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The vision of the semantic web is to give a semantic perspective to the data so that data become a real-world entity rather than a string of characters. The most important step for achieving this vision is defining and describing the relations among the available data on the web. This is the place where ontologies serve as a backbone for the semantic web. An ontology is a knowledge representation scheme that offers enriched semantic meaning of data. Various ontologies are available on the web within the same or different domains with some common information among them that create a hinder during the mapping of the data due to their heterogeneous nature. The ontology alignment is a core solution to resolve this issue; hence, it is demanded to provide a sophisticated ontology alignment approach for semantic mapping. This paper defines a universal and Smart Ontology Alignment (SOA) approach for finding relations between entities by dividing the set of attributes of an entity into 'distinctive features' and 'cancellable features'. The SOA approach is termed smart because of the smart knowledge representation scheme it is based upon. State-of-the-art ontology alignment tools do not use this effect and offer wrong relations between the entities. The proposed structure of knowledge is believed to be more natural and comprehensible, and the relations found using SOA increase the performance of the system. The proposed SOA approach is tested with respect to five benchmarks, and the results show that the performance of our approach is near to optimal. [ABSTRACT FROM AUTHOR]

The importance of prerequisites for education has recently become a promising research direction. This work proposes a statistical model for measuring dependencies in learning resources between knowledge units. Instructors are expected to present knowledge units in a semantically well-organized manner to facilitate students’ understanding of the material. The proposed model reveals how inner concepts of a knowledge unit are dependent on each other and on concepts not in the knowledge unit. To help understand the complexity of the inner concepts themselves, WordNet is included as an external knowledge base in this model. The goal is to develop a model that will enable instructors to evaluate whether or not a learning regime has hidden relationships which might hinder students’ ability to understand the material. The evaluation, employing three textbooks, shows that the proposed model succeeds in discovering hidden relationships among knowledge units in learning resources and in exposing the knowledge gaps in some knowledge units. [ABSTRACT FROM AUTHOR]

The knowledge units of gear transmission scheme digital design are established，and the motion，dynamic and structural attributes of the knowledge units are extracted. From the state space theory of mechanical motion scheme design，the motion and dynamic attributes of the knowledge units are transformed into feature vectors，so that the solution of gear transmission scheme is converted into a matrix calculation. The relationship between dynamic attributes of knowledge units and 3D parametric model is established to realize the visualization of transmission scheme. The knowledge unit database of the gear transmission scheme is established and transformed into the corresponding data structure. The solution of hybrid combination schemes of knowledge units is implemented by considering the series-parallel combination of knowledge units. The gear transmission scheme design module，which is developed by VS，is used to output the three-dimensional model of the gear transmission scheme meeting the user's requirements and the relevant details of the scheme.

The traditional user-based collaborative filtering recommendation algorithm only considers the user's score when calculating the similarity between users, but ignores the differences between different projects. Aiming at the unsatisfactory performance of traditional methods in data sparseness, a collaborative filtering recommendation algorithm based on item label information is proposed for each user to select neighbors. Firstly, based on user rating matrix to determine the initial neighbor, calculate the target users for each target neighbor; when the minimum number of nearest neighbor scoring the goal of the project or not, consider adding the development from the tag information according to the nearest neighbor; for the target item rating prediction. The experimental results show that the algorithm improves the accuracy of similarity calculation, effectively alleviates the sparsity of user rating data, and improves the accuracy of prediction. [ABSTRACT FROM AUTHOR]

The paper deals with matters related to the adjustment training of the specialist who has specified competences in order to solve the specific staffing problems of enterprises, provide scheduled staff re-training, suggest additional specializations to graduates of educational institutions, etc. Defines a structure and content of the management system elements for training and adjustment training of specialists, including a shift from activity-related competence to desirable areas of knowledge, and therefrom to the curricula and programmes.A concept of the knowledge subject is defined. It allows perceiving a specific subject area. A concept of the aspects of the certain knowledge subject is proposed, and in this case it is assumed that the knowledge subject can be represented as a finite set of aspects of the given subject of knowledge. A concept of the knowledge section is defined as a body of knowledge, reflecting some aspect of the particular subject of knowledge. Thus, the entire body of knowledge to be offered by the particular Department may be represented by a variety of specific sections of knowledge. For each section of knowledge is introduced a concept of the training level, which corresponds to the level of detail and quality of the educational material delivered. To assess the level of training it is possible to use the method of expert’s estimates.The paper suggests a scheme that allows realization of the relevant order for target training of specialists. Requirements for training specialists are represented as a competency model of the specialist; an implemented study programme is characterized by the competences, obtained as the learning outcomes.The content of knowledge, corresponding to some competence, is represented as a total of all the sections of knowledge related to the aspects generated by the competence. Then the competence can be revealed through the body of knowledge. As a result, both an order for adjustment training and a Department can be defined as a set of the knowledge sections with indication of quality levels. The concepts of general knowledge, a lack of knowledge, knowledge residue were defined when comparing the weighted knowledge content of the order and the weighted knowledge content of the Department.The paper introduces an indicator of the level of requirements, which value shows a difference of the order-required level of training for the aspect from the level of training provided by the Department. The order-unclaimed knowledge forms the graduate’s general knowledge. This allows you to adjust the amount of additional knowledge to implement the order. To do this, we introduce the concept of a connectivity factor, which takes the value in the range [0,1]. The experts specify this factor, and the more is its value, the higher is the connectivity of the order materials and the knowledge residue.The obtained results make it possible to create an optimal technique (including automated) for adjustment or target training of specialists who possess basic education. In addition, this technique allows a customer to select the most desirable basic Department to organise target training.

