Related papers: An Ontology-Based Capability Description of MTP Mo…
This paper outlines a theoretical framework using which different automatic metrics can be designed for evaluation of Machine Translation systems. It introduces the concept of {\em cognitive ease} which depends on {\em adequacy} and {\em…
The SemanticWeb emerged as an extension to the traditional Web, towards adding meaning to a distributed Web of structured and linked data. At its core, the concept of ontology provides the means to semantically describe and structure…
Integrating deep learning techniques, particularly language models (LMs), with knowledge representation techniques like ontologies has raised widespread attention, urging the need of a platform that supports both paradigms. Although…
In this paper, we propose a framework of knowledge for an agriculture ontology which can be used for the purpose of smart agriculture systems. This ontology not only includes basic concepts in the agricultural domain but also contains…
Large ontologies still pose serious challenges to state-of-the-art ontology alignment systems. In this paper we present an approach that combines a neural embedding model and logic-based modules to accurately divide an input ontology…
Efficiency and scalability are obstacles that have not yet received a viable response from the human activity recognition research community. This paper proposes an activity recognition method. The knowledge model is in the form of…
Data integration is considered a classic research field and a pressing need within the information science community. Ontologies play a critical role in such a process by providing well-consolidated support to link and semantically…
By introducing a common representational system for metadata that describe the employed simulation workflows, diverse sources of data and platforms in computational molecular engineering, such as workflow management systems, can become…
In this paper, we introduce a novel interpreting framework that learns an interpretable model based on an ontology-based sampling technique to explain agnostic prediction models. Different from existing approaches, our algorithm considers…
Ontologies are widely used for representing domain knowledge and meta data, playing an increasingly important role in Information Systems, the Semantic Web, Bioinformatics and many other domains. However, logical reasoning that ontologies…
This paper presents a semantic system named OntMed for an ontology-based data integration of heterogeneous data sources to achieve interoperability between heterogeneous data sources. Our system is based on the quality criteria…
Researchers across nearly every discipline seek to leverage ontologies for knowledge discovery and computational tasks; yet, the number of machine readable materials science ontologies is limited. The work presented in this paper explores…
The integration of Artificial Intelligence (AI) into automation systems has the potential to enhance efficiency and to address currently unsolved existing technical challenges. However, the industry-wide adoption of AI is hindered by the…
PL for SOA proposes, formally, a software engineering methodology, development techniques and support tools for the provision of service product lines. We propose rigorous modeling techniques for the specification and verification of formal…
The semantic description of music metadata is a key requirement for the creation of music datasets that can be aligned, integrated, and accessed for information retrieval and knowledge discovery. It is nonetheless an open challenge due to…
This Ontologies are widely used as a means for solving the information heterogeneity problems on the web because of their capability to provide explicit meaning to the information. They become an efficient tool for knowledge representation…
This paper is based on and advocates the trend in software engineering of extending the use of software patterns as means of structuring solutions to software development problems (be they motivated by best practice or by company interests…
The Virtual Materials Marketplace (VIMMP) project, which develops an open platform for providing and accessing services related to materials modelling, is presented with a focus on its ontology development and data technology aspects.…
Taking advantage of the widespread use of ontologies to organise and harmonize knowledge across several distinct domains, this paper proposes a novel approach to improve an embedding-Large Language Model (embedding-LLM) of interest by…
Machine Learning (ML) systems are capable of reproducing and often amplifying undesired biases. This puts emphasis on the importance of operating under practices that enable the study and understanding of the intrinsic characteristics of ML…