Ontological Knowledge Representation Research Articles

Особенности наследования информации в задачах интеграции систем технической подготовки производства

The article describes the specifics of information inheritance when transferring data from CAD system to CAM system: the object-oriented nature of the transmitted data and the influence of PLM contexts on data semantics. The objectoriented approach implies in the information transfer processes the presence of ―parents‖ and ―descendants‖ and associative relations between them, which makes it possible to reuse engineering projects. UML representation clearly describes the various schemes of information inheritance in the CAD/CAM-integration. These schemes must be taken into account when implementing end-to-end engineering projects. The PLM context is considered as the semantic field of the product life cycle stage, which affects the interpretation of engineering data. Digital space of an enterprise consists of informational contexts which affect the values of the transmitted data. Ignoring this circumstance leads to the loss or distortion of the actual values of the inherited parameters. The article provides a definition of the PLM context as an ontology of the product life cycle stage, which acts as the external environment in relation to integrated applications. A preliminary version of the ontology of the technological domain has been developed. It is proposed to store information about the stages of the product life cycle directly inside the 3D model of the product in the ontological representation of knowledge based on the XML standard. The specifics of information inheritance are considered on the example of integration of the CAM-system developed by the author of the article with its basic CAD-platform KOMPAS-3D. A strategy for automating the influence of PLM contexts on the values of the transmitted data is proposed.

An Ontology Based Expert System for Lung Cancer : OBESLC

Lung Cancer is the second most recurrent cancer in both men and women and which is the leading cause of cancer death worldwide. The American cancer Society (ACS) in US estimates nearly 228,150 new cases of lung cancer and 142,670 deaths from lung cancer for the year 2019. This paper proposes to build an ontology based expert system to diagnose Lung Cancer Disease and to identify the stage of Lung Cancer. Ontology is defined as a specification of conceptualization and describes knowledge about any domain in the form of concepts and relationships among them. It is a framework for representing shareable and reusable knowledge across a domain. The advantage of using ontology for knowledge representation of a particular domain is they are machine readable. We designed a System named OBESLC (Ontology Based Expert System for Lung Cancer) for lung cancer diagnosis, in that to construct an ontology we make use of Ontology Web Language (OWL) and Resource Description Framework (RDF) .The design of this system depends on knowledge about patient’s symptoms and the state of lung nodules to build knowledge base of Lung Cancer Disease. We verified our ontology OBESLC by querying it using SPARQL query language, a popular query language for extracting required information from Semantic web. We validate our ontology by developing reasoning rules using semantic Web Rule Language (SWRL).To provide the user interface, we implemented our approach in java using Jena API and Eclipse Editor.

Web Summarization and Browsing Through Semantic Tag Clouds

The need to manage electronic documents is an open issue in the digital era. It becomes a challenging problem on the internet where a large amount of data needs even more efficient and effective methods and techniques for mining and representing information. In this context, document summarization, browsing processes and visualization techniques have had a great impact on several dimensions of user information perception. In this context, the use of ontologies for knowledge representation has rapidly grown in the last years in several application domains together with social-based techniques such as tag clouds. This form of visualization tool is becoming particularly useful in the interaction process between users and social applications where a huge amount of data needs to have effective and efficient interfaces. In this article, the authors propose a novel methodology based on a combination of ontologies and Tag Clouds for web document collections browsing and summarizing, they call this tool Semantic Tag Cloud.

Criminal intelligence analysis based on ontological knowledge representation model

Nowadays, community security is an issue which is given higher priority by all agencies, aiming to reduce crime incidence. As knowledge representation is the appropriate way to apply on complex crime analysis information, hence ontology-based case matching model is proposed to represent the relationships among the knowledge. Therefore, in this study, the ontology model is developed using semantic web modelling tool, TopBraid Composer Standard Edition in order to represent the crime information with the well-defined classes and relationships. The advantage of TopBraid is the ability in offering comprehensive supports for building, managing and testing the configuration of ontology and Resource Description Framework (RDF) graphs.