This paper describes a way to better navigate in an ever increasing number of standards in the field of ITS. Short overview about fundamental ITS models is presented, the principles of related knowledge system are described. Ontology approach is used, especially as domain-oriented ITS ontology, where a new hybrid method is explained.

Texts are an important way to share and transfer knowledge. In this paper we analyse the impact of a specific form of texts, so called “knowledge texts”, on the efficiency of knowledge transfer. The objective is to verify or reject several hypotheses on the relationships among the style of educational texts (standard or knowledge styles), learning outcomes (performance of the students after learning) and subjective evaluation of conformity of working with individual styles of the texts. For this purpose, we carry out experiment with a homogeneous group of the students (n = 41) divided into an experimental group and a control group. We use statistical methods to process the results of the experiments; ability of the students to solve specific tasks and their opinions on readability and understandability of the texts subject to the time spent for learning. Even if we determine statistically significant relationships between the style of texts and accuracy of the problem solving in the experimental group only, the results allow us to improve the experiment and apply the methodology developed in a less structured branch than the Operational Research (Graph Theory) is. The methodology is another benefit of the paper, because it can be applied independently on a particular domain.

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Virtual portal (VIPO) is designed to provide users with a single-point access to information, and tools to support their decision-making. VIPO illustrates the best practice presented in terms of case studies coded along three dimensions: field, domain and objectives. The second major source of knowledge is based on software packages made available to users including tutor support. The third part of the portal provides useful links to the existing databases which have the potential to facilitate decision making in agribusiness. All three pillars of the VIPO are complemented by on-line consultancy services.

• The originality of papers is measured based knowledge units' network, which is captured by the content of papers. • The content of papers is divided into three parts: research topics, research methods and research results by characteristic words and location in abstract. • Comparing with citations network analysis and knowledge combinations, the method is more reasonable and exact in measuring originality of academic papers. • The practical implication of our research is that to propose a new method to measure the originality of papers. Research on the evaluation of the quality of academic papers is attracting more attention from scholars in scientometrics. However, most previous researches have assessed paper quality based on external indicators, such as citations, which failed to account for the content of the research. To that end, this paper proposed a new method for measuring a paper's originality. The method was based on knowledge units in semantic networks, focusing on the relationship and semantic similarity of different knowledge units. Connectivity and path similarity between different content elements were used in particular networks as indicators of originality. This study used papers published between 2014 and 2018 in three categories (i.e. Library & Information Science, Educational Psychology, and Carbon Nanotubes) and divided their content into three parts (i.e. research topics, research methods and research results). It was found that the originality in all categories increase each year. Furthermore, a comparison of our new method with previous models of citation network analysis and knowledge combination analysis showed that our new method is better than those previous methods when used in measuring originality. [ABSTRACT FROM AUTHOR]

With analysis of the features of decision-making information fusion and actual emergency decision making, this paper presents a decision-making information fusion method based on distance entropy according to the demand for objectivity and scientificity. Firstly, the fusion set is acquired and stored based on knowledge unit model. Secondly, the information units are formed through instantiating knowledge units, which can provide information support for the fusion. Afterwards, the concept of distance entropy is proposed with an element of distance added into the traditional entropy weight method. Thus, we can obtain both local and global fusion weight, finally to gain the global fusion results using the way of linear weighting. Furthermore, the application value and effectiveness of this method are illustrated by empirical analysis. Experimental analysis show that the proposed method can solve problems of the hugeness of knowledge base and improve the objectivity and scientificity of fusion results in decision-making information fusion. [ABSTRACT FROM AUTHOR]

The objective of this work is to identify the differences among educational texts written in two styles: normal educational text and their knowledge form. The research sample consists of 60 documents - educational texts on agriculture waste processing - converted by the authors into the knowledge form. Over the set of indicators used for evaluating the educational texts, we formulated working and operational hypotheses and validated them using the paired sample t-test. The results show that the complex text difficulty rate of knowledge texts is significantly (α = 0.05) lower than of the normal texts. They present the same amount of information logically divided into more simple sentences merged to complex sentences. Based on the difference in frequencies of selected identifiers we are able to distinguish the literary styles. The further research aims at an automatic recognition of the text styles and measuring the amount of knowledge inside the text. [ABSTRACT FROM AUTHOR]