duration interval difference of the internet of things linkage process corresponding to at least one same element in the same linkage control element sequence is controlled by the first target linkage process and the second target linkage process in a linkage manner and is larger than a preset process duration interval difference threshold value, determining that the first target linkage process and the second target linkage process do not form a target linkage data mining combination.
According to another aspect of the embodiments of the present invention, there is provided a data mining system based on big data, applied to a server, where the server is in communication connection with a plurality of smart home linkage devices in an intelligent linkage network environment, and the smart home linkage devices are used for performing smart home linkage control, and the system includes:
the system comprises an acquisition module, a linkage module and a linkage module, wherein the acquisition module is used for acquiring linkage response data of each linkage process of each intelligent home linkage device, and determining the linkage process of the Internet of things in linkage control in a set period of each linkage process and linkage members in linkage control of the linkage process of each Internet of things according to the linkage response data;
the determining module is used for determining a linkage control element sequence included in the linkage process set of the Internet of things which is in linkage control in the set period of the linkage process according to the linkage member of the linkage process of the Internet of things in the minimum range for any linkage process; the elements of each linkage control element sequence are internet of things linkage processes which are in linkage control in the set period in the linkage process, the sum of the elements in each linkage control element sequence is equal to the linkage member of the internet of things linkage process in the minimum range, and the same internet of things linkage processes which are in linkage control by different linkage members in the same linkage process belong to different process nodes;
a judging module for judging whether a first target linkage process and a second target linkage process including the same linkage control element sequence exist, if the first target linkage process and the second target linkage process including the same linkage control element sequence exist, judging whether the process continuous interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence under linkage control of the first target linkage process and the second target linkage process are both smaller than or equal to a preset process continuous interval difference threshold value, if the process continuous interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence under linkage control of the first target linkage process and the second target linkage process are both smaller than or equal to a preset process continuous interval difference threshold value, determining that the first target linkage process and the second target linkage process form a target linkage data mining combination.
According to another aspect of the embodiments of the present invention, a readable storage medium is provided, and the readable storage medium stores thereon a computer program, which when executed by a processor can perform the steps of the big data based data mining method described above.
Compared with the prior art, the big data-based data mining method and system provided by the embodiment of the invention determine the linkage processes of the internet of things in linkage control in a set period of each linkage process according to the linkage response data, and linkage members in linkage control of the linkage processes of the internet of things, and then determine the linkage control element sequences included in the linkage process set of the internet of things in linkage control in the set period of the linkage process according to the linkage members in the linkage processes of the internet of things in the minimum range for any linkage process, if a first target linkage process and a second target linkage process including the same linkage control element sequence exist, and the process duration interval difference of the linkage processes of the internet of things corresponding to the same element in the same linkage control element sequence in the first target linkage process and the second target linkage process is less than or equal to the preset process duration interval difference threshold, it is determined that the first target linkage process and the second target linkage process form a target linkage data mining combination. Therefore, linkage data mining processing can be carried out through the target linkage data mining combination, and the requirements of mining pertinence and accuracy in the linkage data mining process can be met.
In order to make the aforementioned objects, features and advantages of the embodiments of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments are briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the process duration, and for those skilled in the art, other related drawings can be obtained according to the drawings without creative efforts.
FIG. 1 illustrates a component diagram of a server provided by an embodiment of the invention;
FIG. 2 is a flow chart of a big data-based data mining method according to an embodiment of the present invention;
fig. 3 shows a functional block diagram of a big data-based data mining system according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood by the scholars in the technical field, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. According to the embodiment of the invention, all other embodiments obtained by a person with ordinary skill in the art without creative efforts belong to the process duration protected by the invention.
The terms "first," "second," "third," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Fig. 1 shows an exemplary component schematic of a server 100. The server 100 may include one or more processors 104, such as one or more Central Processing Units (CPUs), each of which may implement one or more hardware threads. The server 100 may also include any storage media 106 for storing any kind of information, such as code, settings, data, etc. For example, and without limitation, storage medium 106 may include any one or more of the following in combination: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any storage medium may use any technology to store information. Further, any storage medium may provide volatile or non-volatile retention of information. Further, any storage medium may represent a fixed or removable component of server 100. In one case, when the processor 104 executes the associated instructions stored in any storage medium or combination of storage media, the server 100 may perform any of the operations of the associated instructions. The server 100 further comprises one or more drive units 108 for interacting with any storage medium, such as a hard disk drive unit, an optical disk drive unit, etc.
