CN112182066A - Big data information mining system based on fuzzy theory - Google Patents
Big data information mining system based on fuzzy theory Download PDFInfo
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- CN112182066A CN112182066A CN202011035118.XA CN202011035118A CN112182066A CN 112182066 A CN112182066 A CN 112182066A CN 202011035118 A CN202011035118 A CN 202011035118A CN 112182066 A CN112182066 A CN 112182066A
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Abstract
The invention discloses a big data information mining system based on a fuzzy theory, which relates to the technical field of data mining processing, and aims at the problem of low searching speed in the prior art, the invention provides a scheme which comprises a plurality of computer terminals and a cloud processing system, wherein the computer terminals are connected with the cloud processing system in a wired or wireless manner.
Description
Technical Field
The invention relates to the technical field of data mining processing, in particular to a big data information mining system based on a fuzzy theory.
Background
Fuzzy theory refers to the theory that uses the basic concept of fuzzy sets or continuous membership functions. It can be classified into five branches of fuzzy mathematics, fuzzy system, uncertainty and information, fuzzy decision, fuzzy logic and artificial intelligence, which are not completely independent and have close relation, and Data Mining (Data Mining) is a process of extracting hidden information and knowledge from a large amount of incomplete, noisy, fuzzy and random Data, which is not known by people in advance but is potentially useful. Because the data is analyzed and processed by a certain fuzzy concept, huge data can be rapidly collected and processed, so that the pressure of hardware equipment is reduced, and the searching efficiency is improved.
The existing big data information generally adopts a single algorithm or always inputs a man-made algorithm to search each time, great difficulty is generated in the whole searching effect and the future searching, the efficiency is low, and the data processing quantity has a certain difference.
Disclosure of Invention
The big data information mining system based on the fuzzy theory provided by the invention solves the problem of low search speed.
In order to achieve the purpose, the invention adopts the following technical scheme:
the big data information mining system based on the fuzzy theory comprises a plurality of computer terminals and a cloud processing system, wherein the computer terminals are connected with the cloud processing system in a wired or wireless mode.
Preferably, the cloud processing system comprises a coordination processor, and the coordination processor is connected with an instruction module and a receiving module.
Preferably, the instruction module comprises an instruction processor connected with the coordination processor, the instruction processor is connected with an instruction database, a selection unit and an assignment unit, the selection unit is connected with the instruction database, and the assignment unit is connected with the terminal computer.
Preferably, the receiving module comprises a receiving processor connected with the coordination processor, the receiving processor is connected with a data collecting unit, the data collecting unit is connected with the terminal computer, the data collecting unit is connected with a screening unit, the screening unit is connected with a classifying unit, the classifying unit is connected with a packing unit, and the packing unit is connected with a collecting unit connected with the receiving processor.
Preferably, the receiving processor is connected with a learning module, the learning module is connected with a learning database, and the learning database is connected with the data collecting module.
Preferably, the terminal computers are collective users or individual users.
The big data information mining process based on the fuzzy theory comprises the following steps:
s1: inputting a search instruction, processing the selection or forming a set instruction by the cloud processing system, and then searching the terminal computer;
s2: the novelty searched in the step S1 is subjected to data collection by the cloud processing system, and the collected data is subjected to data classification;
s3: and after the data in the step S2 are classified, data are packaged through the cloud processing system, and then the data are packaged and output.
Preferably, in step S3, after the data is packaged, the data is copied and sorted for storage.
The invention has the beneficial effects that:
1: when the excavation of carrying out data is sought to be handled, can carry out the coordination processing at a plurality of terminals simultaneously, utilize fuzzy theory simultaneously, can be quick search for and assemble at numerous computer terminal, carry out certain preliminary treatment to data simultaneously, when convenient follow-up output, the accounting of the inspection of data reduces the requirement that data separately conveys whole hardware simultaneously, guarantees the steady operation of whole device then, guarantees the transmission capacity of data simultaneously.
2: through the processing of each plurality of system units, certain learning can be carried out on the mining and processing of the data, the learning data are stored, the collection and mining of the data in the later period are facilitated, the integral searching efficiency is increased, and the data processing capacity is improved.
