The main objective of the University is the promotion of successful professionals who have practical skills, can predict, model, process information, and integrate the knowledge obtained in a higher educational establishment.
When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/2942

Skidanenko, A.S.

Skydanenko, Maksym Serhiiovych

Скиданенко, Максим Сергеевич

Скиданенко, Максим Сергійович

SocioEconomic Challenges Journal (Sumy State University)

VISUAL SEARCH ENGINES AS A SEARCH TOOL IN THE LEARNING PROCESS 
Skidanenko M.S.1, aspirant 
Skidanenko A.S., student 
of Sumy State University 
1skidanenko@pohnp.sumdu.edu.ua 
 
The main objective of the University is the promotion of successful professionals who have 
practical skills, can predict, model, process information, and integrate the knowledge obtained in a 
higher educational establishment [1]. 
In the Sumy State University, one of the ways to develop the necessary skills and experience is a 
business game "Iron entrepreneur", based on national research university higher school of 
Economics [2]. 
Team members should have different competences (economic and engineering knowledge), as 
well as be able to find information on the Internet. 
To search for desired information online created a special search engines (Google, Yahoo, 
Yandex, etc.). These systems have their own limited resources list (index) of the documents, which 
are available for search. None of these systems can not cover all the resources, that exist on the 
Internet. To solve this problem developed metasearch systems. They do not have their own search 
databases that do not contain any indexes and searches multiple search engines using resources. Due 
to the completeness of the search in such systems is a maximum and a probability of finding the right 
information is very high [3]. 
A type of meta-search engines is a Visual search engine. Visual search engines consist of two 
areas: the query fields, where the Visual representation of data, and the issue-list of sites that are 
relevant (or irrelevant). The data in these search engines have their own particular hierarchy. The 
advantage of such systems is the availability of associative concepts, synonyms, search queries, 
which, in turn, reveal their associative ranks, and similar concepts can be more "deep" search. These 
search engines have the semantic relations between the links [4]. 
Interactive data search engines help you to search the Internet much easier and faster than through 
traditional search engines. Visual system map shows the request context keywords that are most 
closely associated with your request. Query context visualization-this is only a small fraction of the 
overall functionality of Visual maps, while its main objective-manage search queries. The system 
gives you the opportunity to refine the query until you find the page you are looking for. 
Adding a Word from a Visual map to the query and excluding unnecessary words, you can refine 
the query in a few steps. The system has a lot to do with the advanced search on information sites. 
Examples of Visual search system are: Quintura (Eng) VisualWorld (Eng), KartOO, Ujiko (Engl.) 
[5]. 
Use of metasearch is recommended for systems running queries associated with the search is very 
simple, and, presumably, it is rarely encountered in the network keyword. In this case, the search 
results will immediately give an idea of how widely the data tags (objects) found in the network. 
Another reason for resorting to metasearching is an extreme lack of time. 
However, it is not advisable to resort to metasearching means when performing complex queries. 
For best results search prescriptions should include one or two words, otherwise, the search process 
will be difficult.  
 
Literature: 
1.  Sumy State University – http://sumdu.edu.ua/ukr/ 
2.  Business game "Iron entrepreneur" – http://zhp.inc.hse.ru/ 
3.  Encyclopedia of search system – http://www.searchengines.ru  
4.  http://www.torgovec.com/article.php?articleId=189 
5.  http://www.vsepoisk.ru/2009/07/blog-post_23.html 
 
Електронні засоби та дистанційні технології для навчання протягом життя : тези доповідей  
VIII Міжнародної науково-методичної конференції, м. Суми, 15–16 листопада 2012 р. – 
Суми : Сумський державний університет, 2012. – C. 26-27. 


English

Visual search engines as a search tool in the learning process

Electronic Sumy State University Institutional Repository

VISUAL SEARCH ENGINES AS A SEARCH TOOL IN THE LEARNING PROCESS Skidanenko M.S.1, aspirant Skidanenko A.S., student of Sumy State University 1skidanenko@pohnp.sumdu.edu.ua  The main objective of the University is the promotion of successful professionals who have practical skills, can predict, model, process information, and integrate the knowledge obtained in a higher educational establishment [1]. In the Sumy State University, one of the ways to develop the necessary skills and experience is a business game "Iron entrepreneur", based on national research university higher school of Economics [2]. Team members should have different competences (economic and engineering knowledge), as well as be able to find information on the Internet. To search for desired information online created a special search engines (Google, Yahoo, Yandex, etc.). These systems have their own limited resources list (index) of the documents, which are available for search. None of these systems can not cover all the resources, that exist on the Internet. To solve this problem developed metasearch systems. They do not have their own search databases that do not contain any indexes and searches multiple search engines using resources. Due to the completeness of the search in such systems is a maximum and a probability of finding the right information is very high [3]. A type of meta-search engines is a Visual search engine. Visual search engines consist of two areas: the query fields, where the Visual representation of data, and the issue-list of sites that are relevant (or irrelevant). The data in these search engines have their own particular hierarchy. The advantage of such systems is the availability of associative concepts, synonyms, search queries, which, in turn, reveal their associative ranks, and similar concepts can be more "deep" search. These search engines have the semantic relations between the links [4]. Interactive data search engines help you to search the Internet much easier and faster than through traditional search engines. Visual system map shows the request context keywords that are most closely associated with your request. Query context visualization-this is only a small fraction of the overall functionality of Visual maps, while its main objective-manage search queries. The system gives you the opportunity to refine the query until you find the page you are looking for. Adding a Word from a Visual map to the query and excluding unnecessary words, you can refine the query in a few steps. The system has a lot to do with the advanced search on information sites. Examples of Visual search system are: Quintura (Eng) VisualWorld (Eng), KartOO, Ujiko (Engl.) [5]. Use of metasearch is recommended for systems running queries associated with the search is very simple, and, presumably, it is rarely encountered in the network keyword. In this case, the search results will immediately give an idea of how widely the data tags (objects) found in the network. Another reason for resorting to metasearching is an extreme lack of time. However, it is not advisable to resort to metasearching means when performing complex queries. For best results search prescriptions should include one or two words, otherwise, the search process will be difficult.   Literature: 1.  Sumy State University – http://sumdu.edu.ua/ukr/ 2.  Business game "Iron entrepreneur" – http://zhp.inc.hse.ru/ 3.  Encyclopedia of search system – http://www.searchengines.ru  4.  http://www.torgovec.com/article.php?articleId=189 5.  http://www.vsepoisk.ru/2009/07/blog-post_23.html  Електронні засоби та дистанційні технології для навчання протягом життя : тези доповідей  VIII Міжнародної науково-методичної конференції, м. Суми, 15–16 листопада 2012 р. – Суми : Сумський державний університет, 2012. – C. 26-27. 

https://essuir.sumdu.edu.ua/bitstream/123456789/29424/1/Skidanenko_VISUAL%20SEARCH%20ENGINES%20AS%20A%20SEARCH%20TOOL%20IN%20THE%20LEARNING%20PROCESS.pdf

Visual search engines as a search tool in the learning process

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SocioEconomic Challenges Journal (Sumy State University)

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