deletions | additions       diff --git a/For_the_learning_resources_management__.tex b/For_the_learning_resources_management__.tex  index d668955..ef79311 100644  --- a/For_the_learning_resources_management__.tex  +++ b/For_the_learning_resources_management__.tex 
...
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 \cite{Anikin_VSTU2014_2,Anikin_VSTU2014_1,Anikin_KBSE2014} authors proposed the 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 was developed including ontologies of learning course domain, learning resource, learner's profile and personal learning collection. The last one includes the set of semantic rules for creating the personal learning collection. The new two-stage method for electronic learning resources retrieval and integration into personal learning collection was developed based on ontology reasoning rules.   To implement the proposed knowledge-based approach that realizes  So the personal collection is a result of the learning resources retrieval and integration that can be used in the learning management. This is a set of the learning resources retrieved according to the learner profile, learner's current and outcome competencies and other 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 the set of learning resources and relations, the measured output for the inner circuit is the personal collection quality measures, for the 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.