Search (5 results, page 1 of 1)

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Abstract

This paper describes an approach to SKOS vocabulary mapping that takes into account the context in which vocabulary terms are used in annotations. The standard vocabulary mapping properties in SKOS only allow for binary mappings between concepts. In the BestMap ontology, annotated resources are the contexts in which annotations coincide and allow for a more fine grained control over when mappings hold. A mapping between two vocabularies is defined as a class that groups descriptions of a resource. We use the OWL 2 features for property chains, disjoint properties, union, intersection and negation together with careful use of equivalence and subsumption to specify these mappings.

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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].

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Date

29. 1.2011 18:45:23

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Date

29. 7.2011 14:44:56

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Date

3.12.2016 18:39:22