WO2017117781A1 - Procédé et système de classification d'informations de réseau - Google Patents

Procédé et système de classification d'informations de réseau Download PDF

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Publication number
WO2017117781A1
WO2017117781A1 PCT/CN2016/070405 CN2016070405W WO2017117781A1 WO 2017117781 A1 WO2017117781 A1 WO 2017117781A1 CN 2016070405 W CN2016070405 W CN 2016070405W WO 2017117781 A1 WO2017117781 A1 WO 2017117781A1
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WO
WIPO (PCT)
Prior art keywords
network information
category
word segmentation
segmentation processing
present
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/CN2016/070405
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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.)
Individual
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Individual
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Filing date
Publication date
Application filed by Individual filed Critical Individual
Priority to CN201680000012.1A priority Critical patent/CN105723367A/zh
Priority to PCT/CN2016/070405 priority patent/WO2017117781A1/fr
Publication of WO2017117781A1 publication Critical patent/WO2017117781A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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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
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/205—Parsing
    • G06F40/216—Parsing using statistical methods
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/279—Recognition of textual entities
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/279—Recognition of textual entities
    • G06F40/284—Lexical analysis, e.g. tokenisation or collocates

Definitions

  • the present invention relates to the field of the Internet, and in particular, to a method and system for classifying network information.
  • the network consists of nodes and connections, representing many objects and their interconnections.
  • a network is a kind of graph that is generally considered to be a weighted graph.
  • the network has a specific physical meaning, that is, the network is abstracted from some practical problem of the same type.
  • the network In the field of computers, the network is a virtual platform for information transmission, reception, and sharing. Through it, the information of various points, faces, and bodies is linked together to realize the sharing of these resources.
  • the network is the most important invention in the history of human development. Improve the development of science and technology and human society.
  • Network information is massive, so how to classify network information becomes a key technology in network search. There are many ways to classify network information at present, but the classification is mostly inaccurate.
  • the application provides a method for classifying network information. It solves the shortcomings of inaccurate classification of network information in the prior art technical solutions.
  • a method for classifying network information comprising the following steps:
  • the category of the most vocabulary is used as the first category of the network information.
  • the method further includes:
  • the method further includes:
  • the network information is re-classified.
  • a classification system for network information comprising:
  • An obtaining unit configured to obtain network information that needs to be classified
  • a word segmentation unit for performing word segmentation processing on the network information, and performing quantitative statistics on the same vocabulary obtained by the word segmentation process
  • system further includes:
  • a learning unit configured to input the network information into a second class corresponding to the first class of the learning vector machine to output the network information, and if the second category is the same as the first category, determining that the category of the network information is the first category.
  • system further includes:
  • the reprocessing unit is configured to re-classify the network information if the second category is different from the first category.
  • the technical solution provided by the present invention performs word segmentation processing on network information, and captures keywords of network information, and classifies according to the number of times of the keyword, so that it has the advantage of accurate classification.
  • FIG. 1 is a flowchart of a method for classifying network information according to a first preferred embodiment of the present invention
  • FIG. 2 is a structural diagram of a network information classification system according to a second preferred embodiment of the present invention.
  • FIG. 1 is a schematic diagram of a network information classification method according to a first preferred embodiment of the present invention. The method is as shown in FIG.
  • Step S101 Obtain network information that needs to be classified
  • Step S102 performing word segmentation processing on the network information, and performing quantity statistics on the same vocabulary obtained by the word segmentation processing;
  • the above-mentioned word segmentation processing algorithm may use an existing word segmentation processing algorithm, such as a Baidu word segmentation processing algorithm.
  • Step S103 The category of the most vocabulary is used as the first category of the network information.
  • the technical solution provided by the present invention performs word segmentation processing on network information, and captures keywords of network information, and classifies according to the number of times of the keyword, so that it has the advantage of accurate classification.
  • the foregoing method may further include:
  • the foregoing method may further include:
  • the network information is re-classified.
  • FIG. 2 is a network information classification system according to a second preferred embodiment of the present invention.
  • the system as shown in FIG. 2, includes:
  • the obtaining unit 201 is configured to acquire network information that needs to be classified;
  • the word segmentation unit 202 is configured to perform word segmentation processing on the network information, and perform quantity statistics on the same vocabulary obtained by the word segmentation process;
  • the above-mentioned word segmentation processing algorithm may use an existing word segmentation processing algorithm, such as a Baidu word segmentation processing algorithm.
  • the category unit 203 is configured to use the category of the most vocabulary as the first category of the network information.
  • the technical solution provided by the present invention performs word segmentation processing on network information, and captures keywords of network information, and classifies according to the number of times of the keyword, so that it has the advantage of accurate classification.
  • the above system may further include:
  • the learning unit 204 is configured to input the network information into the second class corresponding to the first class to output the network information, and if the second category is the same as the first category, determine that the network information category is One category.
  • the above system may further include:
  • the reprocessing unit 205 is configured to re-classify the network information if the second category is different from the first category.
  • the program may be stored in a computer readable storage medium, and the storage medium may include: Flash drive, read-only memory (English: Read-Only Memory, referred to as: ROM), random accessor (English: Random Access Memory, referred to as: RAM), disk or CD.
  • ROM Read-Only Memory
  • RAM Random Access Memory

