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In the realm of Digital Humanities, the management of cultural heritage metadata is pivotal for ensuring data trustworthiness. Provenance information - contextual metadata detailing the origin and history of data - plays a crucial role in…
The acquisition of physical artifacts not only involves transferring existing information into the digital ecosystem but also generates information as a process itself, underscoring the importance of meticulous management of FAIR data and…
Although the intention of RDF is to provide an open, minimally constraining way for representing information, there exists an increasing number of applications for which guarantees on the structure and values of an RDF data set become…
Over the last decades the Web has evolved from a human-human communication network to a network of complex human-machine interactions. An increasing amount of data is available as Linked Data which allows machines to "understand" the data,…
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…
Hypergraphs play a pivotal role in the modelling of data featuring higher-order relations involving more than two entities. Hypergraph neural networks emerge as a powerful tool for processing hypergraph-structured data, delivering…
Semantic Web knowledge representation standards, and in particular RDF and OWL, often come endowed with a formal semantics which is considered to be of fundamental importance for the field. Reasoning, i.e., the drawing of logical inferences…
Enterprise information systems have adopted Web-based foundations for exchanges between heterogeneous programmes. These programs provide and consume via Web APIs some resources identified by URIs, whose representations are transmitted via…
The Resource Description Framework (RDF) is a framework for describing metadata, such as attributes and relationships of resources on the Web. Machine learning tasks for RDF graphs adopt three methods: (i) support vector machines (SVMs)…
In the coming era of semantic web linked data analysis is a very burning issue for efficient searching and retrieval of information. One way of establishing this link is to implement subject predicate object relationship through Set Theory…
This article presents a model of general-purpose computing on a semantic network substrate. The concepts presented are applicable to any semantic network representation. However, due to the standards and technological infrastructure devoted…
As the amount of data on the World Wide Web continues to grow exponentially, access to semantically structured information remains limited. The Semantic Web has emerged as a solution to enhance the machine-readability of data, making it…
Geographic data plays an essential role in various Web, Semantic Web and machine learning applications. OpenStreetMap and knowledge graphs are critical complementary sources of geographic data on the Web. However, data veracity, the lack of…
Knowledge Graphs, such as Wikidata, comprise structural and textual knowledge in order to represent knowledge. For each of the two modalities dedicated approaches for graph embedding and language models learn patterns that allow for…
The increasing availability of semantic data has substantially enhanced Web applications. Semantic data such as RDF data is commonly represented as entity-property-value triples. The magnitude of semantic data, in particular the large…
Semantic entity recognition is an important task in the field of visually-rich document understanding. It distinguishes the semantic types of text by analyzing the position relationship between text nodes and the relation between text…
The recent advancements of the Semantic Web and Linked Data have changed the working of the traditional web. There is significant adoption of the Resource Description Framework (RDF) format for saving of web-based data. This massive…
Archived collections of documents (like newspaper archives) serve as important information sources for historians, journalists, sociologists and other interested parties. Semantic Layers over such digital archives allow describing and…
Multi-relational networks are used extensively to structure knowledge. Perhaps the most popular instance, due to the widespread adoption of the Semantic Web, is the Resource Description Framework (RDF). One of the primary purposes of a…
With the need of fast retrieval speed and small memory footprint, document hashing has been playing a crucial role in large-scale information retrieval. To generate high-quality hashing code, both semantics and neighborhood information are…