article

Sindice.com: a document-oriented lookup index for open linked data

Authors:

Michele Catasta,

Richard Cyganiak,

Holger Stenzhorn,

Giovanni TummarelloAuthors Info & Claims

International Journal of Metadata, Semantics and Ontologies, Volume 3, Issue 1

Pages 37 - 52

https://doi.org/10.1504/IJMSO.2008.021204

Published: 01 November 2008 Publication History

Abstract

Data discovery on the Semantic Web requires crawling and indexing of statements, in addition to the 'linked-data' approach of de-referencing resource URIs. Existing Semantic Web search engines are focused on database-like functionality, compromising on index size, query performance and live updates. We present Sindice, a lookup index over Semantic Web resources. Our index allows applications to automatically locate documents containing information about a given resource. In addition, we allow resource retrieval through inverse-functional properties, offer a full-text search and index SPARQL endpoints. Finally, we extend the sitemap protocol to efficiently index large datasets with minimal impact on data providers.

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Gidado AEzeife CAlhajj RAgarwal NMa ZRokne JAn JCharalampos CMagdy W(2022)Maximizing Bigdata Retrieval: Block as a Value for NoSQL over SQLProceedings of the 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.1109/ASONAM55673.2022.10068692(556-563)Online publication date: 10-Nov-2022
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Index Terms

Sindice.com: a document-oriented lookup index for open linked data
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Semantic networks
2. Information systems

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Published In

cover image International Journal of Metadata, Semantics and Ontologies

International Journal of Metadata, Semantics and Ontologies Volume 3, Issue 1

January 2008

91 pages

ISSN:1744-2621

EISSN:1744-263X

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Publisher

Inderscience Publishers

Geneva 15, Switzerland

Publication History

Published: 01 November 2008

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Cited By

Bizer CHeath TBerners-Lee T(2023)Linked Data - The Story So FarLinking the World’s Information10.1145/3591366.3591378(115-143)Online publication date: 5-Sep-2023
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Gidado AEzeife CAlhajj RAgarwal NMa ZRokne JAn JCharalampos CMagdy W(2022)Maximizing Bigdata Retrieval: Block as a Value for NoSQL over SQLProceedings of the 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.1109/ASONAM55673.2022.10068692(556-563)Online publication date: 10-Nov-2022
Azad HDeepak AAzad A(2022)LOD search engine: A semantic search over linked dataJournal of Intelligent Information Systems10.1007/s10844-021-00687-059:1(71-91)Online publication date: 1-Aug-2022
Dias LBarrére Ede Souza J(2021)The impact of semantic annotation techniques on content-based video lecture recommendationJournal of Information Science10.1177/016555152093173247:6(740-752)Online publication date: 1-Dec-2021
Hogan A(2020)The Semantic WebSemantic Web10.3233/SW-19038711:1(169-185)Online publication date: 1-Jan-2020
Polleres AKamdar MFernández JTudorache TMusen M(2020)A more decentralized vision for Linked DataSemantic Web10.3233/SW-19038011:1(101-113)Online publication date: 1-Jan-2020
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Mountantonakis MTzitzikas Y(2019)Large-scale Semantic Integration of Linked DataACM Computing Surveys10.1145/334555152:5(1-40)Online publication date: 13-Sep-2019
Menendez ECasanova MPaes Leme LBoughanem M(2019)Novel Node Importance Measures to Improve Keyword Search over RDF GraphsDatabase and Expert Systems Applications10.1007/978-3-030-27618-8_11(143-158)Online publication date: 26-Aug-2019
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