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HLIE08 2008 : Workshop on High-level Information Extraction ECML PKDD 2008

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Link: http://www-ai.cs.tu-dortmund.de/HLIE08/index.html
 
When Sep 19, 2008 - Sep 19, 2008
Where Antwerp, Belgium
Submission Deadline Jun 30, 2008
Notification Due Jul 16, 2008
Categories    NLP   machine learning   data mining   information retrieval
 

Call For Papers

The ECML-08 Workshop on High-level Information Extraction will be held in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases that will take place September 15 to 19, 2008, in Antwerp, Belgium.

+++ Deadline extended to June 30.

Information extraction (IE) techniques aim to extract informations from data sources. IE methods versatilely address naturally arising learning tasks where the data is generally structured, highly correlated, and frequently preserve multiple-way dependencies within and between recurrent structures. By now, "low-level" tasks such as named entity recognition are well understood, however, solving complex IE tasks -- like relation and event-extraction -- remains a challenge.

In the last years, significant contributions to high-level IE in relevant fields led to applications that have matured to a point beyond proof of concept. However, which strategy (e.g., pipeline, structured, or hybrid) is beneficial for which problems is not yet well understood, neither from the theoretical nor the practical point of view.

We aim at bringing together an interdisciplinary group of researchers who are working on high-level information extraction. The goal of this workshop will be to structure and explore the state of the art, to evolve high-level IE models with regard to real-world applications, and to identify future challenges and applications. We intend to cover a broad range of methods, including pipelined/hybrid approaches and structured prediction models; in particular we are interested in the following topics:

# Algorithms:
What are the differences between pipelined and structured methods? Are there hybrid methods, using the best of the two worlds? Are there novel algorithms and techniques for solving high-level IE or subproblems thereof?

# Theoretical results:
Are there convergence/generalization bounds for high-level IE techniques? Is there a characterization of problems for which a direct solution always exists? How can high-level IE methods be evaluated?

# Pre- and post-processing techniques:
Which high-level IE applications benefit from pre-/post-processing? Can pre-/post-processing be harmful? Are these techniques independent of the underlying IE methods? How can pre- and post-processing techniques be evaluated?

# Applications:
What are novel applications involving high-level IE? Are there equivalent problems in related areas that can be solved with existing methods?

For further details and topics of interest, please refer to the website of the workshop.


ORGANIZATION

* Sebastian Blohm (University of Karlsruhe)
* Ulf Brefeld (TU Berlin)
* Felix Jungermann (University of Dortmund)
* Roman Yangarber (University of Helsinki)


FURTHER INFORMATION

* Workshop web page: http://www-ai.cs.tu-dortmund.de/HLIE08/index.html
* Conference web page: http://www.ecmlpkdd2008.org/

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