Dynamic EMCUD for knowledge acquisition

[[abstract]]Due to the knowledge explosion, the new objects will be evolved in a dynamic environment. Hence, the knowledge can be classified into static knowledge and dynamic knowledge. Although many knowledge acquisition methodologies, based upon the Repertory Grid technique, have been proposed to systematically elicit useful rules from static grid from domain experts, they lack the ability of grid evolution to incrementally acquire the dynamic knowledge of new evolved objects. In this paper, we propose dynamic EMCUD, a new Repertory Grid-based knowledge acquisition methodology to elicit the embedded meanings of knowledge (embedded rules bearing on m objects and k object attributes), to enhance the ability of original EMCUD to iteratively integrate new evolved objects and new added attributes into the original Acquisition Table (AT) and original Attribute Ordering Table (AOT). The AOT records the relative importance of each attribute to each object in EMCUD to capture the embedded meanings with acceptable certainty factor value by relaxing or ignoring some minor attributes. In order to discover the new evolved objects, a collaborative framework including local knowledge based systems (KBSs) and a collaborative KBS is proposed to analyze the correlations of inference behaviors of embedded rules between multiple KBSs in a dynamic environment. Each KBS monitors the frequent inference behaviors of interesting embedded rules to construct a small AT increment to facilitate the acquisition of dynamic knowledge after experts confirming the new evolved objects. Moreover, the significance of knowledge may change after a period of time, a trend of all attributes to each evolved object is used to construct a new AOT increment to help experts automatically adjust the relative importance of each attribute to each object using time series analysis approach. Besides, three cases are considered to assist experts in adjusting the certainty factor values of the dynamic knowledge of the new evolved objects from the collection of inference logs in the collaborative KBS. To evaluate the performance of dynamic EMCUD in incrementally integrating new knowledge into the knowledge base, a worm detection prototype system is implemented. (c) 2006 Elsevier Ltd. All rights reserved

КВАЛИФИКАЦИОННО-ОРИЕНТИРОВАННАЯ ЭКСПЕРТНАЯ СИСТЕМА УПРАВЛЕНИЯ ОБРАЗОВАТЕЛЬНЫМ ПРОЦЕССОМ ВУЗА В СОВРЕМЕННЫХ ПРОЦЕССАХ НЕПРЕРЫВНОГО КВАЛИФИКАЦИОННОГО РАЗВИТИЯ КАДРОВ В РОССИИ

In the current situation of the formation of a national system for the independent assessment of qualifications in Russia and the search for new modern tools to correlate with professional and educational standards, a new management tool is presented that allows coordinating experts’ developing professional standards, representatives of the professional and educational communities. As such an instrument is a qualification-oriented expert system for managing the educational process of the university. Constructed on the target matrix of competencies of each specific student, the qualification-oriented expert system of the university education process management gives the necessary information on how the level of the competences corresponds to the professional standard, which enables management correction at the level of a student, academic staff, university administration. The obtained results of application of the qualification-oriented expert system make it possible to consider its prospects by obtaining and analyzing the global data set (BigData) for Russia on the status and trends of the qualification replenishment of the human resource of Russia.В современной ситуации формирования национальной системы независимой оценки квалификаций России и поиска новых современных инструментов соотнесения профессиональных и образовательных стандартов представляется новый управленческий инструмент, позволяющий скоординировать экспертов, разрабатывающих профессиональные стандарты, представителей профессионального и образовательного сообществ. В качестве такого инструмента выступает квалификационно-ориентированная экспертная система управления образовательным процессом вуза. Построенная на целевой матрице компетенций каждого конкретного студента, квалификационно-ориентированная экспертная система управления образовательным процессом вуза дает необходимую информацию о том, насколько уровень освоения компетенций студентом соответствует профессиональному стандарту, что дает возможность управленческой коррекции на уровне студента, преподавателя, вуза. Полученные результаты применения квалификационно-ориентированной экспертной системы позволяют рассматривать ее перспективы получения и анализа глобального массива данных (BigData) по России о состоянии и тенденциях квалификационного пополнения кадрового ресурса России

Dynamic EMCUD for knowledge acquisition

[[abstract]]Due to the knowledge explosion, the new objects will be evolved in a dynamic environment. Hence, the knowledge can be classified into static knowledge and dynamic knowledge. Although many knowledge acquisition methodologies, based upon the Repertory Grid technique, have been proposed to systematically elicit useful rules from static grid from domain experts, they lack the ability of grid evolution to incrementally acquire the dynamic knowledge of new evolved objects. In this paper, we propose dynamic EMCUD, a new Repertory Grid-based knowledge acquisition methodology to elicit the embedded meanings of knowledge (embedded rules bearing on m objects and k object attributes), to enhance the ability of original EMCUD to iteratively integrate new evolved objects and new added attributes into the original Acquisition Table (AT) and original Attribute Ordering Table (AOT). The AOT records the relative importance of all attribute to each object in EMCUD to capture the embedded meanings with acceptable certainty factor value by relaxing or ignoring some minor attributes. In order to discover the new evolved objects, a collaborative framework including local knowledge based systems (KBSs) and a collaborative KBS is proposed to analyze the correlations of inference behaviors of embedded rules between multiple KBSs in a dynamic environment. Each KBS monitors the frequent inference behaviors of interesting embedded rules to construct a small AT increment to facilitate the acquisition of dynamic knowledge after experts confirming the new evolved objects. Moreover, the significance of knowledge may change after a period of time, a trend of all attributes to each evolved object is used to construct a new AOT increment to help experts automatically adjust the relative importance of each attribute to each object using time series analysis approach. Besides, three cases are considered to assist experts in adjusting the certainty factor values of the dynamic knowledge of the new evolved objects from the collection of inference logs in the collaborative KBS. To evaluate the performance of dynamic EMCUD in incrementally integrating new knowledge into the knowledge base, a worm detection prototype system is implemented

Dynamic EMCUD for Knowledge Acquisition

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