The server 100 also includes input/output 110 (I/O) for receiving various inputs (via input unit 112) and for providing various outputs (via output unit 114)). One particular output mechanism may include a presentation device 116 and an associated Graphical User Interface (GUI) 118. The server 100 may also include one or more network interfaces 120 for exchanging data with other devices via one or more communication units 122. One or more communication buses 124 couple the above-described components together.
The communication unit 122 may be implemented in any manner, such as over a local area network, a wide area network (e.g., the internet), a point-to-point connection, etc., or any combination thereof. The communication unit 122 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers 100, and so forth, governed by any protocol or combination of protocols.
Fig. 2 is a flowchart illustrating a big data-based data mining method according to an embodiment of the present invention, which can be executed by the server 100 shown in fig. 1, and the detailed steps of the big data-based data mining method are described as follows.
And S110, acquiring linkage response data of each linkage process of each intelligent home linkage device, and determining the linkage processes of the Internet of things in linkage control in a set period of each linkage process and linkage members in linkage control of the linkage processes of the Internet of things according to the linkage response data.
And step S120, for any linkage process, determining a linkage control element sequence included in the linkage process set of the Internet of things in linkage control in the set period according to the linkage member of the linkage process of the Internet of things in the minimum range. The elements of each linkage control element sequence are internet of things linkage processes which are in linkage control in the set period in the linkage process, the sum of the elements in each linkage control element sequence is equal to the linkage member of the internet of things linkage process in the minimum range, and the same internet of things linkage processes which are in linkage control by different linkage members in the same linkage process belong to different process nodes.
Step S130, judging whether a first target linkage process and a second target linkage process comprising the same linkage control element sequence exist, if the first target linkage process and the second target linkage process comprising the same linkage control element sequence exist, judging whether the process continuous interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence under linkage control of the first target linkage process and the second target linkage process are both smaller than or equal to a preset process continuous interval difference threshold value, if the process continuous interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence under linkage control of the first target linkage process and the second target linkage process are both smaller than or equal to a preset process continuous interval difference threshold value, determining that the first target linkage process and the second target linkage process form a target linkage data mining combination.
Based on the above steps, the present embodiment determines the linkage process of the internet of things in linkage control in a set period according to the linkage response data, and linkage members for linkage control of linkage processes of the internet of things, and then for any linkage process, determining a linkage control element sequence included in the linkage process set of the Internet of things which is in linkage control in a set period in the linkage process according to the linkage member of the linkage process of the Internet of things in the minimum range, if there is a first target linkage process and a second target linkage process that include the same sequence of linkage control elements, and the process continuous interval difference of the linkage processes of the internet of things corresponding to the same element in the linkage control element sequence of the first target linkage process and the second target linkage process is less than or equal to the preset process continuous interval difference threshold value, it is determined that the first target linkage process and the second target linkage process form a target linkage data mining combination. Therefore, linkage data mining processing can be carried out through the target linkage data mining combination, and the requirements of mining pertinence and accuracy in the linkage data mining process can be met.
In a possible design, the present embodiment may determine, as the target linkage process, a linkage process of a linkage member that performs linkage control on the internet of things linkage process in the set period, where the number of times of linkage control on the internet of things linkage process is greater than or equal to the minimum range. In this way, for any target linkage process, the linkage control element sequence included in the internet of things linkage process set in linkage control of the target linkage process in the set period may be determined according to the linkage member of the internet of things linkage process in the minimum range in step S120.
In one possible design, for step S130, the elements included in the linkage control element sequence of each linkage process may be sorted according to the linkage member order of the linkage process of the linkage control internet of things. And if the elements included in the linkage control element sequences of different linkage processes are the same and the sequence of each element is consistent, determining that a first target linkage process and a second target linkage process including the same linkage control element sequence exist.
In a possible design, for step S130, it may be sequentially determined, according to a linkage member sequence of the linkage process of the linkage control internet of things, whether a process duration interval difference of the linkage process of the internet of things corresponding to each same element in the linkage control element sequence of the first target linkage process and the second target linkage process is less than or equal to a preset process duration interval difference threshold.
If the process continuous interval difference of the internet of things linkage processes corresponding to the same elements in the first target linkage process and the second target linkage process linkage control element sequence is smaller than or equal to a preset process continuous interval difference threshold, determining that the process continuous interval difference of the internet of things linkage processes corresponding to the same elements in the first target linkage process and the second target linkage process linkage control element sequence is smaller than or equal to a preset process continuous interval difference threshold.
