WO2017128438A1 - Procédé et système d'application de mégadonnées - Google Patents

Procédé et système d'application de mégadonnées Download PDF

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Publication number
WO2017128438A1
WO2017128438A1 PCT/CN2016/073010 CN2016073010W WO2017128438A1 WO 2017128438 A1 WO2017128438 A1 WO 2017128438A1 CN 2016073010 W CN2016073010 W CN 2016073010W WO 2017128438 A1 WO2017128438 A1 WO 2017128438A1
Authority
WO
WIPO (PCT)
Prior art keywords
big data
keywords
present
same type
keyword
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2016/073010
Other languages
English (en)
Chinese (zh)
Inventor
马岩
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Boxinnuoda Economic Relations and Trade Consultants Co Ltd
Original Assignee
Shenzhen Boxinnuoda Economic Relations and Trade Consultants Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shenzhen Boxinnuoda Economic Relations and Trade Consultants Co Ltd filed Critical Shenzhen Boxinnuoda Economic Relations and Trade Consultants Co Ltd
Priority to CN201680000284.1A priority Critical patent/CN105706088A/zh
Priority to PCT/CN2016/073010 priority patent/WO2017128438A1/fr
Publication of WO2017128438A1 publication Critical patent/WO2017128438A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/35—Clustering; Classification

Definitions

  • the present invention relates to the field of communication and big data, and in particular, to a method and system for applying big data.
  • a method for applying big data is provided, which solves the shortcomings of the prior art that cannot combine a plurality of big data.
  • a method of applying big data comprising the steps of:
  • 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 further includes:
  • the plurality of big data are used separately.
  • the method further includes:
  • an application system for big data comprising:
  • 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.
  • 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.
  • 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.
  • 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.
  • FIG. 1 is a flowchart of a method for applying big data according to the present invention
  • FIG. 2 is a structural diagram of an application system for big data provided by the present invention.
  • 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.
  • 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.
  • 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.
  • the foregoing method may further include:
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

La présente invention concerne un procédé et un système d'application de mégadonnées. Le procédé comprend les étapes consistant : à acquérir divers types de mégadonnées ; à extraire des mots clés issus des divers types de mégadonnées ; et si les mots clés sont du même type, à utiliser ensemble les divers types de mégadonnées. La solution technique de la présente invention présente l'avantage d'utiliser ensemble divers types de mégadonnées.
PCT/CN2016/073010 2016-01-31 2016-01-31 Procédé et système d'application de mégadonnées Ceased WO2017128438A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201680000284.1A CN105706088A (zh) 2016-01-31 2016-01-31 大数据的应用方法及系统
PCT/CN2016/073010 WO2017128438A1 (fr) 2016-01-31 2016-01-31 Procédé et système d'application de mégadonnées

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2016/073010 WO2017128438A1 (fr) 2016-01-31 2016-01-31 Procédé et système d'application de mégadonnées

Publications (1)

Publication Number Publication Date
WO2017128438A1 true WO2017128438A1 (fr) 2017-08-03

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2016/073010 Ceased WO2017128438A1 (fr) 2016-01-31 2016-01-31 Procédé et système d'application de mégadonnées

Country Status (2)

Country Link
CN (1) CN105706088A (fr)
WO (1) WO2017128438A1 (fr)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106897443A (zh) * 2017-03-01 2017-06-27 深圳市博信诺达经贸咨询有限公司 大数据的划分方法及系统

Citations (4)

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WO2007059272A1 (fr) * 2005-11-15 2007-05-24 Microsoft Corporation Paradigme de classement d'informations
CN104572645A (zh) * 2013-10-11 2015-04-29 高德软件有限公司 兴趣点数据关联方法及装置
CN104679902A (zh) * 2015-03-20 2015-06-03 湘潭大学 一种结合跨媒体融合的信息摘要提取方法
CN105045914A (zh) * 2015-08-18 2015-11-11 瑞达昇科技(大连)有限公司 信息归纳分析方法及装置

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US7395255B2 (en) * 2002-09-13 2008-07-01 General Motors Corporation Data management system having a common database infrastructure
CN103631963B (zh) * 2013-12-18 2017-10-17 北京博雅立方科技有限公司 一种基于大数据的关键词优化处理方法及装置
CN104699851A (zh) * 2015-04-08 2015-06-10 上海理想信息产业（集团）有限公司 一种大数据环境下业务标签的扩展方法
CN104933296A (zh) * 2015-05-28 2015-09-23 汤海京 一种基于多维数据融合的大数据处理方法和设备
CN104965893A (zh) * 2015-06-18 2015-10-07 山东师范大学 一种大数据广告投放方法
CN105005604A (zh) * 2015-07-06 2015-10-28 苏州金立方通讯科技有限公司 一种大数据系统
CN105279392B (zh) * 2015-09-28 2018-07-24 深圳华大基因科技服务有限公司 一种基于云平台的大数据分析装置
CN105224955A (zh) * 2015-10-16 2016-01-06 武汉邮电科学研究院 基于微博大数据获取网络服务状态的方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2007059272A1 (fr) * 2005-11-15 2007-05-24 Microsoft Corporation Paradigme de classement d'informations
CN104572645A (zh) * 2013-10-11 2015-04-29 高德软件有限公司 兴趣点数据关联方法及装置
CN104679902A (zh) * 2015-03-20 2015-06-03 湘潭大学 一种结合跨媒体融合的信息摘要提取方法
CN105045914A (zh) * 2015-08-18 2015-11-11 瑞达昇科技(大连)有限公司 信息归纳分析方法及装置

Also Published As

Publication number Publication date
CN105706088A (zh) 2016-06-22

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