Article

S-CREAM - Semi-automatic CREAtion of Metadata

Authors:

Siegfried Handschuh,

Fabio CiravegnaAuthors Info & Claims

EKAW '02: Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web

Pages 358 - 372

Published: 01 October 2002 Publication History

Abstract

Richly interlinked, machine-understandable data constitute the basis for the Semantic Web. We provide a framework, S-CREAM, that allows for creation of metadata and is trainable for a specific domain. Annotating web documents is one of the major techniques for creating metadata on the web. The implementation of S-CREAM, OntoMat-Annotizer supports now the semi-automatic annotation of web pages. This semi-automatic annotation is based on the information extraction component Amilcare. OntoMat-Annotizer extract with the help of Amilcare knowledge structure from web pages through the use of knowledge extraction rules. These rules are the result of a learning-cycle based on already annotated pages.

References

[1]

Fabio Ciravegna. Adaptive Information Extraction from Text by Rule Induction and Generalisation. In Proceedings of the 17th International Joint Conference on Artificial Intelligence (IJCAI)e, Seattle, Usa, August 2001.

[2]

Fabio Ciravegna. Challenges in Information Extraction from Text for Knowledge Management. IEEE Intelligent Systems and Their Applications, 16(6):88-90, 2001.

[3]

Fabio Ciravegna. (LP)², an Adaptive Algorithm for Information Extraction from Web-related Texts. In Proceedings of the IJCAI-2001 Workshop on Adaptive Text Extraction and Mining held in conjunction with 17th International Joint Conference on Artificial Intelligence (IJCAI), Seattle, Usa, August 2001.

[4]

Fabio Ciravegna and Daniela Petrelli. User Involvement in Adaptive Information Extraction: Position Paper. In Proceedings of the IJCAI-2001 Workshop on Adaptive Text Extraction and Mining held in conjunction with 17th International Joint Conference on Artificial Intelligence (IJCAI), Seattle, Usa, August 2001.

[5]

S. Decker, M. Erdmann, D. Fensel, and R. Studer. Ontobroker: Ontology Based Access to Distributed and Semi-Structured Information. In R. Meersman et al., editors, Database Semantics: Semantic Issues in Multimedia Systems, pages 351- 369. Kluwer Academic Publisher, 1999.

[6]

L. Denoue and L. Vignollet. An annotation tool for Web browsers and its applications to information retrieval. In In Proceedings of RIAO2000, Paris, April 2000. http://www.univ-savoie.fr/labos/syscom/Laurent.Denoue/riao2000.doc.

[7]

Aaron Douthat. The message understanding conference scoring software user's manual. In 7th Message Understanding Conference Proceedings, MUC-7, 1998. http://www.itl.nist.gov/iaui/894.02/related_projects/muc/.

[8]

M. Erdmann, A. Maedche, H.-P. Schnurr, and Steffen Staab. From Manual to Semi-automatic Semantic Annotation: About Ontology-based Text Annotation Tools. In P. Buitelaar & K. Hasida (eds). Proceedings of the COLING 2000 Workshop on Semantic Annotation and Intelligent Content, Luxembourg, August 2000.

[9]

H. Eriksson, R. Fergerson, Y. Shahar, and M. Musen. Automatic generation of ontology editors. In Proceedings of the 12th Banff Knowledge Acquisition Workshop, Banff, Alberta, Canada, 1999.

[10]

D. Fensel, J. Angele, S. Decker, M. Erdmann, H.-P. Schnurr, S. Staab, R. Studer, and Andreas Witt. On2broker: Semantic-based access to information sources at the WWW. In In Proceedings of the World Conference on the WWW and Internet (WebNet 99), Honolulu, Hawaii, USA, 1999.

[11]

Reference description of the DAML+OIL (March 2001) ontology markup language, March 2001. http://www.daml.org/2001/03/reference.html.

[12]

B. J. Grosz and C. L. Sidner. Attention, intentions, and the structure of discourse. Computational Linguistics, 12(3):175-204, 1986.

[13]

T. R. Gruber. A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition, 6(2):199-221, 1993.

[14]

S. Handschuh, S. Staab, and A. Maedche. CREAM -- Creating relational metadata with a component-based, ontology driven framework. In In Proceedings of K-Cap 2001, Victoria, BC, Canada, October 2001.