In one possible design, for step S130, if there is no first target linkage process and no second target linkage process that include the same linkage control element sequence, it is determined that there is no target linkage data mining combination; and/or if the process duration interval difference of the internet of things linkage process corresponding to at least one same element in the same linkage control element sequence is controlled by the first target linkage process and the second target linkage process in a linkage manner and is larger than a preset process duration interval difference threshold value, determining that the first target linkage process and the second target linkage process do not form a target linkage data mining combination.
Fig. 3 shows a functional block diagram of the big data based data mining system 200 according to an embodiment of the present invention, where the functions implemented by the big data based data mining system 200 may correspond to the steps executed by the foregoing method. The big data-based data mining system 200 may be understood as the server 100, or a processor of the server 100, or may be understood as a component that is independent from the server 100 or the processor and implements the functions of the present invention under the control of the server 100, as shown in fig. 3, and the functions of the functional modules of the big data-based data mining system 200 are described in detail below.
The obtaining module 210 is configured to obtain linkage response data of each linkage process of each smart home linkage device, and determine, according to the linkage response data, an internet of things linkage process of each linkage process in a set period through linkage control, and linkage members of each internet of things linkage process through linkage control.
The determining module 220 is configured to determine, for any linkage process, a linkage control element sequence included in the internet of things linkage process set in linkage control in the set period according to the linkage member of the internet of things linkage process in the minimum range. The elements of each linkage control element sequence are internet of things linkage processes which are in linkage control in the set period in the linkage process, the sum of the elements in each linkage control element sequence is equal to the linkage member of the internet of things linkage process in the minimum range, and the same internet of things linkage processes which are in linkage control by different linkage members in the same linkage process belong to different process nodes.
The determining module 230 is configured to determine whether there are a first target linkage process and a second target linkage process including the same linkage control element sequence, and if there are a first target linkage process and a second target linkage process including the same linkage control element sequence, judging whether the process continuous interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence under linkage control of the first target linkage process and the second target linkage process are both smaller than or equal to a preset process continuous interval difference threshold value, if the process continuous interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence under linkage control of the first target linkage process and the second target linkage process are both smaller than or equal to a preset process continuous interval difference threshold value, determining that the first target linkage process and the second target linkage process form a target linkage data mining combination.
In one possible example, the determining module 220 is further configured to:
determining the linkage process of the linkage member of the Internet of things linkage process with the number of times of linkage control of the Internet of things linkage process in the set period being more than or equal to the minimum range as a target linkage process;
and for any target linkage process, determining a linkage control element sequence included in the linkage control Internet of things linkage process set of the target linkage process in the set period according to the linkage member of the linkage process of the Internet of things in the minimum range.
In one possible example, the determining module 230 is configured to determine whether a first target linkage process and a second target linkage process of the same linkage control element sequence exist by:
sequencing elements included in the linkage control element sequence of each linkage process according to the linkage member sequence of the linkage process of the linkage control Internet of things;
and if the elements included in the linkage control element sequences of different linkage processes are the same and the sequence of each element is consistent, determining that a first target linkage process and a second target linkage process including the same linkage control element sequence exist.
In a possible example, the determining module 230 is configured to determine whether the process duration difference of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence is less than or equal to a preset process duration difference threshold by the following means:
sequentially judging whether the process duration interval difference of the internet of things linkage process corresponding to each same element in the first target linkage process and the second target linkage process linkage control same linkage control element sequence is less than or equal to a preset process duration interval difference threshold value or not according to the linkage member sequence of the linkage control internet of things linkage process;
if the process continuous interval difference of the internet of things linkage processes corresponding to the same elements in the first target linkage process and the second target linkage process linkage control element sequence is smaller than or equal to a preset process continuous interval difference threshold, determining that the process continuous interval difference of the internet of things linkage processes corresponding to the same elements in the first target linkage process and the second target linkage process linkage control element sequence is smaller than or equal to a preset process continuous interval difference threshold.
In one possible example, the determining module 230 is further configured to:
if the first target linkage process and the second target linkage process comprising the same linkage control element sequence do not exist, determining that a target linkage data mining combination does not exist; and/or
And if the process duration interval difference of the internet of things linkage process corresponding to at least one same element in the same linkage control element sequence is controlled by the first target linkage process and the second target linkage process in a linkage manner and is larger than a preset process duration interval difference threshold value, determining that the first target linkage process and the second target linkage process do not form a target linkage data mining combination.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus and method embodiments described above are illustrative only, as the flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
Alternatively, all or part of the implementation may be in software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the process duration of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any drawing credit or debit acknowledgement in the claims should not be construed as limiting the claim concerned.
