WO2017128438A1

WO2017128438A1 - Method and system for application of big data

Info

Publication number: WO2017128438A1
Application number: PCT/CN2016/073010
Authority: WO
Inventors: 马岩
Original assignee: 深圳市博信诺达经贸咨询有限公司
Priority date: 2016-01-31
Filing date: 2016-01-31
Publication date: 2017-08-03
Also published as: CN105706088A

Abstract

Provided in the present invention are a method and a system for the application of big data. The method comprises the following steps: acquiring various kinds of big data; extracting keywords from the various kinds of big data; and if the keywords are of the same type, using the various kinds of big data together. The technical solution provided in the present invention has the advantage of using various kinds of big data together.

Description

Big data application method and system

Technical field

The present invention relates to the field of communication and big data, and in particular, to a method and system for applying big data.

Background technique

The future development trend and prospects of big data and cloud computing are extremely broad. The future of the Internet is the world of big data and cloud computing, big data and cloud computing will become every IT The skills that personnel must have. In big data, the application of existing big data is generally single, and it is impossible to combine multiple big data.

technical problem

A method for applying big data is provided, which solves the shortcomings of the prior art that cannot combine a plurality of big data.

Technical solution

In one aspect, a method of applying big data is provided, the method comprising the steps of:

Get a variety of big data;

Extracting keywords in a variety of big data. If the keyword belongs to the same type of keyword, the multiple big data is applied together.

Optionally, the method further includes:

If the keyword does not belong to the same type of keyword, the plurality of big data are used separately.

Optionally, the method further includes:

Get the results of the use, adjust the type of multiple big data according to the structure.

In a second aspect, an application system for big data is provided, the system comprising:

An acquisition unit for acquiring a plurality of big data;

The extracting unit is configured to extract keywords in a plurality of big data, and if the keywords belong to the same type of keywords, the plurality of big data are applied together.

Optionally, the system further includes:

The unit is used for keywords such as keywords that do not belong to the same type, and the plurality of big data are used separately.

Optionally, the system further includes:

The adjustment unit is used to obtain the result of use, and adjust various types of big data according to the structure.

Beneficial effect

The technical solution provided by the specific embodiment of the present invention acquires a plurality of big data and extracts keywords in a plurality of big data. If the keyword belongs to the same type of keyword, the plurality of big data are applied together, so It has the advantage of merging multiple big data together.

DRAWINGS

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below. Obviously, the drawings in the following description are only It is a certain embodiment of the present invention, and other drawings can be obtained from those skilled in the art without any creative work.

1 is a flowchart of a method for applying big data according to the present invention;

2 is a structural diagram of an application system for big data provided by the present invention.

Embodiments of the invention

The technical solutions in the embodiments of the present invention are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present invention. It is obvious that the described embodiments are only a part of the embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts are within the scope of the present invention.

Referring to FIG. 1 , FIG. 1 is a flowchart of a method for applying big data according to a first preferred embodiment of the present invention. The method is implemented by an intelligent terminal. The method is as shown in FIG. 1 and includes the following steps:

Step S101: Acquire a plurality of big data;

Step S102: Extract keywords in a plurality of big data, and if the keywords belong to the same type of keywords, apply the plurality of big data together.

Optionally, after the step S102, the foregoing method may further include:

Step S103: If the keywords do not belong to the same type of keywords, the plurality of big data are used separately.

Optionally, after the step S102, the foregoing method may further include:

Referring to FIG. 2, FIG. 2 is a system for applying big data according to a second preferred embodiment of the present invention. The system includes:

The obtaining unit 201 is configured to acquire a plurality of big data.

The extracting unit 202 is configured to extract keywords in the plurality of big data. If the keywords belong to the same type of keywords, the plurality of big data are applied together.

Optionally, the above system may further include:

The use unit 203 is configured to use the plurality of big data separately if the keywords do not belong to the same type of keywords.

Optionally, the above system may further include:

The adjusting unit 204 is configured to obtain a result of using, and adjust a type of the plurality of big data according to the structure.

It should be noted that, for the foregoing method embodiments or embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should know that the present invention is not subject to the described action sequence. Limitations, as certain steps may be performed in other sequences or concurrently in accordance with the present invention. In the following, those skilled in the art should also understand that the embodiments or examples described in the specification are preferred embodiments, and the actions and units involved are not necessarily required by the present invention.

In the above embodiments, the descriptions of the various embodiments are different, and the details that are not detailed in a certain embodiment can be referred to the related descriptions of other embodiments.

The steps in the method of the embodiment of the present invention may be sequentially adjusted, merged, and deleted according to actual needs.

The units in the apparatus of the embodiment of the present invention may be combined, divided, and deleted according to actual needs. Those skilled in the art can combine or combine the different embodiments described in the specification and the features of the different embodiments.

Through the description of the above embodiments, those skilled in the art can clearly understand that the present invention can be implemented in hardware, firmware implementation, or a combination thereof. When implemented in software, the functions described above may be stored in or transmitted as one or more instructions or code on a computer readable medium. Computer readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one location to another. A storage medium may be any available media that can be accessed by a computer. Taking this as an example, but not limited to: the computer readable medium may include random access memory (Random) Access Memory, RAM), Read-Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), Compact Disc Read-Only Memory, CD-ROM, or other optical disc storage, magnetic storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also. Any connection may suitably be a computer readable medium. For example, if the software is using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (Digital Subscriber Line, DSL) or wireless technology such as infrared, radio and microwave transmission from a website, server or other remote source, then coaxial cable, fiber optic cable, twisted pair, DSL or such as infrared, wireless and microwave Wireless technology is included in the fixing of the associated medium. As used in the present invention, a disk and a disc include a compact disc (CD), a laser disc, a compact disc, a digital versatile disc (DVD), a floppy disk, and a Blu-ray disc, wherein the disc is usually magnetically copied, and the disc is The laser is used to optically replicate the data. Combinations of the above should also be included within the scope of the computer readable media.

In summary, the above description is only a preferred embodiment of the technical solution of the present invention, and is not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and scope of the present invention are intended to be included within the scope of the present invention.

Claims

A method for applying big data, characterized in that the method comprises the following steps:

Get a variety of big data;

Extracting keywords in a variety of big data. If the keyword belongs to the same type of keyword, the multiple big data is applied together.
The method of claim 1 further comprising:

If the keyword does not belong to the same type of keyword, the plurality of big data are used separately.
The method of claim 1 further comprising:

Get the results of the use, adjust the type of multiple big data according to the structure.
An application system for big data, characterized in that the system comprises:

An acquisition unit for acquiring a plurality of big data;

The extracting unit is configured to extract keywords in a plurality of big data, and if the keywords belong to the same type of keywords, the plurality of big data are applied together.
The system of claim 4, wherein the system further comprises:

The unit is used for keywords such as keywords that do not belong to the same type, and the plurality of big data are used separately.
The system of claim 4, wherein the system further comprises:

The adjustment unit is used to obtain the result of use, and adjust various types of big data according to the structure.