3,965 research outputs found
Lightweight Ontologies
Ontologies are explicit specifications of conceptualizations. They are often thought of as directed graphs whose nodes represent concepts and whose edges represent relations between concepts. The notion of concept is understood as defined in Knowledge Representation, i.e., as a set of objects or individuals. This set is called the concept extension or the concept interpretation. Concepts are often lexically defined, i.e., they have natural language names which are used to describe the concept extensions (e.g., concept mother denotes the set of all female parents). Therefore, when ontologies are visualized, their nodes are often shown with corresponding natural language concept names. The backbone structure of the ontology graph is a taxonomy in which the relations are “is-a”, whereas the remaining structure of the graph supplies auxiliary information about the modeled domain and may include relations like “part-of”, “located-in”, “is-parent-of”, and many others
A Pattern Based Approach for Re-engineering Non-Ontological Resources into Ontologies
With the goal of speeding up the ontology development process, ontology engineers are starting to reuse as much as possible available ontologies and non-ontological resources such as classification schemes, thesauri, lexicons and folksonomies, that already have some degree of consensus. The reuse of such non-ontological resources necessarily involves their re-engineering into ontologies. Non-ontological resources are highly heterogeneous in their data model and contents: they encode different types of knowledge, and they can be modeled and implemented in different ways. In this paper we present (1) a typology for non-ontological resources, (2) a pattern based approach for re-engineering non-ontological resources into ontologies, and (3) a use case of the proposed approach
Research and Development Workstation Environment: the new class of Current Research Information Systems
Against the backdrop of the development of modern technologies in the field
of scientific research the new class of Current Research Information Systems
(CRIS) and related intelligent information technologies has arisen. It was
called - Research and Development Workstation Environment (RDWE) - the
comprehensive problem-oriented information systems for scientific research and
development lifecycle support. The given paper describes design and development
fundamentals of the RDWE class systems. The RDWE class system's generalized
information model is represented in the article as a three-tuple composite web
service that include: a set of atomic web services, each of them can be
designed and developed as a microservice or a desktop application, that allows
them to be used as an independent software separately; a set of functions, the
functional filling-up of the Research and Development Workstation Environment;
a subset of atomic web services that are required to implement function of
composite web service. In accordance with the fundamental information model of
the RDWE class the system for supporting research in the field of ontology
engineering - the automated building of applied ontology in an arbitrary domain
area, scientific and technical creativity - the automated preparation of
application documents for patenting inventions in Ukraine was developed. It was
called - Personal Research Information System. A distinctive feature of such
systems is the possibility of their problematic orientation to various types of
scientific activities by combining on a variety of functional services and
adding new ones within the cloud integrated environment. The main results of
our work are focused on enhancing the effectiveness of the scientist's research
and development lifecycle in the arbitrary domain area.Comment: In English, 13 pages, 1 figure, 1 table, added references in Russian.
Published. Prepared for special issue (UkrPROG 2018 conference) of the
scientific journal "Problems of programming" (Founder: National Academy of
Sciences of Ukraine, Institute of Software Systems of NAS Ukraine
Comprehensive Security Framework for Global Threats Analysis
Cyber criminality activities are changing and becoming more and more professional. With the growth of financial flows through the Internet and the Information System (IS), new kinds of thread arise involving complex scenarios spread within multiple IS components. The IS information modeling and Behavioral Analysis are becoming new solutions to normalize the IS information and counter these new threads. This paper presents a framework which details the principal and necessary steps for monitoring an IS. We present the architecture of the framework, i.e. an ontology of activities carried out within an IS to model security information and User Behavioral analysis. The results of the performed experiments on real data show that the modeling is effective to reduce the amount of events by 91%. The User Behavioral Analysis on uniform modeled data is also effective, detecting more than 80% of legitimate actions of attack scenarios
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Using a lightweight multimedia content model for semantic annotation
In this paper we discuss the use of a multimedia content model for automatic extraction of semantic metadata from multimedia content. We developed a modular and extensible framework to model the content feature of multimedia data and also describe the way it can be integrated with other existing vocabularies. The goal of this model is to generate sufficient understanding of media content, its context and its relation to domain knowledge in order to perform multimedia reasoning. We implemented a tool that analyzes and links low-level descriptions to higher-level domain specific semantic concepts by means of statistical learning and clustering analysis. Experimental result shows the approach performs well in visual concept prediction in the image which can be further augmented with other information sources such as context text and or audio source
The Impact on Citation Analysis Based on Ontology and Linked Data
Research focus: The aim of this chapter is to introduce a new citation analysis and service framework based on the semantic web technologies (e.g., ontology and linked data). Research methods: This research project is based on a review of relevant literature and a series of experimental results based on ontology and linked data. Motivation: Traditional citation analysis methods and tools are overly dependent on citation databases, and traditional citation information service may ignore the semantics of knowledge resources and lack ability to store and query data in a machine-readable mode. Findings: The findings underline that the new citation analysis and service system framework based on ontology and linked data are feasible, which can integrate information requirements and knowledge services, and provide users with more personalized and comprehensive services
Pedagogically-driven Ontology Network for Conceptualizing the e-Learning Assessment Domain
The use of ontologies as tools to guide the generation, organization and personalization of e-learning content, including e-assessment, has drawn attention of the researchers because ontologies can represent the knowledge of a given domain and researchers use the ontology to reason about it. Although the use of these semantic technologies tends to enhance technology-based educational processes, the lack of validation to improve the quality of learning in their use makes the educator feel reluctant to use them. This paper presents progress in the development of an ontology network, called AONet, that conceptualizes the e-assessment domain with the aim of supporting the semi-automatic generation of assessment, taking into account not only technical aspects but also pedagogical ones.Fil: Romero, Lucila. Universidad Nacional del Litoral; ArgentinaFil: North, Matthew. The college of Idabo; Estados UnidosFil: Gutierrez, Milagros. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Centro de Investigación y Desarrollo de Ingeniería en Sistemas de Información; ArgentinaFil: Caliusco, Maria Laura. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Centro de Investigación y Desarrollo de Ingeniería en Sistemas de Información; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentin
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