Claims (2)
1. The big data-based data mining method is applied to a server, the server is in communication connection with a plurality of intelligent home linkage devices in an intelligent linkage network environment, the intelligent home linkage devices are used for intelligent home linkage control, and the method comprises the following steps:
acquiring linkage response data of each linkage process of each intelligent home linkage device, and determining an internet of things linkage process of each linkage process in linkage control in a set period and linkage members of each internet of things linkage process in linkage control according to the linkage response data;
for any linkage process, determining a linkage control element sequence included in the linkage process set of the Internet of things which is in linkage control in the set period according to the linkage member of the linkage process of the Internet of things in the minimum range; the elements of each linkage control element sequence are internet of things linkage processes which are in linkage control in the set period in the linkage process, the sum of the elements in each linkage control element sequence is equal to the linkage member of the internet of things linkage process in the minimum range, and the same internet of things linkage processes which are in linkage control by different linkage members in the same linkage process belong to different process nodes;
judging whether a first target linkage process and a second target linkage process comprising the same linkage control element sequence exist or not, if the first target linkage process and the second target linkage process comprising the same linkage control element sequence exist, judging whether the process continuous interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence under linkage control of the first target linkage process and the second target linkage process are both smaller than or equal to a preset process continuous interval difference threshold value, if the process continuous interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence under linkage control of the first target linkage process and the second target linkage process are both smaller than or equal to a preset process continuous interval difference threshold value, determining that the first target linkage process and the second target linkage process form a target linkage data mining combination;
after the step of determining the linkage processes of the internet of things in linkage control in a set period of each linkage process according to the linkage response data and the step of linkage members in linkage control of the linkage processes of the internet of things, the method further comprises the following steps:
determining the linkage process of the linkage member of the Internet of things linkage process with the number of times of linkage control of the Internet of things linkage process in the set period being more than or equal to the minimum range as a target linkage process;
for any linkage process, determining a linkage control element sequence included in the linkage control Internet of things linkage process set in the set period according to the linkage member of the linkage process of the Internet of things in the minimum range, wherein the linkage control element sequence includes:
for any target linkage process, determining a linkage control element sequence included in the linkage control Internet of things linkage process set of the target linkage process in the set period according to the linkage member of the linkage process of the Internet of things in the minimum range;
the step of judging whether a first target linkage process and a second target linkage process of the same linkage control element sequence exist comprises the following steps:
sequencing elements included in the linkage control element sequence of each linkage process according to the linkage member sequence of the linkage process of the linkage control Internet of things;
if the linkage control element sequences of different linkage processes comprise the same elements and the sequence of each element is consistent, determining that a first target linkage process and a second target linkage process comprising the same linkage control element sequence exist;
the step of judging whether the process continuous interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence are both smaller than or equal to a preset process continuous interval difference threshold value or not in linkage control of the first target linkage process and the second target linkage process comprises the following steps:
sequentially judging whether the process duration interval difference of the internet of things linkage process corresponding to each same element in the first target linkage process and the second target linkage process linkage control same linkage control element sequence is less than or equal to a preset process duration interval difference threshold value or not according to the linkage member sequence of the linkage control internet of things linkage process;
if the process continuous interval difference of the internet of things linkage process corresponding to each same element in the first target linkage process and the second target linkage process linkage control same linkage control element sequence is less than or equal to a preset process continuous interval difference threshold, determining that the process continuous interval difference of the internet of things linkage process corresponding to the same element in the first target linkage process and the second target linkage process linkage control same linkage control element sequence is less than or equal to a preset process continuous interval difference threshold;
the method further comprises the following steps:
if the first target linkage process and the second target linkage process comprising the same linkage control element sequence do not exist, determining that a target linkage data mining combination does not exist; and/or
And if the process duration interval difference of the internet of things linkage process corresponding to at least one same element in the same linkage control element sequence is controlled by the first target linkage process and the second target linkage process in a linkage manner and is larger than a preset process duration interval difference threshold value, determining that the first target linkage process and the second target linkage process do not form a target linkage data mining combination.
