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Knowledge graphs are a valuable tool for intelligent tutoring systems and are typically constructed with a focus on objectivity and accuracy. However, they may not effectively capture the subjectivity and complex relationships often present in the ...

The field of research in ontology engineering appears to be mature, considering the vast number of contemporary methods and instruments for the formalization and application of knowledge representation models. However, the evolutionary aspects of ...

The Semantic Web is an incomplete dream so far, but a revolutionary platform as Blockchain could be the solution to this, not optimal reality. There is still little understanding of, and support for, the evolutionary aspects of ontologies. This is ...

Ontologies are used to represent knowledge and they have become very important in the Semantic Web era. Ontologies evolve continuously during their life cycle to adapt to new requirements and needs, especially in the biomedical field, where the number ...

We propose a new method for knowledge acquisition and ontology refinement for the Semantic Web. The method is based on a combination of the attribute exploration algorithm from the formal concept analysis and active learning approach to machine ...

Ontology is becoming the key knowledge capture structure in many domains. It plays a very important role in the area of semantic web and is widely used in multiple fields including Intelligent Tutoring Systems (ITS) and e-Learning. Ontologies are ...

Ontologies, or more generally speaking, Knowledge Organization Systems (KOS) have been developed to support the correct interpretation of shared data in collaborative applications. The quantity and the heterogeneity of domain knowledge often require ...

Autonomous and Distributed repositories containing digital documents are maintained and managed independently in accordance to organization's business needs. Documents containing same information in different repositories maybe represented differently, ...

Huge amounts of data are generated by sensor readings, social media and databases. Such data introduce new challenges due to their volume and variety, and thus, new techniques are required for their utilization. We believe that reasoning can ...

Ontology development starts with a rigorous ontological analysis that provides a conceptualization of the domain to model agreed by the community. An ontology, specified in a formal language, approximates the intended models of this conceptualization. ...

Knowledge constantly grows in scientific discourse and is revised over time by different stakeholders, either collaboratively or through institutionalized efforts. The body of knowledge gets structured and refined as the Communities of Practice ...

In this paper, we present a generic ontology evolution approach guided by a pattern-oriented process and a quality evaluation activity. Pattern modeling aims to drive and control change application while maintaining consistency of the evolved ontology. ...

The development of new techniques and the emergence of new high- throughput tools have led to a new information revolution. The amount and the diversity of the information that need to be stored and processed have led to the adoption of data integration ...

Changes in an ontology may have a disruptive impact on any system using it. This impact may depend on structural changes such as introduction or removal of concept definitions, or it may be related to a change in the expected performance of the ...

This paper introduces the notion of Ontology Robustness in Evolution and discusses a solution based on the distinction among a stable component and a contingent component of the ontology. The stable component represents the annotation used to store data ...

The automatic extraction of ontologies from text and lexical resources has become more and more mature. Nowadays, the results of state-of-the-art ontology learning methods are already good enough for many practical applications. However, most of them ...

Currently, the available architectures for knowledge management are mainly centralized and focus on basic string processing in essence. They tend to ignore that knowledge is distributed and full of semantics in and among complex knowledge-based ...

Ontology evolution is an intrinsic phenomenon of any knowledge-intensive system, which can be addressed either implicitly or explicitly. This paper describes an explicit, data-driven approach to capture and visualize ontology evolution by semi-...

This article wants to address the need for a research effort and framework that studies and embraces the novel, difficult but crucial issues of adaptation of knowledge resources to their respective user communities, and vice versa, as a ...

Only few well-maintained domain ontologies can be found on the Web. The likely reasons for the lack of useful domain ontologies include that (1) informal means to convey intended meaning more efficiently are used for ontology specification only to ...