АНАЛИЗ МЕТОДОВ КЛАССИФИКАЦИИ ИНФОРМАЦИИ В ИНТЕРНЕТЕ ПРИ РЕШЕНИИ ЗАДАЧ ИНФОРМАЦИОННОГО ПОИСКА
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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

THE ANALYSIS OF METHODS OF INFORMATION QUALIFICATION IN INTERNET DURING SOLVING PROBLEMS OF INFORMATION SEARCH

Men Q. 

UDC 025.4
DOI:

  • Abstract
  • List of references
  • About authors

Due to the fact that the Internet stores a large amount of information must be used effective methods of search. The characteristics inherent in job search, are the completeness, reliability and high speed. These characteristics can be achieved with the use of appropriate methods of classification. The article considers several approaches. The cluster method is based on partitioning elements of the set into groups. The distance between the elements is set to metric. Linguistic analysis based on the ability to extract information from the text. The scheme of linguistic processing. Statistical approaches proceed from the specific patterns frequency of the meeting words. Symptom analysis is the study of the morphemic, morphological and syntactic features of words and sentences in the text. Semantic analysis is the analysis of the text concerning the meaning of the words inside it. The combined approach involves the use of several of the above approaches in tandem, series, or parallel, to increase the accuracy of the analysis. Depending on the emerging challenges, will be useful for the appropriate method of classification.

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Men Qingan

Voronezh Institute of High Technologies

Voronezh, Russian Federation

Keywords: information search, internet, statistics, classification, semantics, sign, metric

For citation: Men Q. THE ANALYSIS OF METHODS OF INFORMATION QUALIFICATION IN INTERNET DURING SOLVING PROBLEMS OF INFORMATION SEARCH. Modeling, Optimization and Information Technology. 2016;4(2). URL: https://moit.vivt.ru/wp-content/uploads/2016/06/MenCinan_2_16_1.pdf DOI: (In Russ).

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Published 30.06.2016