[15]

Siegfried Handschuh and Steffen Staab. Authoring and Annotation of Web Pages in CREAM. In Proceeding of the WWW2002 - Eleventh International World Wide Web Conferenceb (to appear), Hawaii, USA, May 2002.

[16]

J. Heflin and J. Hendler. Searching the Web with SHOE. In Artificial Intelligence for Web Search. Papers from the AAAI Workshop. WS-00-01, pages 35-40. AAAI Press, 2000.

[17]

J. Kahan, M. Koivunen, E. Prud'Hommeaux, and R. Swick. Annotea: An Open RDF Infrastructure for Shared Web Annotations. In Proc. of the WWW10 International Conference. Hong Kong, 2001.

[18]

Nicholas Kushmerick. Wrapper induction for information extraction. In Proceedings of the 15th International Joint Conference on Artificial Intelligence (IJCAI), 1997.

[19]

S. Luke, L. Spector, D. Rager, and J. Hendler. Ontology-based Web Agents. In Proceedings of First International Conference on Autonomous Agents, 1997.

[20]

P. Martin and P. Eklund. Embedding Knowledge in Web Documents. In Proceedings of the 8th Int. World Wide Web Conf. (WWW'8), Toronto, May 1999, pages 1403-1419. Elsevier Science B.V., 1999.

[21]

Diana Maynard, Valentin Tablan, Hamish Cunningham, Cristian Ursu, Horacio Saggion, Kalina Bontcheva, and Yorick Wilks. Architectural Elements of Language Engineering Robustness. Journal of Natural Language Engineering - Special Issue on Robust Methods in Analysis of Natural Language Data, 2002. forthcoming.

[22]

R.S. Mickalski, I. Mozetic, J. Hong, and H. Lavrack. The multi purpose incremental learning system AQ15 and its testing application to three medical domains. In Proceedings of the 5th National Conference on Artificial Intelligence, Philadelphia, USA, 1986.

[23]

M. Strube and U. Hahn. Functional Centering -- Grounding Referential Coherence in Information Structure. Computational Linguistics, 25(3):309-344, 1999.

[24]

M. Vargas-Vera, E. Motta, J. Domingue, S. Buckingham Shum, and M. Lanzoni. Knowledge Extraction by using an Ontology-based Annotation Tool. In K-CAP 2001 workshop on Knowledge Markup and Semantic Annotation, Victoria, BC, Canada, October 2001.

[25]

Ka-Ping Yee. CritLink: Better Hyperlinks for the WWW, 1998. http://crit.org/~ping/ht98.html.

Cited By

Xu ZMei LLiu YZhang HHu C(2015)Crowd sensing based semantic annotation of surveillance videosInternational Journal of Distributed Sensor Networks10.1155/2015/6793142015(61-61)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1155/2015/679314
Singhal ASrivastava JAkerkar RBassiliades NDavies JErmolayev V(2014)Generating Semantic Annotations For Research DatasetsProceedings of the 4th International Conference on Web Intelligence, Mining and Semantics (WIMS14)10.1145/2611040.2611056(1-11)Online publication date: 2-Jun-2014
https://dl.acm.org/doi/10.1145/2611040.2611056
Liu XGuo CZhang L(2014)Scholar metadata and knowledge generation with human and artificial intelligenceJournal of the Association for Information Science and Technology10.1002/asi.2301365:6(1187-1201)Online publication date: 1-Jun-2014
https://dl.acm.org/doi/10.1002/asi.23013
Show More Cited By

Index Terms

S-CREAM - Semi-automatic CREAtion of Metadata
1. Hardware
  1. Power and energy
    1. Power estimation and optimization
      1. Platform power issues

Index terms have been assigned to the content through auto-classification.

