Three step clustering of dynamic internet resources using document object models
The paper discusses the problem of clustering internet resources related to search engines optimization. The 
 research work was made in conditions when cluster''s structure is changing with time according to the text content of internet 
 resources dynamic components.
 The DOM of modern internet resources includes a set of dynamic components that have the ability of changing its con-tent whenever a browser loads it. In this case, it is not admissible to use classic cluster analysis without paying attention on the dynamic components. The authors investigate the situation when cluster structure changes in time according to changing 
 text content of DOM dynamic components. Changes in internet resources directly affect clusters'' structure qualitatively and 
 quantitatively. As a result, there are clusters'' drifts and diffusions. As a suggestion it is recommended to use DOM-filtration 
 in order to achieve a higher static level with a stable cardinality of the characteristic vectors. A new possibility of improve-ment of the “ownership level” dynamic indicator can be achieved after a three step clustering algorithm using DOM-filter. 
 After making the research work we''ve got a stable state cluster. A program implemented with Visual Studio 2010 was used to 
 access the content of internet resources. After loading an internet resource in a web-browser all DOM components were 
 saved in a relational data base. All clustering analysis and calculations were made using MS SQL Server 2012.
 The offered approach can be implemented to improve the search engines that use clustering methods for internet re-sources with a big number of dynamic components in its DOM.