Software engineering ontologies categorization

Software engineering is an own scientific and practice aria with an own structure, terminology, products, pro-cesses and resources. The software product is a knowledge-based product and it is the result of the knowledge-based actions. In this research, categorization of ontologies in software engineering are presented. The known criterion (process, domain, structure) are used for the categorization of ontologies but two criterion (process and domain) was modified. The process criterions is looked in the connection whit time period and the prede-velopment time added to time period. The domain criterions is making whit help of the representation of soft-ware engineering world in the form of domains. The ontologies are involved in representing knowledge of three types of the software engineering domains. In the first, the application domain, the focus is on under-standing the customer needs and what the software product must do. In the second, the implementation do-main, the focus is on understanding how the software product must behave and respond to the customer needs. In the third, the problem domain, the focus is on understanding the software engineering problems, which can be during software life cycle processes of the software product. Our research goal is to develop categorization of the software engineering ontologies on the base of adding known criterion. Ontological representation of software engineering knowledge; categorization; domain analysis; object-oriented programming; ontology-driven utilizing of programming styles. Categorization of the software engineering ontologies. The results of case study, using ontologies by categorization are presented. Had developed categorization of ontologies, it is possible exactly to define types of software engineering ontologies and its places into software processes. This is demonstrating on the examples of the case studies. Problems in programming 2018; 1: 55-64

Knowledge Representation in Patient Safety Reporting: An Ontological Approach.

The current development of patient safety reporting systems is criticized for loss of information and low data quality due to the lack of a uniformed domain knowledge base and text processing functionality. To improve patient safety reporting, the present paper suggests an ontological representation of patient safety knowledge. We propose a framework for constructing an ontological knowledge base of patient safety. The present paper describes our design, implementation, and evaluation of the ontology at its initial stage. We describe the design and initial outcomes of the ontology implementation. The evaluation results demonstrate the clinical validity of the ontology by a self-developed survey measurement. The proposed ontology was developed and evaluated using a small number of information sources. Presently, US data are used, but they are not essential for the ultimate structure of the ontology. The goal of improving patient safety can be aided through investigating patient safety reports and providing actionable knowledge to clinical practitioners. As such, constructing a domain specific ontology for patient safety reports serves as a cornerstone in information collection and text mining methods. The use of ontologies provides abstracted representation of semantic information and enables a wealth of applications in a reporting system. Therefore, constructing such a knowledge base is recognized as a high priority in health care.

Development of requirements for a decision support system aimed at quality assessment of public services provided based on the ontological approach

Liliya R. Chernyakhovskaya - Professor, Department of Technical Cybernetics, Ufa State Aviation Technical UniversityAddress: 12, Karl Marx Street, Ufa, Republic of Bashkortostan, 450008, Russian FederationE-mail: lrchern@yandex.ruAlbina F. Galiullina - Doctoral Student, Department of Technical Cybernetics, Ufa State Aviation Technical UniversityAddress: 12, Karl Marx Street, Ufa, Republic of Bashkortostan, 450008, Russian FederationE-mail: GAF1205@yandex.ru This article describes the requirements for a decision support system which is designed to assess the quality of public services. Requirements for a decision support system are used as a starting point at its design stage and determine the functions of the developed system without showing the mechanism of its implementation. At the same time, the requirements serve as constraints in the process of system development. The set of the developed requirements for the decision support system includes basic, functional, non-functional and economic requirements. We propose to use the ontological approach in the development of requirements for the system. This allows us to solve a number of problems arising from the description of the requirements in natural language: the lack of exposition clarity, misrepresentation of the requirements and so on. The ontological model allows developers to interpret the requirements in the same way, to structure the specification of requirements for the system and to eliminate blurring in their definitions. Ontological representation of knowledge about requirements for the developed system and about the system providing public services in general is used for the semantic integration of existing information resources, appropriate interpretation of the content of text documents and search queries presented in a natural language. The developed ontology improves the quality of user (stakeholder) interaction during the system operation. In addition, it includes rules for term combination to provide reliable assertions on the state of the decision support system.[1] This work was supported by the Russian Foundation for Basic Research, project no. 14-08-97023 “Intellectual support of managing decision-making in innovative projects relying on knowledge processing and mathematical modeling”

Knowledge-based recommendation: a review of ontology-based recommender systems for e-learning

Recommender systems in e-learning domain play an important role in assisting the learners to find useful and relevant learning materials that meet their learning needs. Personalized intelligent agents and recommender systems have been widely accepted as solutions towards overcoming information retrieval challenges by learners arising from information overload. Use of ontology for knowledge representation in knowledge-based recommender systems for e-learning has become an interesting research area. In knowledge-based recommendation for e-learning resources, ontology is used to represent knowledge about the learner and learning resources. Although a number of review studies have been carried out in the area of recommender systems, there are still gaps and deficiencies in the comprehensive literature review and survey in the specific area of ontology-based recommendation for e-learning. In this paper, we present a review of literature on ontology-based recommenders for e-learning. First, we analyze and classify the journal papers that were published from 2005 to 2014 in the field of ontology-based recommendation for e-learning. Secondly, we categorize the different recommendation techniques used by ontology-based e-learning recommenders. Thirdly, we categorize the knowledge representation technique, ontology type and ontology representation language used by ontology-based recommender systems, as well as types of learning resources recommended by e-learning recommenders. Lastly, we discuss the future trends of this recommendation approach in the context of e-learning. This study shows that use of ontology for knowledge representation in e-learning recommender systems can improve the quality of recommendations. It was also evident that hybridization of knowledge-based recommendation with other recommendation techniques can enhance the effectiveness of e-learning recommenders.