Recommendations

Automatic gazette creation for named entity recognition and application to resume processing
COMPUTE '12: Proceedings of the 5th ACM COMPUTE Conference: Intelligent & scalable system technologies

Named entities are important content-carrying units within documents. Consequently named entity recognition (NER) is an important part of information extraction. One fast and accurate approach to NER uses a list or gazette consisting of known instances. ...
Semi-automatic semantic annotation of PubMed queries

Information processing algorithms require significant amounts of annotated data for training and testing. The availability of such data is often hindered by the complexity and high cost of production. In this paper, we investigate the benefits of a ...
CREAM: creating relational metadata with a component-based, ontology-driven annotation framework
K-CAP '01: Proceedings of the 1st international conference on Knowledge capture

Richly interlinked, machine-understandable data constitutes the basis for the Semantic Web. Annotating web documents is one of the major techniques for creating metadata on the Web. However, annotation tools so far are restricted in their capabilities ...

Comments

Information & Contributors

Information

Published In

cover image Guide Proceedings

EKAW '02: Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web

October 2002

400 pages

ISBN:3540442685

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 October 2002

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

53
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 30 Aug 2024

Other Metrics

View Author Metrics

Citations

Cited By

Xu ZMei LLiu YZhang HHu C(2015)Crowd sensing based semantic annotation of surveillance videosInternational Journal of Distributed Sensor Networks10.1155/2015/6793142015(61-61)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1155/2015/679314
Singhal ASrivastava JAkerkar RBassiliades NDavies JErmolayev V(2014)Generating Semantic Annotations For Research DatasetsProceedings of the 4th International Conference on Web Intelligence, Mining and Semantics (WIMS14)10.1145/2611040.2611056(1-11)Online publication date: 2-Jun-2014
https://dl.acm.org/doi/10.1145/2611040.2611056
Liu XGuo CZhang L(2014)Scholar metadata and knowledge generation with human and artificial intelligenceJournal of the Association for Information Science and Technology10.1002/asi.2301365:6(1187-1201)Online publication date: 1-Jun-2014
https://dl.acm.org/doi/10.1002/asi.23013
Toledo CAle MChiotti OGalli M(2011)An Ontology-driven Document Retrieval Strategy for Organizational Knowledge Management SystemsElectronic Notes in Theoretical Computer Science (ENTCS)10.5555/2952802.2952988281:C(21-34)Online publication date: 29-Dec-2011
https://dl.acm.org/doi/10.5555/2952802.2952988
De Virgilio R(2011)RDFa based annotation of web pages through keyphrases extractionProceedings of the 2011th Confederated international conference on On the move to meaningful internet systems - Volume Part II10.5555/2075764.2075790(644-661)Online publication date: 17-Oct-2011
https://dl.acm.org/doi/10.5555/2075764.2075790
Fernández MCantador ILópez VVallet DCastells PMotta E(2011)Semantically enhanced Information RetrievalWeb Semantics: Science, Services and Agents on the World Wide Web10.1016/j.websem.2010.11.0039:4(434-452)Online publication date: 1-Dec-2011
https://dl.acm.org/doi/10.1016/j.websem.2010.11.003
Adrian BHees JHerman ISintek MDengel A(2010)EpiphanyProceedings of the 17th international conference on Knowledge engineering and management by the masses10.5555/1948294.1948313(178-192)Online publication date: 11-Oct-2010
https://dl.acm.org/doi/10.5555/1948294.1948313
Bikakis NGiannopoulos GDalamagas TSellis T(2010)Integrating keywords and semantics on document annotation and searchProceedings of the 2010 international conference on On the move to meaningful internet systems: Part II10.5555/1926129.1926157(921-938)Online publication date: 25-Oct-2010
https://dl.acm.org/doi/10.5555/1926129.1926157
Sosnovsky SDicheva D(2010)Ontological technologies for user modellingInternational Journal of Metadata, Semantics and Ontologies10.1504/IJMSO.2010.0326495:1(32-71)Online publication date: 1-Apr-2010
https://dl.acm.org/doi/10.1504/IJMSO.2010.032649
Yeh CChang CLin PWang YTsai Y(2010)Ontology-Based personal annotation management on semantic peer network to facilitating collaborationsProceedings of the 5th international conference on Advances in Grid and Pervasive Computing10.1007/978-3-642-13067-0_46(441-450)Online publication date: 10-May-2010
https://dl.acm.org/doi/10.1007/978-3-642-13067-0_46
Show More Cited By

View Options

View options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents