Analysis of the developed quantitative method for automatic attribution of scientific and technical text content written in Ukrainian

Design of a recommendation system based on collaborative filtering and machine learning considering personal needs of the user

Main components of ontology concept within implementation context of knowledge bases in accounting are considered in this paper. Examples of accounting knowledge fragments are given, and possibilities of instrumental support for knowledge-oriented accounting systems are analyze as well.

The paper discusses the issues of ensuring a performance of the corporate website that, therefore, facilitates the fulfillment of the strategic development goals of the enterprise. The efficiency of the audit for improving the online business management mechanisms is justified. The organizational and methodological peculiarities of the performance audit of the corporate website are reviewed. The usefulness of quantitative indicators received via analytical online-services is determined, and their applicability in the performance audit of the corporate website is confirmed. A special attention is drawn to the possibility of transforming quantitative indicators into the data necessary for the decision-making. The article suggests the use of the key performance indicators of the corporate website calculated on the basis of the numerical value of the quantitative indicators. Based on the clustering method, the ratio between the key indicators of the corporate website performance and the development goals of the enterprise is defined thereby making the objectives of the enterprise tangible and understandable for its management staff. It is claimed that the audit results encourage achieving the desired enterprise performance rates as well as fulfilling its strategic development goals.

The fuzzy rules for changing of complexity level at adaptive testing were designed. Using of fussy rules for learning objects optimal selection for generation of individual learning path is proposed. Since the limits of student's knowledge assessment is difficult to determine, it is proposed to use the fuzzy approach. There is proved that using of fuzzy approach simplifies the evaluation of student's knowledge, because fuzzy systems are better understood by students and mark for answering test questions can be also considered as fuzzy. Fuzzy models are transparent enough and understandable, therefore they are acceptable when informative interpretation is more important than simulation accuracy. Experimental results show that adaptive test with fuzzy rules is three times faster that classical test.