Use of the Ontological Model for Personification of the Semantic Search

Semantic search is an important component of modern intelligent applications oriented on work in open information environment. The intelligence level of application depends of it’s capabilities in knowledge processing and defines it’s facilities. Now applications widely use ontologies for knowledge representation. Therefore criteria of intelligence level estimation (that can analyze ontologies) of applications and retrieval systems as their particular case are proposed. In this paper, an ontological model of the intelligent interaction of the main objects and subjects of the semantic search (the Web information resources, information objects and information consumers etc.) is developed. Software realization of semantic search on base of this ontological model and integration of this search instrument with applied systems are describes.

DEPONTO: A Reusable Dependability Domain Ontology

This paper proposes a dependability reusable ontology for knowledge representation. The fundamental knowledge related to dependability follows its taxonomy. Thus, this paper gives an analysis of what is the dependability domain ontology andof its components.The dependability domain ontology plays an important role in ensuring the dependability of information systems by providing support for their diagnosis in case of faults, errors and failures.The proposed ontology is used as a dependability framework in two case study Cyber-Physical Systemswhich demonstrate its reusability within this category of systems.

ПРОГНОЗУВАННЯ СТАНІВ І ЕФЕКТУ ПРИ ДОПОМІЖНИХ РЕПРОДУКТИВНИХ ТЕХНОЛОГІЯХ НА ОСНОВІ БАГАТОРІВНЕВИХ ОНТОЛОГІЙ

<p>The problem of prediction on the basis ontological knowledge representation of assisted reproductive technologies is considered. A number of levels medical care for patients with infertility problems is identified. At each level the set of surviving in the memory elements of information given on it with a binary relation induced by associative links between the various elements, bijectively is assigned oriented connected graph G.</p><p>Forecasting is ensured by using a decision rule oriented on the computation of projected state indicator. It is calculated by comparing the transition probabilities of the initial states available to patient, in prospective with probability of transition from other states in the same analyzed element graph. Demonstrated possibility practical implementation of the suggested approach. The forecasting accuracy for the first period accumulation of data completely persuasive and is (88,2 ±4) % is shown.</p>

Ontology-centered environmental information delivery for personalized decision support

Data on observed and forecasted environmental conditions, such as weather, air quality and pollen, are offered in a great variety in the web and serve as basis for decisions taken by a wide range of the population. However, the value of these data is limited because their quality varies largely and because the burden of their interpretation in the light of a specific context and in the light of the specific needs of a user is left to the user herself. To remove this burden from the user, we propose an environmental Decision Support System (DSS) model with an ontology-based knowledge base as its integrative core. The availability of an ontological knowledge representation allows us to encode in a uniform format all knowledge that is involved (environmental background knowledge, the characteristic features of the profile of the user, the formal description of the user request, measured or forecasted environmental data, etc.) and apply advanced reasoning techniques on it. The result is an advanced DSS that provides high quality environmental information for personalized decision support.

USING ONTOLOGIES FOR THE EMERGENCY RESPONSE SUPPORT: A SURVEY

Ontology is an efficient and an adequate way of conceptualization of knowledge representation for real world applications. Ontologies are successfully used in varieties of knowledge domains. In this paper, we focus on the field of medical ontology knowledge construction and representation. We identified three different medical ontologies classes: Generic, Specific and Mass Casualties Incidents (MCI) medical ontologies. This survey should support the construction of medical Ontologies in future for a better patient treatment. In particular, we survey and focus on the existing medical related ontologies and investigate their suitability for use in Mass Casualties Incidents (MCI).

Semantic Retrieval for Ontology-Based Aircraft Fault Knowledge

With consideration of the actual requirement of fault knowledge retrieval in current aviation maintenance, semantic retrieval method for ontology-based aircraft fault knowledge is studied. Based on the concepts of semantic and semantic retrieval, it is proposed that the knowledge representation of ontology is applicable for semantic retrieval. On the basis of aircraft fault ontology model, the semantic retrieval model has been established, and the concept-matching similarity algorithm using semantic distance of ontology concepts is proposed. In the semantic retrieval method, the depth factor and density factor of ontology model are expressed, and the semantic distance calculation and the transformation function from semantic distance to conceptual similarity are proposed. The semantic retrieval research provides support for efficient application of ontology-based aircraft fault knowledge.

