IMPLEMENTATION AND RESEARCH OF INTELLIGENT INFORMATION RETRIEVAL AND DATA ANALYSIS IN WEB APPLICATIONS
- Подробности
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- Опубликовано: 12.02.2023 18:11
- Автор: Administrator
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Volume 13 (1), February 2023, Pages 65-73
Nijat Babayev
PhD student on Systematic analysis, management and information processing specialization, Azerbaijan State Oil and Industry University. Email id: Этот адрес электронной почты защищён от спам-ботов. У вас должен быть включен JavaScript для просмотра. https://orcid.org/0000-0001-5302-4338
ABSTRACT
The main stages of Web-Mining were described, the main difference between information extraction and information retrieval was highlighted in the article. The contents of Web Content Mining (extraction of Web content), Web Structure Mining (extraction of Web structures), and Web Usage Mining (analysis of the use of Web resources) have been clarified separately.
In the section entitled “Information systems for Data Mining and processes in Web Applications”, it was shown that when using Web Mining, developers face several types of challenges.
Also, the main approaches to conducting intelligent search of information and data analysis in web applications were discussed in the article. The components of the Data Mining model and the stages of its application was considered. As a practical example of the implementation of a software product for research, Russian development - the program PolyAnalyst was considered.
It was also noted that the professional version of the system - PolyAnalyst Pro allows us to analyze various data formats and optimize business processes. The system performs a full range of data analysis tasks: loading, combining, cleaning and transforming data, deep text analysis, extracting information, visualizing results and creating reports.
In the conclusion part it was noted that to improve the efficiency of work in real time, the creation of new software tools using Web Mining can bring maximum benefits. Building such intelligent analyzers can help analyze log files efficiently.
Keywords: Web Mining, Data Mining, Web applications, information retrieval, Web resources.