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.

References

[1]

http://www.daml.org/ontologies/, daml ontology library, by daml.

[2]

http://www.schemaweb.info/, schema web.

[3]

http://www.semanticwebsearch.com/, semantic web search, by intellidimension.

[4]

http://www.semwebcentral.org/, semwebcentral, by infoether and bbn.

[5]

http://www.w3.org/2004/ontaria/, ontaria, by w3c.

[6]

F. Baader, D. Calvanese, D. McGuinness, D. Nardi, and P. Patel-Schneider. The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, 2003.

Digital Library

[7]

R. S. Cost, S. Kallurkar, H. Majithia, C. Nicholas, and Y. Shi. Integrating distributed information sources with carrot ii. In Proceedings of the 6th International Workshop on Cooperative Information Agents VI, pages 194--201. Springer-Verlag, 2002.

Digital Library

[8]

J. Davies, R. Weeks, and U. Krohn. Quizrdf: search technology for thesemantic web. In WWW2002 workshop on RDF and Semantic Web Applications, 11th International WWW Conference (WWW11), 2002.

[9]

S. Decker, M. Erdmann, D. Fensel, and R. Studer. Ontobroker: Ontology based access to distributed and semi-structured information. In DS-8, pages 351--369, 1999.

Digital Library

[10]

T. Finin, J. Mayfield, C. Fink, A. Joshi, and R. S. Cost. Information retrieval and the semantic web, January 2004.

[11]

S. Handschuh and S. Staab. Cream: Creating metadata for the semantic web. Comput. Networks, 42(5):579--598, 2003.

Digital Library

[12]

T. Haveliwala. Efficient computation of pageRank. Technical Report 1999-31, 1999.

[13]

I. Horrocks. DAML+OIL: A description logic for the semantic web. IEEE Data Engineering Bulletin, 25(1):4--9, 2002.

Digital Library

[14]

M. Lifantsev. Rank computation methods for Web documents. Technical Report TR-76, ECSL, Department of Computer Science, SUNY at Stony Brook, Stony Brook, NY, November 1999.

[15]

S. Luke, L. Spector, D. Rager, and J. Hendler. Ontology-based web agents. In Proceedings of the First International Conference on Autonomous Agents (Agents97), pages 59--66, 1997.

Digital Library

[16]

P. Martin and P. Eklund. Embedding knowledge in web documents. In Proceedings of the 8th International World Wide Web Conference (WWW8), pages 324--341, 1999.

Digital Library

[17]

J. Mayfield and T. Finin. Information retrieval on the semantic web: Integrating inference and retrieval. In Proceedings of the SIGIR 2003 Semantic Web Workshop, 2003.

[18]

L. Page, S. Brin, R. Motwani, and T. Winograd. The pagerank citation ranking: Bringing order to the web. Technical report, Stanford Digital Library Technologies Project, 1998.

[19]

I. Rogers. The google pagerank algorithm and how it works. http://www.iprcom.com/papers/pagerank/, May 2002.

[20]

U. Shah, T. Finin, and A. Joshi. Information retrieval on the semantic web. In Proceedings of the 11th international conference on Information and knowledge management, pages 461--468, 2002.

Digital Library

Cited By

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
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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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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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CIKM04: Conference on Information and Knowledge Management

November 8 - 13, 2004

D.C., Washington, USA

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Cited By

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
ZHAO LWANG JWANG CGUO M(2022)A Cross‐Domain Ontology Semantic Representation Based on NCBI‐BlueBERT EmbeddingChinese Journal of Electronics10.1049/cje.2020.00.32631:5(860-869)Online publication date: Sep-2022
https://doi.org/10.1049/cje.2020.00.326
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