A crowdsourcing approach to building a legal ontology from text

This article focuses on the problems of application of artificial intelligence to represent legal knowledge. The volume of legal knowledge used in practice is unusually large, and therefore the ontological knowledge representation is proposed to be used for semantic analysis, presentation and use of common vocabulary, and knowledge integration of problem domain. At the same time some features of legal knowledge representation in Ukraine have been taken into account. The software package has been developed to work with the ontology. The main features of the program complex, which has a Web-based interface and supports multi-user filling of the knowledge base, have been described. The crowdsourcing method is due to be used for filling the knowledge base of legal information. The success of this method is explained by the self-organization principle of information. However, as a result of such collective work a number of errors are identified, which are distributed throughout the structure of the ontology. The results of application of this program complex are discussed in the end of the article and the ways of improvement of the considered technique are planned.

Implementation of Knowledge Models by Applying Ontologies

The influencing factors for undergraduate students dropout can be considered subjective and unusual dependencies. This situation is not particular to IFSC and is treated with great concern also by other educational institutions. Numerous theories pointing the origin and cause of the problem have arisen from discussions, followed by proposals and examples of solutions that often do not work or are not feasible because they are related to peculiarities. This work focuses in the study of the effects that can be obtained by making use of the resources offered by modeling and ontological knowledge representation in the context mentioned above.

Combining ontological and temporal formalisms for composite activity modelling and recognition in smart homes

Activity recognition is essential in providing activity assistance for users in smart homes. While significant progress has been made for single-user single-activity recognition, it still remains a challenge to carry out real-time progressive composite activity recognition. This paper introduces a hybrid ontological and temporal approach to composite activity modelling and recognition by extending existing ontology-based knowledge-driven approach. The compelling feature of the approach is that it combines ontological and temporal knowledge representation formalisms to provide powerful representation capabilities for activity modelling. The paper describes in detail ontological activity modelling which establishes relationships between activities and their involved entities, and temporal activity modelling which defines relationships between constituent activities of a composite activity. As an essential part of the model, the paper also presents methods for developing temporal entailment rules to support the interpretation and inference of composite activities. In addition, this paper outlines an integrated architecture for composite activity recognition and elaborated a unified activity recognition algorithm which can support the recognition of simple and composite activities. The approach has been implemented in a feature-rich prototype system upon which testing and evaluation have been conducted. Initial experimental results have shown average recognition accuracy of 100% and 88.26% for simple and composite activities, respectively.

Automatically Generated Layered Ontological Models for Semantic Analysis of Component-Based Control Systems

The IEC 61499 standard is designed for distributed control and proposes new visual form of programming using block diagrams with embedded state machines and unlimited hierarchical nesting and distribution across networking devices. Such visual programs require new methods of automatic syntactic and semantic analysis. This paper proposes a new approach to semantic analysis using multiple-layered ontological knowledge representation and rule-based inference engine. Its working is demonstrated on example.

ENERGY EFFICIENCY EVALUATION IN MANUFACTURING THROUGH AN ONTOLOGY‐REPRESENTED KNOWLEDGE BASE

SUMMARYImproving energy efficiency in a manufacturing company through an energy management system requires active participation of different stakeholders and involvement of different organizational entities and technical processes. Interoperability of stakeholders and entities is the key factor to achieve a successful implementation of an energy management system. Researchers have been developing approaches in applying ontologies to address interoperability issues among humans as well as machines. Ontologies have also been used for knowledge representation in different domains, such as energy management and manufacturing. In recent years, researchers have developed knowledge‐based intelligent energy management systems in buildings, especially households, which use ontologies for knowledge representation. In the manufacturing domain, ontologies have been used for knowledge management in order to provide a common formal understanding between the stakeholders, who have different background knowledge. This paper proposes an approach to apply ontology to allow knowledge‐based energy efficiency evaluation in manufacturing companies. The ontology provides a formal knowledge representation that addresses the interoperability issues due to different human stakeholders as well as machines involved in the energy management system of the company. This paper also describes the methods used to construct and to process the ontology. Copyright © 2013 John Wiley & Sons, Ltd.

Overview of Ontology-Based Power System Applications

With the construction of smart grid, an increasing number of resources of smart grid knowledge base inevitably lead to the information island of power system and low utilization ratio of power system knowledge. Introduced the ontology for knowledge representation of Smart Grid domain and constructed a repository to be shared by each application software system. It can enhance the power system simulation and analysis capabilities of the complex state of the Smart Grid. At present, Smart Grid lacks of researches on knowledge applications based on ontology technology. This paper introduces some typical applications based on ontology, elaborates the application status of the ontology in power system. According to the ontology technology applied to typical domains, it looks forward to the direction of ontology-based applications in power system.