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AI and Global Science and Technology Assessment

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1 Author(s)
Hsinchun Chen ; Univ. of Arizona, Tucson, AR, USA

Addressing the research opportunities we've identified could substantially broaden the spectrum of multilingual text-mining and its practicality for supporting global S&T knowledge management. These opportunities also share a common set of challenges that deserve further attention. For example, competitive intelligence surveillance, which allows organizations to understand their current and potential competitors better, often requires the extraction of names of different organizations, technologies, or products from various S&T documents. When dealing with multilingual documents, adequate cross-lingual entity-resolution mechanisms are essential for effective global S&T analysis. Furthermore, some S&T documents are scientific or technologically oriented, whereas others have a predominantly business orientation. This increases the chance of different documents using different terms inreferring to identical or similar concepts. Establishing cross-domain interoperability is essential, especially in multilingual environments.

Published in:

Intelligent Systems, IEEE  (Volume:24 ,  Issue: 4 )

Date of Publication:

July-Aug. 2009

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