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Computational Linguistics (AREA)
  • General Health & Medical Sciences (AREA)
  • Databases & Information Systems (AREA)
  • Probability & Statistics with Applications (AREA)
  • Data Mining & Analysis (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

L'invention concerne un procédé et un système de classification d'informations de réseau, le procédé comprenant les étapes suivantes : acquisition d'informations de réseau nécessitant une classification (101) ; exécution d'un traitement de segmentation de mots sur les informations de réseau et comptage des quantités de mots identiques obtenus au moyen du traitement de segmentation de mots (102) ; adoption du type du mot présent dans la quantité la plus importante comme étant un premier type d'informations de réseau (103). Le procédé et le système de classification selon l'invention présentent l'avantage d'une classification précise.
PCT/CN2016/070405 2016-01-07 2016-01-07 Procédé et système de classification d'informations de réseau Ceased WO2017117781A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201680000012.1A CN105723367A (zh) 2016-01-07 2016-01-07 网络信息的分类方法及系统
PCT/CN2016/070405 WO2017117781A1 (fr) 2016-01-07 2016-01-07 Procédé et système de classification d'informations de réseau

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2016/070405 WO2017117781A1 (fr) 2016-01-07 2016-01-07 Procédé et système de classification d'informations de réseau

Publications (1)

Publication Number Publication Date
WO2017117781A1 true WO2017117781A1 (fr) 2017-07-13

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Application Number Title Priority Date Filing Date
PCT/CN2016/070405 Ceased WO2017117781A1 (fr) 2016-01-07 2016-01-07 Procédé et système de classification d'informations de réseau

Country Status (2)

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CN (1) CN105723367A (fr)
WO (1) WO2017117781A1 (fr)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106777401A (zh) * 2017-03-10 2017-05-31 北京搜狐新媒体信息技术有限公司 信息分类方法及装置

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050246333A1 (en) * 2004-04-30 2005-11-03 Jiang-Liang Hou Method and apparatus for classifying documents
CN101794311A (zh) * 2010-03-05 2010-08-04 南京邮电大学 基于模糊数据挖掘的中文网页自动分类方法
CN102819595A (zh) * 2012-08-10 2012-12-12 北京星网锐捷网络技术有限公司 网页分类方法、装置及网络设备
CN103049568A (zh) * 2012-12-31 2013-04-17 武汉传神信息技术有限公司 对海量文档库的文档分类的方法
CN104750833A (zh) * 2015-04-03 2015-07-01 浪潮集团有限公司 一种文本分类方法及装置
CN104750754A (zh) * 2013-12-31 2015-07-01 北龙中网（北京）科技有限责任公司 网站所属行业的分类方法和服务器

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102222072A (zh) * 2010-04-19 2011-10-19 腾讯科技（深圳）有限公司 一种信息分类的方法和装置

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050246333A1 (en) * 2004-04-30 2005-11-03 Jiang-Liang Hou Method and apparatus for classifying documents
CN101794311A (zh) * 2010-03-05 2010-08-04 南京邮电大学 基于模糊数据挖掘的中文网页自动分类方法
CN102819595A (zh) * 2012-08-10 2012-12-12 北京星网锐捷网络技术有限公司 网页分类方法、装置及网络设备
CN103049568A (zh) * 2012-12-31 2013-04-17 武汉传神信息技术有限公司 对海量文档库的文档分类的方法
CN104750754A (zh) * 2013-12-31 2015-07-01 北龙中网（北京）科技有限责任公司 网站所属行业的分类方法和服务器
CN104750833A (zh) * 2015-04-03 2015-07-01 浪潮集团有限公司 一种文本分类方法及装置

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