Towards a Quantitative, Platform-Independent Analysis of Knowledge Systems (2004) [12 citations — 4 self]
Download:
http://www.cs.utexas.edu/users/pclark/papers/kr04-
http://www.aifb.uni-karlsruhe.de/WBS/sst/Research/
http://www.cs.utexas.edu/users/mfkb/papers/kr04-br
DBLP
CACHED:
http://www.cs.utexas.edu/users/pclark/papers/kr04-
http://www.aifb.uni-karlsruhe.de/WBS/sst/Research/
http://www.cs.utexas.edu/users/mfkb/papers/kr04-br
DBLP
CACHED:
by
Noah S. Friedland
,
Paul G. Allen
,
Michael Witbrock
,
Gavin Matthews
,
Nancy Salay
,
Pierluigi Miraglia
,
Jurgen Angele
,
Steffen Staab
,
David Israel
,
Vinay Chaudhri
,
Bruce Porter
,
Ken Barker
,
Peter Clark
Proceedings of the Ninth International Conference on Principles of Knowledge Representation and Reasoning
Add To MetaCart
Popular Tags
No tags have been applied to this document.
BibTeX | Add To MetaCart
@INPROCEEDINGS{Friedland04towardsa,
author = {Noah S. Friedland and Paul G. Allen and Michael Witbrock and Gavin Matthews and Nancy Salay and Pierluigi Miraglia and Jurgen Angele and Steffen Staab and David Israel and Vinay Chaudhri and Bruce Porter and Ken Barker and Peter Clark},
title = {Towards a Quantitative, Platform-Independent Analysis of Knowledge Systems},
booktitle = {Proceedings of the Ninth International Conference on Principles of Knowledge Representation and Reasoning},
year = {2004},
pages = {507--515},
publisher = {AAAI Press}
}
author = {Noah S. Friedland and Paul G. Allen and Michael Witbrock and Gavin Matthews and Nancy Salay and Pierluigi Miraglia and Jurgen Angele and Steffen Staab and David Israel and Vinay Chaudhri and Bruce Porter and Ken Barker and Peter Clark},
title = {Towards a Quantitative, Platform-Independent Analysis of Knowledge Systems},
booktitle = {Proceedings of the Ninth International Conference on Principles of Knowledge Representation and Reasoning},
year = {2004},
pages = {507--515},
publisher = {AAAI Press}
}
Bookmarks
OpenURL
Abstract:
The Halo Pilot, a six-month effort to evaluate the state-ofthe -art in applied Knowledge Representation and Reasoning (KRR) systems, collaboratively developed a taxonomy of failures with the goal of creating a common framework of metrics against which we could measure inter- and intra- system failure characteristics of each of the three Halo knowledge applications. This platform independent taxonomy was designed with the intent of maximizing its coverage of potential failure types; providing the necessary granularity and precision to enable clear categorization of failure types; and providing a productive framework for short and longer term corrective action.