2. The utility model provides a data mining system based on big data which characterized in that is applied to the server, a plurality of intelligent house aggregate unit communication connection on server and the intelligent linkage network environment, intelligent house aggregate unit is used for carrying out intelligent house aggregate unit, the system includes:
the system comprises an acquisition module, a linkage module and a linkage module, wherein the acquisition module is used for acquiring linkage response data of each linkage process of each intelligent home linkage device, and determining the linkage process of the Internet of things in linkage control in a set period of each linkage process and linkage members in linkage control of the linkage process of each Internet of things according to the linkage response data;
the determining module is used for determining a linkage control element sequence included in the linkage process set of the Internet of things which is in linkage control in the set period of the linkage process according to the linkage member of the linkage process of the Internet of things in the minimum range for any linkage process; the elements of each linkage control element sequence are internet of things linkage processes which are in linkage control in the set period in the linkage process, the sum of the elements in each linkage control element sequence is equal to the linkage member of the internet of things linkage process in the minimum range, and the same internet of things linkage processes which are in linkage control by different linkage members in the same linkage process belong to different process nodes;
a judging module for judging whether a first target linkage process and a second target linkage process including the same linkage control element sequence exist, if the first target linkage process and the second target linkage process including the same linkage control element sequence exist, judging whether the process continuous interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence under linkage control of the first target linkage process and the second target linkage process are both smaller than or equal to a preset process continuous interval difference threshold value, if the process continuous interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence under linkage control of the first target linkage process and the second target linkage process are both smaller than or equal to a preset process continuous interval difference threshold value, determining that the first target linkage process and the second target linkage process form a target linkage data mining combination;
the determining module is further configured to:
determining the linkage process of the linkage member of the Internet of things linkage process with the number of times of linkage control of the Internet of things linkage process in the set period being more than or equal to the minimum range as a target linkage process;
for any target linkage process, determining a linkage control element sequence included in the linkage control Internet of things linkage process set of the target linkage process in the set period according to the linkage member of the linkage process of the Internet of things in the minimum range;
the judging module is used for judging whether a first target linkage process and a second target linkage process of the same linkage control element sequence exist or not in the following mode:
sequencing elements included in the linkage control element sequence of each linkage process according to the linkage member sequence of the linkage process of the linkage control Internet of things;
if the linkage control element sequences of different linkage processes comprise the same elements and the sequence of each element is consistent, determining that a first target linkage process and a second target linkage process comprising the same linkage control element sequence exist;
the judging module is used for judging whether the process continuous interval differences of the internet of things linkage processes corresponding to the same element in the same linkage control element sequence are all smaller than or equal to a preset process continuous interval difference threshold value through the following modes:
sequentially judging whether the process duration interval difference of the internet of things linkage process corresponding to each same element in the first target linkage process and the second target linkage process linkage control same linkage control element sequence is less than or equal to a preset process duration interval difference threshold value or not according to the linkage member sequence of the linkage control internet of things linkage process;
if the process continuous interval difference of the internet of things linkage process corresponding to each same element in the first target linkage process and the second target linkage process linkage control same linkage control element sequence is less than or equal to a preset process continuous interval difference threshold, determining that the process continuous interval difference of the internet of things linkage process corresponding to the same element in the first target linkage process and the second target linkage process linkage control same linkage control element sequence is less than or equal to a preset process continuous interval difference threshold;
the judging module is further configured to:
if the first target linkage process and the second target linkage process comprising the same linkage control element sequence do not exist, determining that a target linkage data mining combination does not exist; and/or
And if the process duration interval difference of the internet of things linkage process corresponding to at least one same element in the same linkage control element sequence is controlled by the first target linkage process and the second target linkage process in a linkage manner and is larger than a preset process duration interval difference threshold value, determining that the first target linkage process and the second target linkage process do not form a target linkage data mining combination.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010911330.1A CN112052279A (en) | 2020-09-02 | 2020-09-02 | Data mining method and system based on big data |
| PCT/CN2020/126048 WO2021143291A1 (en) | 2020-09-02 | 2020-11-03 | Method and system for data mining based on big data |
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| CN202010911330.1A CN112052279A (en) | 2020-09-02 | 2020-09-02 | Data mining method and system based on big data |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101408754B (en) * | 2008-10-30 | 2010-12-29 | 中山大学 | Intelligent house optimizing system based on data excavation |
| CN103368921B (en) * | 2012-04-06 | 2016-08-10 | 三星电子（中国）研发中心 | Distributed user modeling and method for smart machine |
| US9798783B2 (en) * | 2013-06-14 | 2017-10-24 | Actuate Corporation | Performing data mining operations within a columnar database management system |
| CN106549833B (en) * | 2015-09-21 | 2020-01-21 | 阿里巴巴集团控股有限公司 | Control method and device for intelligent household equipment |
| CN105739317A (en) * | 2016-02-25 | 2016-07-06 | 中国联合网络通信集团有限公司 | Intelligent household control method, device and system |
| CN106950847A (en) * | 2017-05-09 | 2017-07-14 | 青岛理工大学 | A kind of intelligent home control system based on ZigBee and cloud computing |
| CN111007735A (en) * | 2019-12-20 | 2020-04-14 | 睿住科技有限公司 | Intelligent household equipment linkage method and system based on community license plate recognition |
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