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Open source search: a data mining platform
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Volume 39 ,  Issue 1  (June 2005) table of contents
COLUMN: ICDM invited presentation table of contents
Pages: 4 - 10  
Year of Publication: 2005
ISSN:0163-5840
Author
Wray Buntine  University of Helsinki & Helsinki University of Technology, HUT, Finland
Publisher
ACM  New York, NY, USA
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ABSTRACT

Commercial search engines provide a quality service at no cost to consumers thanks to embedded targeted marketing. Despite this, I argue there are still reasons why an open source effort should be encouraged in the community: as part of broader open publishing initiatives, to allow quality subject specific search engines to develop, and "because we can," because search is one of the great grand challenge problems and we, the research community, cannot join in without an accessible, non-proprietary system. This talk outlines arguments and discusses some of the new technology that could go into such a system, as well as the infrastructure that would be required to make it work.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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K. Aberer, F. Klemm, M. Rajman, and J. Wu. An architecture for peer-to-peer information retrieval. In SIGIR workshop on Peer-to-Peer Information Retrieval, 2004.
 
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O. Drori. How to display search results in digital libraries-user study. In NDDL 2003, pages 13--28, 2003.
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A. K. McCallum. Mallet: A machine learning for language toolkit. http://mallet.cs.umass.edu, 2002.
 
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C. Nedellec. Ontologies and information extraction. In S. Staab and R. Studer, editors, Handbook on Ontologies in Information Systems. Springer Verlag, 2004.
 
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W. Nejdl. How to build Google2Google - an (incomplete) recipe. In International Semantic Web Conference, pages 1--5, 2004.