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Method combination for information extraction

Published: 17 June 2010 Publication History

Abstract

The paper discuses information extraction especially entity identification approaches such as position-based, content/context-based and visual-based, their characteristics and disadvantages and proposes method combination. Benefits of each method for the others are described in second half. At the end using of extracted information for adaptation is slightly mentioned.

References

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Soderland S. Learning Information Extraction Rules for Semi-Structured and Free Text. Mach. Learn. Vol. 34, pages 233--272, 1999.
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Gatterbauer, W., Bohunsky P., Herzog M., Krüpl B., and Pollak B. Towards domain- independent information extraction from web tables. In WWW '07: Proceedings of the 16th international conference on World Wide Web, pages 71--80, New York, NY, USA, 2007. ACM.
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Bařinka, L. and Jelínek, I. 2009. Data extraction by visual matching. In Proceedings of the international Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing (Ruse, Bulgaria, June 18--19, 2009).
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Kravcik M. and Gasevic, D. (2007). Leveraging the Semantic Web for Adaptive Education. Journal of Interactive Media in Education (Adaptation and IMS Learning Design)
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Sarawagi S. Information Extraction. FnT Databases, 2008.
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Brusilovsky P., Maybury M. T., From adaptive hypermedia to the adaptive web. Commun. ACM, vol. 45, p. 30--33, 2002.

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CompSysTech '10: Proceedings of the 11th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing on International Conference on Computer Systems and Technologies
June 2010
575 pages
ISBN:9781450302432
DOI:10.1145/1839379
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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 June 2010

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Author Tags

  1. adaptive web
  2. information extraction
  3. semantic web

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CompSysTech '10

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Overall Acceptance Rate 241 of 492 submissions, 49%

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