13 research outputs found
Combining machine learning and semantic web: A systematic mapping study
In line with the general trend in artificial intelligence research to create intelligent systems that combine learning and symbolic components, a new sub-area has emerged that focuses on combining Machine Learning components with techniques developed by the Semantic Web community - Semantic Web Machine Learning (SWeML). Due to its rapid growth and impact on several communities in thepast two decades, there is a need to better understand the space of these SWeML Systems, their characteristics, and trends. Yet, surveys that adopt principled and unbiased approaches are missing. To fill this gap, we performed a systematic study and analyzed nearly 500 papers published in the past decade in this area, where we focused on evaluating architectural and application-specific features. Our analysis identified a rapidly growing interest in SWeML Systems, with a high impact on several application domains and tasks. Catalysts for this rapid growth are the increased application of deep learning and knowledge graph technologies. By leveraging the in-depth understanding of this area acquired through this study, a further key contribution of this article is a classification system for SWeML Systems that we publish as ontology.</p
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Results of the Ontology Alignment Evaluation Initiative 2021
The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity and use different evaluation modalities (e.g., blind evaluation, open evaluation, or consensus). The OAEI 2021 campaign offered 13 tracks and was attended by 21 participants. This paper is an overall presentation of that campaign
Stakeholder Influence on Earnings Management: Ethical Considerations and Potential Avenues
Discursively âUndoingâ and âDoing Europeâ the Austrian Way
Literature on European and national identities displays a tension between occasional observations of an emerging âbanal Europeanismâ (Cram, 2009) and a dominant strand (e.g. Guibernau, 2007; Toplak & Ć umi, 2012) that questions the viability of European identifications vis-Ă -vis historically entrenched nationalisms, particularly in the context of the debt crisis and the resulting (re)nationalization of European politics. This chapter builds on recent work on Austrian European Union (EU) scepticism and its contestation (Karner, 2013) to examine instances â in diverse media coverage, readersâ letters to the editor of Austriaâs most widely read newspaper, internet platforms, political essays and party political positions â of national identity negotiations in relation to the EU and as articulated in the context of successive European crises and the most recent elections to the European Parliament. The qualitative, thematic analysis of these wide-ranging materials developed here draws on two key concepts in critical discourse analysis, the notions of deixis (Billig, 1995) or ârhetorical pointingâ and of the topos or âstructure of argumentâ (e.g. Reisigl & Wodak, 2001), which are complemented by a third theoretical tool, namely the anthropological concept of âgrammars of identityâ (Baumann & Gingrich, 2004). The resulting discussion reveals the uneasy coexistence of (critical) Europeanisms and various national reassertions in Austriaâs public sphere and their respective discursive features. Further, the theoretical approaches synthesized cast light on internal diversities within political positions that are often too monolithicly classified as being âsimplyâ pro- or anti-European respectively. Instead, the analysis presented here reveals a spectrum of (at least five) competing positions
Muscles, Morals and Mind: craft apprenticeship and the formation of person
The paper considers apprenticeship as a model of education that both teaches technical skills and provides the grounding for personal formation. The research presented is based on long-term anthropological fieldwork with minaret builders in Yemen, mud masons in Mali and fine-woodwork trainees in London. These case studies of on-site learning and practice support an expanded notion of knowledge that exceeds propositional thinking and language and centrally includes the body and skilled performance. Crafts â like sport, dance and other skilled physical activities â are largely communicated, understood and negotiated between practitioners without words, and learning is achieved through observation, mimesis and repeated exercise. The need for an interdisciplinary study of communication and understanding from the body is therefore underlined, and the paper suggests a way forward drawing on linguistic theory and recent neurological findings. It is argued that the validation and promotion of skilled practice as âintelligentâ is necessary for raising the status and credibility of apprentice-style learning within our Western systems of education
Knowledge graphs evolution and preservation
One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is that of a: "Public FAIR Knowledge Graph of Everything: We increasingly see the creation of knowledge graphs that capture information about the entirety of a class of entities. [...] This grand challenge extends this further by asking if we can create a knowledge graph of "everything" ranging from common sense concepts to location based entities. This knowledge graph should be "open to the public" in a FAIR manner democratizing this mass amount of knowledge." Although linked open data (LOD) is one knowledge graph, it is the closest realisation (and probably the only one) to a public FAIR Knowledge Graph (KG) of everything. Surely, LOD provides a unique testbed for experimenting and evaluating research hypotheses on open and FAIR KG. One of the most neglected FAIR issues about KGs is their ongoing evolution and long term preservation. We want to investigate this problem, that is to understand what preserving and supporting the evolution of KGs means and how these problems can be addressed. Clearly, the problem can be approached from different perspectives and may require the development of different approaches, including new theories, ontologies, metrics, strategies, procedures, etc. This document reports a collaborative effort performed by 9 teams of students, each guided by a senior researcher as their mentor, attending the International Semantic Web Research School (ISWS 2019). Each team provides a different perspective to the problem of knowledge graph evolution substantiated by a set of research questions as the main subject of their investigation. In addition, they provide their working definition for KG preservation and evolution