deletions | additions       diff --git a/For_the_learning_resources_management__.tex b/For_the_learning_resources_management__.tex  index ef79311..1d7ef6d 100644  --- a/For_the_learning_resources_management__.tex  +++ b/For_the_learning_resources_management__.tex 
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For the learning resources management task it is necessary to find subset of the learning resources within set of the learning resources available in the repository. This subset should fulfill the learner needs and preferences. It is also necessary to organize the learning process on this set of learning resources.  Earlier in In their previous works  \cite{Anikin_VSTU2014_2,Anikin_VSTU2014_1,Anikin_KBSE2014} the  authors proposed the an  ontology-based concept of new learning content creation in open learning network on the base of learning resources retrieval and integration in personal learning collections. The ontological model for knowledge representation personal learning collection  was developed including ontologies defined as a set  of the  learning course domain, learning resource, resources retrieved according to the learner profile,  learner's profile current and outcome competencies  and other  personal preferences, and set of relations between the resources which define the  learning collection. The last one includes sequence to achieve  the set learning objectives. The process  of semantic rules for creating learning content management was presented as a control system (Fig. \ref{fig:management}), where control object is  the personal learning collection. The new two-stage method collection, controller for the inner circuit is the personal collection builder,  for electronic the outer circuit - the learner profile editor, the system output is the set of  learning resourcesretrieval  and integration into relations between them, the measured output for the inner circuit is the  personallearning  collection was developed based on ontology reasoning rules.   To implement quality measures, for  the proposed knowledge-based approach that realizes outer circuit - measured current and intentional competencies of the learner. So the feedback loops ensure the quality of the personal collection and conformity with the variable learner properties.  So the personal collection is a result The ontological model for knowledge representation was developed including ontologies  ofthe learning resources retrieval and integration that can be used in the  learning management. This is a set of the course domain,  learning resources retrieved according to the learner profile, resource,  learner's current and outcome competencies profile  andother requirements. It also includes relations between the resources that define the order of using the resources in learning to achieve the intentional competencies.   So the controlled system (Fig. \ref{fig:management}) is the  personal learning collection, controller for the inner circuit is the personal collection builder, for the outer circuit - the learner profile editor, the system output is collection. The last one includes  the set of learning resources and relations, the measured output semantic rules  for the inner circuit is creating  the personal collection quality measures, learning collection. The new two-stage method  for the outer circuit - measured current electronic learning resources retrieval  and intentional competencies of the learner. So the feedback loops ensure the quality of the integration into  personal learning  collection and conformity with the variable learner properties. was developed based on ontology reasoning rules.   To implement the proposed knowledge-based approach that realizes