Article

Swoogle: a search and metadata engine for the semantic web

Authors:

Pavan Reddivari,

Joel SachsAuthors Info & Claims

CIKM '04: Proceedings of the thirteenth ACM international conference on Information and knowledge management

Pages 652 - 659

https://doi.org/10.1145/1031171.1031289

Published: 13 November 2004 Publication History

Abstract

Swoogle is a crawler-based indexing and retrieval system for the Semantic Web. It extracts metadata for each discovered document, and computes relations between documents. Discovered documents are also indexed by an information retrieval system which can use either character N-Gram or URIrefs as keywords to find relevant documents and to compute the similarity among a set of documents. One of the interesting properties we compute is <i>ontology rank</i>, a measure of the importance of a Semantic Web document.

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Cited By

Mahmoud AMohammed ZBen Ammar MSatty AAbdalla FKhamis GSalih MMohamed A(2025)Enhancing Semantic Search Precision through the CBOW Algorithm in the Semantic WebEngineering, Technology & Applied Science Research10.48084/etasr.945015:1(19522-19527)Online publication date: 2-Feb-2025
https://doi.org/10.48084/etasr.9450
Sharma SJain S(2024)The Semantics of COVID-19 Web Data: Ontology Learning and PopulationCurrent Materials Science10.2174/266614541666623011111353417:1(44-64)Online publication date: Mar-2024
https://doi.org/10.2174/2666145416666230111113534
Quintero RTorres-Ruiz MSaldaña-Pérez MGuzmán Sánchez-Mejorada CMata-Rivera F(2023)A Conceptual Graph-Based Method to Compute Information ContentMathematics10.3390/math1118397211:18(3972)Online publication date: 19-Sep-2023
https://doi.org/10.3390/math11183972
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Index Terms

Swoogle: a search and metadata engine for the semantic web
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing
    2. Retrieval models and ranking

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Information

Published In

cover image ACM Conferences

CIKM '04: Proceedings of the thirteenth ACM international conference on Information and knowledge management

November 2004

678 pages

ISBN:1581138741

DOI:10.1145/1031171

General Chair:
David Grossman
Illinois Institute of Technology
,
Program Chairs:
Luis Gravano
Columbia University
,
ChengXiang Zhai
University of Illinois at Urbana-Champaign
,
Otthein Herzog
University of Bremen, Germany
,
David A. Evans
Clairvoyance Corporation

Copyright © 2004 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 13 November 2004

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November 8 - 13, 2004

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

Mahmoud AMohammed ZBen Ammar MSatty AAbdalla FKhamis GSalih MMohamed A(2025)Enhancing Semantic Search Precision through the CBOW Algorithm in the Semantic WebEngineering, Technology & Applied Science Research10.48084/etasr.945015:1(19522-19527)Online publication date: 2-Feb-2025
https://doi.org/10.48084/etasr.9450
Sharma SJain S(2024)The Semantics of COVID-19 Web Data: Ontology Learning and PopulationCurrent Materials Science10.2174/266614541666623011111353417:1(44-64)Online publication date: Mar-2024
https://doi.org/10.2174/2666145416666230111113534
Quintero RTorres-Ruiz MSaldaña-Pérez MGuzmán Sánchez-Mejorada CMata-Rivera F(2023)A Conceptual Graph-Based Method to Compute Information ContentMathematics10.3390/math1118397211:18(3972)Online publication date: 19-Sep-2023
https://doi.org/10.3390/math11183972
Rogushina J(2023)A three-dimensional model of semantic search: queries, resources, and resultsPROBLEMS IN PROGRAMMING10.15407/pp2023.04.039(39-55)Online publication date: Dec-2023
https://doi.org/10.15407/pp2023.04.039
Niu CZhang WByna SChen Y(2023)PSQS: Parallel Semantic Querying Service for Self-describing File Formats2023 IEEE International Conference on Big Data (BigData)10.1109/BigData59044.2023.10386205(536-541)Online publication date: 15-Dec-2023
https://doi.org/10.1109/BigData59044.2023.10386205
Tran ATran TNhut NLong N(2023)Building a deep ontology-based herbal medicinal plant search systemInternational Journal of Information Technology10.1007/s41870-023-01250-615:4(2209-2223)Online publication date: 24-Apr-2023
https://doi.org/10.1007/s41870-023-01250-6
Jonquet CGraybeal JBouazzouni SDorf MFiore NKechagioglou XRedmond TRosati ISkrenchuk AVendetti JMusen M(2023)Ontology Repositories and Semantic Artefact Catalogues with the OntoPortal TechnologyThe Semantic Web – ISWC 202310.1007/978-3-031-47243-5_3(38-58)Online publication date: 27-Oct-2023
https://doi.org/10.1007/978-3-031-47243-5_3
Aghaei SAngele KHuaman EBushati GSchiestl MFensel A(2022)Interactive Search on the Web: The Story So FarInformation10.3390/info1307032413:7(324)Online publication date: 4-Jul-2022
https://doi.org/10.3390/info13070324
Portisch JHladik MPaulheim H(2022)Background knowledge in ontology matching: A surveySemantic Web10.3233/SW-223085(1-55)Online publication date: 8-Sep-2022
https://doi.org/10.3233/SW-223085
Mohamed HFathalla SLehmann JJabeen H(2022)Efficient computation of comprehensive statistical information of large OWL datasets: a scalable approachEnterprise Information Systems10.1080/17517575.2022.206268317:7Online publication date: 24-Apr-2022
https://doi.org/10.1080/17517575.2022.2062683
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