Drawings
FIG. 1 is a schematic diagram of a big data information mining system based on fuzzy theory according to the present invention;
fig. 2 is a schematic diagram of a cloud processing system of a big data information mining system based on a fuzzy theory according to the present invention;
FIG. 3 is a schematic diagram of a mining process of a big data information mining system based on fuzzy theory according to the present invention;
Detailed Description
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, and not all of the embodiments.
Big data information mining system based on fuzzy theory, including a plurality of computer terminals and high in the clouds processing system, computer terminal and high in the clouds processing system are through wired or wireless connection, and wherein computer terminal is a plurality of user terminal, carries out solitary calculation design, and the data processing of each item that the cooperation far-end processing system goes on.
The cloud processing system comprises a coordination processor, the coordination processor is connected with an instruction module and a receiving module, instruction data are transmitted to the coordination processor by the computer terminal, and the coordination processor carries out commands on the instruction module and the receiving module to coordinate to work.
The instruction module comprises an instruction processor connected with the coordination processor, the instruction processor is connected with an instruction database, a selecting unit and an assigning unit, the selecting unit is connected with the instruction database, the assigning unit is connected with the terminal computer, signals processed by the coordination processor are assigned to the instruction processor, the instruction processor firstly searches for needed instructions in the instruction database through the selecting unit, then the needed instructions enter the assigning unit after being processed by the instruction processor, the assigning unit assigns the instructions to other terminal computers, and fuzzy searching and searching are carried out on the computers.
The receiving module comprises a receiving processor connected with the coordinating processor, the receiving processor is connected with a data collecting unit, the data collecting unit is connected with a terminal computer, the data collecting unit is connected with a screening unit, the screening unit is connected with a classifying unit, the classifying unit is connected with a packing unit, the packing unit is connected with a collecting unit connected with the receiving processor, after the coordinating processor gives an instruction signal for instruction processing, the working signal is synchronously given to the receiving processor, at the moment, the data collecting unit starts working, the data information collected by the instruction set given by the distributing module is collected, then the preliminary screening is carried out by the screening unit, the redundant repeated information is deleted, the later data processing amount is reduced, then the data is classified and packed by the classifying unit and the packing unit, and then the packed data is transmitted to the receiving processor for processing by the collecting unit, and feeding back the data to the coordination processor, and outputting the data to a terminal computer which sends the instruction to finish the mining processing work of the specified big data.
The receiving processor is connected with a learning module, the learning module is connected with a learning database, the learning database is connected with a data collecting module, after the receiving processor transmits data to the coordination processor, the data searched in the data are transmitted to the learning module, the learning module compresses and simplifies the data of the packaging set, and then the data are stored in the learning database.
The terminal computers are collective users or individual users.
The big data information mining process based on the fuzzy theory comprises the following steps:
s1: inputting a search instruction, processing the selection or forming a set instruction by the cloud processing system, and then searching the terminal computer;
s2: the novelty searched in the step S1 is subjected to data collection by the cloud processing system, and the collected data is subjected to data classification;
s3: and after the data in the step S2 are classified, data are packaged through the cloud processing system, and then the data are packaged and output.
In step S3, after the data is packaged, the data is copied and sorted for storage.
The working principle is as follows:
after one computer inputs data, the required fuzzy data is transmitted to a coordination processor through wired or wireless transmission, at the moment, the coordination processor processes the data, the processed signal is assigned to an instruction processor, the instruction processor firstly searches for the required instruction in an instruction data database through a selection unit, then enters an assignment unit through the processing of the instruction processor, the assignment unit assigns and transmits the instruction to other terminal computers, fuzzy searching and searching are carried out on the computers, after the coordination processor gives the instruction signal of the instruction processing, the work signal of a receiving processor is synchronously given, at the moment, a data collection unit starts working, collects the data information collected by an instruction set given by an assignment module, then the data information is preliminarily screened through a screening unit, redundant repeated information is deleted, and the later-stage data processing amount is reduced, the data are classified and packed through the classification unit and the packing unit, then the packed data are transmitted to the receiving processor through the collection unit to be processed, the data are fed back to the coordination processor and output to a terminal computer sent by an instruction, the specified mining processing work of big data is completed, after the receiving processor transmits the data to the coordination processor, the searched data are transmitted to the learning module, the learning module compresses and simplifies the packed and collected data and stores the data in the learning database, when the data are used in the later period, a certain amount of data can be directly called in the learning use database, the working pressure of the whole system is reduced, and meanwhile, when other computers search and mine, repeated operation is carried out, and the whole system is ensured to be carried out quickly.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be able to cover the technical scope of the present invention and the equivalent alternatives or modifications according to the technical solution and the inventive concept of the present invention within the technical scope of the present invention.
