RDFsim: Similarity-Based Browsing over DBpedia Using Embeddings

Browsing has been the core access method for the Web from its beginning. Analogously, one good practice for publishing data on the Web is to support dereferenceable URIs, to also enable plain web browsing by users. The information about one URI is usually presented through HTML tables (such as DBped...

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Autores principales:	Manos Chatzakis, Michalis Mountantonakis, Yannis Tzitzikas
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	similarity browsing Semantic Web DBpedia entities embeddings Information technology T58.5-58.64
Acceso en línea:	https://doaj.org/article/9241cea8b7354747a1c8856d136afb6d
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spelling	oai:doaj.org-article:9241cea8b7354747a1c8856d136afb6d2021-11-25T17:58:24ZRDFsim: Similarity-Based Browsing over DBpedia Using Embeddings10.3390/info121104402078-2489https://doaj.org/article/9241cea8b7354747a1c8856d136afb6d2021-10-01T00:00:00Zhttps://www.mdpi.com/2078-2489/12/11/440https://doaj.org/toc/2078-2489Browsing has been the core access method for the Web from its beginning. Analogously, one good practice for publishing data on the Web is to support dereferenceable URIs, to also enable plain web browsing by users. The information about one URI is usually presented through HTML tables (such as DBpedia and Wikidata pages) and graph representations (by using tools such as LODLive and LODMilla). In most cases, for an entity, the user gets all triples that have that entity as subject or as object. However, sometimes the number of triples is numerous. To tackle this issue, and to reveal similarity (and thus facilitate browsing), in this article we introduce an interactive similarity-based browsing system, called RDFsim, that offers “Parallel Browsing”, that is, it enables the user to see and browse not only the original data of the entity in focus, but also the K most similar entities of the focal entity. The similarity of entities is founded on knowledge graph embeddings; however, the indexes that we introduce for enabling real-time interaction do not depend on the particular method for computing similarity. We detail an implementation of the approach over specific subsets of DBpedia (movies, philosophers and others) and we showcase the benefits of the approach. Finally, we report detailed performance results and we describe several use cases of RDFsim.Manos ChatzakisMichalis MountantonakisYannis TzitzikasMDPI AGarticlesimilaritybrowsingSemantic WebDBpediaentitiesembeddingsInformation technologyT58.5-58.64ENInformation, Vol 12, Iss 440, p 440 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	similarity browsing Semantic Web DBpedia entities embeddings Information technology T58.5-58.64
spellingShingle	similarity browsing Semantic Web DBpedia entities embeddings Information technology T58.5-58.64 Manos Chatzakis Michalis Mountantonakis Yannis Tzitzikas RDFsim: Similarity-Based Browsing over DBpedia Using Embeddings
description	Browsing has been the core access method for the Web from its beginning. Analogously, one good practice for publishing data on the Web is to support dereferenceable URIs, to also enable plain web browsing by users. The information about one URI is usually presented through HTML tables (such as DBpedia and Wikidata pages) and graph representations (by using tools such as LODLive and LODMilla). In most cases, for an entity, the user gets all triples that have that entity as subject or as object. However, sometimes the number of triples is numerous. To tackle this issue, and to reveal similarity (and thus facilitate browsing), in this article we introduce an interactive similarity-based browsing system, called RDFsim, that offers “Parallel Browsing”, that is, it enables the user to see and browse not only the original data of the entity in focus, but also the K most similar entities of the focal entity. The similarity of entities is founded on knowledge graph embeddings; however, the indexes that we introduce for enabling real-time interaction do not depend on the particular method for computing similarity. We detail an implementation of the approach over specific subsets of DBpedia (movies, philosophers and others) and we showcase the benefits of the approach. Finally, we report detailed performance results and we describe several use cases of RDFsim.
format	article
author	Manos Chatzakis Michalis Mountantonakis Yannis Tzitzikas
author_facet	Manos Chatzakis Michalis Mountantonakis Yannis Tzitzikas
author_sort	Manos Chatzakis
title	RDFsim: Similarity-Based Browsing over DBpedia Using Embeddings
title_short	RDFsim: Similarity-Based Browsing over DBpedia Using Embeddings
title_full	RDFsim: Similarity-Based Browsing over DBpedia Using Embeddings
title_fullStr	RDFsim: Similarity-Based Browsing over DBpedia Using Embeddings
title_full_unstemmed	RDFsim: Similarity-Based Browsing over DBpedia Using Embeddings
title_sort	rdfsim: similarity-based browsing over dbpedia using embeddings
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/9241cea8b7354747a1c8856d136afb6d
work_keys_str_mv	AT manoschatzakis rdfsimsimilaritybasedbrowsingoverdbpediausingembeddings AT michalismountantonakis rdfsimsimilaritybasedbrowsingoverdbpediausingembeddings AT yannistzitzikas rdfsimsimilaritybasedbrowsingoverdbpediausingembeddings
_version_	1718411816678195200

RDFsim: Similarity-Based Browsing over DBpedia Using Embeddings

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