scholarly journals Ontology Alignment Using Web Linked Ontologies as Background Knowledge

2016 ◽  
pp. 207-227 ◽  
Author(s):  
Thomas Hecht ◽  
Patrice Buche ◽  
Juliette Dibie ◽  
Liliana Ibanescu ◽  
Cassia Trojahn dos Santos
Keyword(s):  
Background Knowledge ◽  
Ontology Alignment

scholarly journals Multimatcher Model to Enhance Ontology Matching Using Background Knowledge

Information ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 487
Author(s):  
Sohaib Al-Yadumi ◽  
Wei-Wei Goh ◽  
Ee-Xion Tan ◽  
Noor Zaman Jhanjhi ◽  
Patrice Boursier
Keyword(s):  
State Of The Art ◽  
Model Performance ◽  
Background Knowledge ◽  
Ontology Matching ◽  
Semantic Heterogeneity ◽  
Ontology Alignment ◽  
Selection Algorithm ◽  
Confidence Measure ◽  
Proposed Model ◽  
Ontology Alignment Evaluation Initiative

Ontology matching is a rapidly emerging topic crucial for semantic web effort, data integration, and interoperability. Semantic heterogeneity is one of the most challenging aspects of ontology matching. Consequently, background knowledge (BK) resources are utilized to bridge the semantic gap between the ontologies. Generic BK approaches use a single matcher to discover correspondences between entities from different ontologies. However, the Ontology Alignment Evaluation Initiative (OAEI) results show that not all matchers identify the same correct mappings. Moreover, none of the matchers can obtain good results across all matching tasks. This study proposes a novel BK multimatcher approach for improving ontology matching by effectively generating and combining mappings from biomedical ontologies. Aggregation strategies to create more effective mappings are discussed. Then, a matcher path confidence measure that helps select the most promising paths using the final mapping selection algorithm is proposed. The proposed model performance is tested using the Anatomy and Large Biomed tracks offered by the OAEI 2020. Results show that higher recall levels have been obtained. Moreover, the F-measure values achieved with our model are comparable with those obtained by the state of the art matchers.

FUZZY ONTOLOGY ALIGNMENT USING BACKGROUND KNOWLEDGE

2014 ◽  
Vol 22 (01) ◽  
pp. 75-112 ◽  
Author(s):  
KONSTANTIN TODOROV ◽  
CELINE HUDELOT ◽  
ADRIAN POPESCU ◽  
PETER GEIBEL
Keyword(s):  
Ground Truth ◽  
Background Knowledge ◽  
General Purpose ◽  
Ontology Alignment ◽  
Human Judgment ◽  
Fuzzy Ontology ◽  
Matching Process ◽  
Cross Language ◽  
Domain Concept ◽  
Core Features

We propose an ontology alignment framework with two core features: the use of background knowledge and the ability to handle vagueness in the matching process and the resulting concept alignments. The procedure is based on the use of a generic reference vocabulary, which is used for fuzzifying the ontologies to be matched. The choice of this vocabulary is problem-dependent in general, although Wikipedia represents a general-purpose source of knowledge that can be used in many cases, and even allows cross language matchings. In the first step of our approach, each domain concept is represented as a fuzzy set of reference concepts. In the next step, the fuzzified domain concepts are matched to one another, resulting in fuzzy descriptions of the matches of the original concepts. Based on these concept matches, we propose an algorithm that produces a merged fuzzy ontology that captures what is common to the source ontologies. The paper describes experiments in the domain of multimedia by using ontologies containing tagged images, as well as an evaluation of the approach in an information retrieval setting. The undertaken fuzzy approach has been compared to a classical crisp alignment by the help of a ground truth that was created based on human judgment.

Feature distribution and background knowledge in category learning

2000 ◽  
Vol 53 (4) ◽  
pp. 962-982 ◽  
Author(s):  
Gregory L. Murphy ◽  
Audrey S. Kaplan
Keyword(s):  
Category Learning ◽  
Background Knowledge

LEXICAL MEANS OF EXPRESSING EVALUATION IN MODERN GERMAN JOURNALISTIC TEXTS

2020 ◽  
Author(s):  
Ирина Владимировна Матвеева ◽  
Сергей Николаевич Саможенов ◽  
Юлия Николаевна Зинцова
Keyword(s):  
Background Knowledge ◽  
Evaluation Tools ◽  
Language Competence

Авторы публицистических текстов все чаще отходят от стандартизации речи и клишированности в пользу поиска новых экспрессивных средств выражения оценочности, которые требуют от читателя определенного количества фоновых знаний и разработанной языковой компетенции. В данной статье установлены лексические особенности использования оценочных средств в немецких публицистических текстах, выявлены их разновидности и сферы употребления. Authors of journalistic texts are increasingly moving away from the standardization of speech and cliché in favor of searching for new expressive means of expressing evaluation, which require the reader to have a certain amount of background knowledge and developed language competence. In this article, the lexical features of the use of evaluation tools in German journalistic texts are established, their varieties and areas of use are identified.

scholarly journals Being a Patient Representative Is More Work Than Being a Patient Advocate—Done Right, It Is Also Likely to Be More Effective

2021 ◽  
Vol 28 (2) ◽  
pp. 1017-1019
Author(s):  
Richard Wassersug
Keyword(s):  
Health Outcomes ◽  
Background Knowledge ◽  
Positive Influence ◽  
Patient Advocate ◽  
Different Types ◽  
Health Related ◽  
Patient Representative

For a patient to be effective as a “patient representative” within a health-related organization, work and more than just accepting an honorific title is required. I argue that for a patient to be most effective as a patient representative requires different types of background knowledge and commitment than being a “patient advocate”. Patients need to be cautious about how, when, and where they take on an official role of either an “advocate” or “representative”, if they truly want to be a positive influence on health outcomes.

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