Claims (8)
1. Big data information mining system based on fuzzy theory, including a plurality of computer terminals and high in the clouds processing system, its characterized in that, computer terminal and high in the clouds processing system are through wired or wireless connection.
2. The fuzzy theory-based big data information mining system according to claim 1, wherein the cloud processing system comprises a coordination processor, and the coordination processor is connected with an instruction module and a receiving module.
3. The fuzzy theory-based big data information mining system according to claim 2, wherein the instruction module comprises an instruction processor connected with the coordination processor, the instruction processor is connected with an instruction database, a selecting unit and an assigning unit, the selecting unit is connected with the instruction database, and the assigning unit is connected with the terminal computer.
4. The fuzzy theory-based big data information mining system according to claim 2, wherein the receiving module comprises a receiving processor connected with the coordination processor, the receiving processor is connected with a data collecting unit, the data collecting unit is connected with the terminal computer, the data collecting unit is connected with a screening unit, the screening unit is connected with a classifying unit, the classifying unit is connected with a packing unit, and the packing unit is connected with a collecting unit connected with the receiving processor.
5. The fuzzy theory based big data information mining system according to claim 4, wherein the receiving processor is connected with a learning module, the learning module is connected with a learning database, and the learning database is connected with the data collecting module.
6. The fuzzy theory based big data information mining system according to claim 1, wherein the terminal computers are collective users or individual users.
7. The big data information mining process based on the fuzzy theory is characterized by comprising the following steps of:
s1: inputting a search instruction, processing the selection or forming a set instruction by the cloud processing system, and then searching the terminal computer;
s2: the novelty searched in the step S1 is subjected to data collection by the cloud processing system, and the collected data is subjected to data classification;
s3: and after the data in the step S2 are classified, data are packaged through the cloud processing system, and then the data are packaged and output.
8. The fuzzy theory-based big data information mining system according to claim 7, wherein in step S3, after the data is packed, the data is copied and classified for storage.
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Citations (6)
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| US20110191277A1 (en) * | 2008-06-16 | 2011-08-04 | Agundez Dominguez Jose Luis | Automatic data mining process control |
| CN104778266A (en) * | 2015-04-22 | 2015-07-15 | 无锡天脉聚源传媒科技有限公司 | Multi-data source searching method and device |
| CN107526762A (en) * | 2017-02-28 | 2017-12-29 | 天津转知汇网络技术有限公司 | Service end, multi-data source searching method and system |
| CN108989340A (en) * | 2018-08-21 | 2018-12-11 | 新开普电子股份有限公司 | A kind of implementation method directly docked with third party system |
| CN111428106A (en) * | 2020-03-18 | 2020-07-17 | 安徽格雷皖创信息科技有限公司 | Big data-based information collection and analysis system |
| US20200278964A1 (en) * | 2019-03-01 | 2020-09-03 | Palantir Technologies Inc. | Fuzzy searching and applications therefor |
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2020
- 2020-09-27 CN CN202011035118.XA patent/CN112182066A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110191277A1 (en) * | 2008-06-16 | 2011-08-04 | Agundez Dominguez Jose Luis | Automatic data mining process control |
| CN104778266A (en) * | 2015-04-22 | 2015-07-15 | 无锡天脉聚源传媒科技有限公司 | Multi-data source searching method and device |
| CN107526762A (en) * | 2017-02-28 | 2017-12-29 | 天津转知汇网络技术有限公司 | Service end, multi-data source searching method and system |
| CN108989340A (en) * | 2018-08-21 | 2018-12-11 | 新开普电子股份有限公司 | A kind of implementation method directly docked with third party system |
| US20200278964A1 (en) * | 2019-03-01 | 2020-09-03 | Palantir Technologies Inc. | Fuzzy searching and applications therefor |
| CN111428106A (en) * | 2020-03-18 | 2020-07-17 | 安徽格雷皖创信息科技有限公司 | Big data-based information collection and analysis system |
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