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Balakrishnan, U,; Soergel, D.; Helfer, O.: Representing concepts through description logic expressions for knowledge organization system (KOS) mapping (2020) 0.05

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Source: Knowledge Organization at the Interface. Proceedings of the Sixteenth International ISKO Conference, 2020 Aalborg, Denmark. Ed.: M. Lykke et al
Year: 2020

Rocha Souza, R.; Lemos, D.: a comparative analysis : Knowledge organization systems for the representation of multimedia resources on the Web (2020) 0.03

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Content: DOI:10.5771/0943-7444-2020-4-300.
Source: Knowledge organization. 47(2020) no.4, S.300-319
Year: 2020

Peponakis, M.; Mastora, A.; Kapidakis, S.; Doerr, M.: Expressiveness and machine processability of Knowledge Organization Systems (KOS) : an analysis of concepts and relations (2020) 0.02

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Source: International journal on digital libraries. 20(2020) no.4, S.433-452
Year: 2020

Wenige, L.; Ruhland, J.: Similarity-based knowledge graph queries for recommendation retrieval (2019) 0.01
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Abstract

Current retrieval and recommendation approaches rely on hard-wired data models. This hinders personalized cus-tomizations to meet information needs of users in a more flexible manner. Therefore, the paper investigates how similarity-basedretrieval strategies can be combined with graph queries to enable users or system providers to explore repositories in the LinkedOpen Data (LOD) cloud more thoroughly. For this purpose, we developed novel content-based recommendation approaches.They rely on concept annotations of Simple Knowledge Organization System (SKOS) vocabularies and a SPARQL-based querylanguage that facilitates advanced and personalized requests for openly available knowledge graphs. We have comprehensivelyevaluated the novel search strategies in several test cases and example application domains (i.e., travel search and multimediaretrieval). The results of the web-based online experiments showed that our approaches increase the recall and diversity of rec-ommendations or at least provide a competitive alternative strategy of resource access when conventional methods do not providehelpful suggestions. The findings may be of use for Linked Data-enabled recommender systems (LDRS) as well as for semanticsearch engines that can consume LOD resources. (PDF) Similarity-based knowledge graph queries for recommendation retrieval. Available from: https://www.researchgate.net/publication/333358714_Similarity-based_knowledge_graph_queries_for_recommendation_retrieval [accessed May 21 2020].

Bittner, T.; Donnelly, M.; Winter, S.: Ontology and semantic interoperability (2006) 0.01

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Date: 3.12.2016 18:39:22

Dobrev, P.; Kalaydjiev, O.; Angelova, G.: From conceptual structures to semantic interoperability of content (2007) 0.01

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Source: Conceptual structures: knowledge architectures for smart applications: 15th International Conference on Conceptual Structures, ICCS 2007, Sheffield, UK, July 22 - 27, 2007 ; proceedings. Eds.: U. Priss u.a

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