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  LUKe and MIKe: Learning from User Knowledge and Managing Interactive Knowledge Extraction

Metzger, S., Stoll, M., Hose, K., & Schenkel, R. (2012). LUKe and MIKe: Learning from User Knowledge and Managing Interactive Knowledge Extraction. In X.-W. Chen, G. Lebanon, H. Wang, & M. J. Zaki (Eds.), CIKM'12 (pp. 2671-2673). New York, NY: ACM.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0014-5960-A Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0023-C142-D
Genre: Conference Paper
Latex : {LUKe} and {MIKe}: Learning from User Knowledge and Managing Interactive Knowledge Extraction

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 Creators:
Metzger, Steffen1, 2, Author           
Stoll, Michael3, Author
Hose, Katja1, Author           
Schenkel, Ralf1, Author           
Affiliations:
1Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              
2International Max Planck Research School, MPI for Informatics, Max Planck Society, ou_1116551              
3External Organizations, ou_persistent22              

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 Abstract: Semantic recognition and annotation of unqiue enities and their relations is a key in understanding the essence contained in large text corpora. It typically requires a combination of efficient automatic methods and manual verification. Usually, both parts are seen as consecutive steps. In this demo we present MIKE, a user interface enabling the integration of user feedback into an iterative extraction process. We show how an extraction system can directly learn from such integrated user supervision. In general, this setup allows for stepwise training of the extraction system to a particular domain, while using user feedback early in the iterative extraction process improves extraction quality and reduces the overall human effort needed.

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Language(s): eng - English
 Dates: 2012
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 647511
DOI: 10.1145/2396761.2398721
URI: http://doi.acm.org/10.1145/2396761.2398721
Other: Local-ID: C1256DBF005F876D-B1BE320040B32699C1257A5200325F1E-MetzgerSHS_CIKM2012
BibTex Citekey: MetzgerSHS_CIKM2012
 Degree: -

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Title: 21st ACM International Conference on Information and Knowledge Management
Place of Event: Maui, USA
Start-/End Date: 2012-10-29 - 2012-11-02

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Title: CIKM'12
  Subtitle : The Proceedings of the 21st ACM International Conference on Information and Knowledge Management
  Abbreviation : CIKM 2012
Source Genre: Proceedings
 Creator(s):
Chen, Xue-Wen1, Editor
Lebanon, Guy1, Editor
Wang, Haixun1, Editor
Zaki, Mohammed J.1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: New York, NY : ACM
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 2671 - 2673 Identifier: ISBN: 978-1-4503-1156-4