Related papers: OAK: Ontology-Based Knowledge Map Model for Digita…
In recent years, data science has evolved significantly. Data analysis and mining processes become routines in all sectors of the economy where datasets are available. Vast data repositories have been collected, curated, stored, and used…
In order to provide the agricultural industry with the infrastructure it needs to take advantage of advanced technology, such as big data, the cloud, and the internet of things (IoT); smart farming is a management concept that focuses on…
An ontology is a formal representation of domain knowledge, which can be interpreted by machines. In recent years, ontologies have become a major tool for domain knowledge representation and a core component of many knowledge management…
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…
Recent machine learning approaches have been effective in Artificial Intelligence (AI) applications. They produce robust results with a high level of accuracy. However, most of these techniques do not provide human-understandable…
Distributed data mining (DDM) deals with the problem of finding patterns or models, called knowledge, in an environment with distributed data and computations. Today, a massive amounts of data which are often geographically distributed and…
Most of the existing techniques to product discovery rely on syntactic approaches, thus ignoring valuable and specific semantic information of the underlying standards during the process. The product data comes from different heterogeneous…
Sustainable agricultural production aligns with several sustainability goals established by the United Nations (UN). However, there is a lack of studies that comprehensively examine sustainable agricultural practices across various products…
The increasing digitalization of the manufacturing domain requires adequate knowledge modeling to capture relevant information. Ontologies and Knowledge Graphs provide means to model and relate a wide range of concepts, problems, and…
Since Organizations have recognized that knowledge constitutes a valuable intangible asset for creating and sustaining competitive advantages, knowledge sharing has a vital role in present society. It is an activity through which…
The current learning systems typically lack the level of metacognitive awareness, self-directed learning, and time management skills. Most of the ontologically based learning management systems are in the proposed phase and those which are…
The reuse of atomistic simulation data is often limited by heterogeneous formats, incomplete metadata, and a lack of standardized representations of workflows and provenance. Here we present an ontology-based infrastructure for representing…
Retrieve information resources made by the machine processing may refer to multiple sources. A personal web as part of information resources in the Internet requires a feature that can be understood by computer machines. Therefore, in this…
Knowledge-based economy forces companies in the nation to group together as a cluster in order to maintain their competitiveness in the world market. The cluster development relies on two key success factors which are knowledge sharing and…
Scientometric techniques have been remarkably successful at mapping science but they face important difficulties when mapping research for societal problems possibly because they they are derived only from scientific documents and thus do…
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…
Empirical data plays an important role in evolutionary computation research. To make better use of the available data, ontologies have been proposed in the literature to organize their storage in a structured way. However, the full…
The loss of knowledge when skilled operators leave poses a critical issue for companies. This know-how is diverse and unstructured. We propose a novel method that combines knowledge graph embeddings and multi-modal interfaces to collect and…
The paper provides a survey of semantic methods for solution of fundamental tasks in mathematical knowledge management. Ontological models and formalisms are discussed. We propose an ontology of mathematical knowledge, covering a wide range…
In this paper, we present an ontology of mathematical knowledge concepts that covers a wide range of the fields of mathematics and introduces a balanced representation between comprehensive and sensible models. We demonstrate the…