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Getting Meaning into the Machine
May/June 2006 (vol. 21 no. 3)
pp. 70-71
| ASCII Text | x | ||
| Yorick Wilks, "Getting Meaning into the Machine," IEEE Intelligent Systems, vol. 21, no. 3, pp. 70-71, May/June, 2006. | |||
| BibTex | x | ||
| @article{ 10.1109/MIS.2006.48, author = {Yorick Wilks}, title = {Getting Meaning into the Machine}, journal ={IEEE Intelligent Systems}, volume = {21}, number = {3}, issn = {1541-1672}, year = {2006}, pages = {70-71}, doi = {http://doi.ieeecomputersociety.org/10.1109/MIS.2006.48}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - MGZN JO - IEEE Intelligent Systems TI - Getting Meaning into the Machine IS - 3 SN - 1541-1672 SP70 EP71 EPD - 70-71 A1 - Yorick Wilks, PY - 2006 KW - Semantic Web KW - artificial intelligence KW - machine translation KW - connectionism KW - machine learning KW - information extraction VL - 21 JA - IEEE Intelligent Systems ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MIS.2006.48
The key possibility the Semantic Web offers to traditional AI is delivering some of its value in a depleted form initially, by trading representational expressiveness for tractability, as some have put it. The model to follow here could be search technology and machine translation on the WWW (or even speech technology): each is available now in imperfect forms that we can't imagine living without.This article is part of a special issue on the Future of AI.
Index Terms:
Semantic Web, artificial intelligence, machine translation, connectionism, machine learning, information extraction
Citation:
Yorick Wilks, "Getting Meaning into the Machine," IEEE Intelligent Systems, vol. 21, no. 3, pp. 70-71, May-June 2006, doi:10.1109/MIS.2006.48
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