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Topic

Semantic Web

About: Semantic Web is a research topic. Over the lifetime, 26987 publications have been published within this topic receiving 534275 citations. The topic is also known as: Sem Web & SemWeb.


Papers
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Proceedings ArticleDOI
16 Apr 2012
TL;DR: This work presents an efficient approach to relational learning on LOD data, based on the factorization of a sparse tensor that scales to data consisting of millions of entities, hundreds of relations and billions of known facts, and shows how ontological knowledge can be incorporated in the factorizations to improve learning results and how computation can be distributed across multiple nodes.
Abstract: Vast amounts of structured information have been published in the Semantic Web's Linked Open Data (LOD) cloud and their size is still growing rapidly. Yet, access to this information via reasoning and querying is sometimes difficult, due to LOD's size, partial data inconsistencies and inherent noisiness. Machine Learning offers an alternative approach to exploiting LOD's data with the advantages that Machine Learning algorithms are typically robust to both noise and data inconsistencies and are able to efficiently utilize non-deterministic dependencies in the data. From a Machine Learning point of view, LOD is challenging due to its relational nature and its scale. Here, we present an efficient approach to relational learning on LOD data, based on the factorization of a sparse tensor that scales to data consisting of millions of entities, hundreds of relations and billions of known facts. Furthermore, we show how ontological knowledge can be incorporated in the factorization to improve learning results and how computation can be distributed across multiple nodes. We demonstrate that our approach is able to factorize the YAGO~2 core ontology and globally predict statements for this large knowledge base using a single dual-core desktop computer. Furthermore, we show experimentally that our approach achieves good results in several relational learning tasks that are relevant to Linked Data. Once a factorization has been computed, our model is able to predict efficiently, and without any additional training, the likelihood of any of the 4.3 ⋅ 1014 possible triples in the YAGO~2 core ontology.

430 citations

Book ChapterDOI
09 Jun 2002
TL;DR: This paper focuses on collaborative development of ontologies with OntoEdit which is guided by a comprehensive methodology.
Abstract: Ontologies now play an important role for enabling the semantic web. They provide a source of precisely defined terms e.g. for knowledge-intensive applications. The terms are used for concise communication across people and applications. Typically the development of ontologies involves collaborative efforts of multiple persons. OntoEdit is an ontology editor that integrates numerous aspects of ontology engineering. This paper focuses on collaborative development of ontologies with OntoEdit which is guided by a comprehensive methodology.

422 citations

01 Jan 2004
TL;DR: D2R Server is a tool for publishing the content of relational databases on the Semantic Web that allows Web agents to retrieve RDF and XHTML representations of resources and to query non-RDF databases using the SParQL query language over the SPARQL protocol.
Abstract: D2R Server is a tool for publishing the content of relational databases on the Semantic Web. Database content is mapped to RDF by a declarative mapping which specifies how resources are identified and how property values are generated from database content. Based on this mapping, D2R Server allows Web agents to retrieve RDF and XHTML representations of resources and to query non-RDF databases using the SPARQL query language over the SPARQL protocol. The generated representations are richly interlinked on RDF and XHTML level in order to enable browsers and crawlers to navigate database content.

421 citations

Journal ArticleDOI
TL;DR: A comprehensive review of BIM and IoT integration research to identify common emerging areas of application and common design patterns in the approach to tackling BIM-IoT device integration along with an examination of current limitations and predictions of future research directions is conducted.

418 citations

Journal ArticleDOI
TL;DR: It is found that the areas of open standard, web services, RDF, semantic technologies and portals with self‐service technologies are going to play a significant part in the evolution of CM systems.
Abstract: Purpose – Aims to review the key concepts of competency management (CM) and to propose method for developing competency method.Design/methodology/approach – Examines the CM features of 22 CM systems and 18 learning management systems.Findings – Finds that the areas of open standard (XML, web services, RDF), semantic technologies (ontologies and the semantic web) and portals with self‐service technologies are going to play a significant part in the evolution of CM systems.Originality/value – Emphasizes the beneficial attributes of CM for private and public organizations.

418 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023116
2022348
2021412
2020612
2019782
2018881