Corpus-Based Knowledge Representation
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence. Pages 1567-1571.
Abstract
A corpus-based knowledge representation system consists of a large collection of disparate knowledge fragments or schemas, and a rich set of statistics computed over the corpus. We argue that by collecting such a corpus and computing the appropriate statistics, corpus-based representation offers an alternative to traditional knowledge representation for a broad class of applications. The key advantage of corpusbased representation is that we avoid the laborious process of building a (often brittle) knowledge base. We describe the basic building blocks of a corpus-based representation system and a set of applications for which such a paradigm is appropriate, including one application where the approach is already showing promising results.
@inproceedings{ijcai2003p274,
title = {Corpus-Based Knowledge Representation},
author = {Levy, Alon Y. and Madhavan, Jayant},
booktitle = {Proceedings of the Eighteenth International Joint Conference on
Artificial Intelligence, {IJCAI-03}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Georg Gottlob},
pages = {1567--1571},
year = {2003},
url = {https://ijcai.org/proceedings/2003/274},
}
TY - CPAPER TI - Corpus-Based Knowledge Representation AU - Levy, Alon Y. AU - Madhavan, Jayant T2 - Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03 PB - International Joint Conferences on Artificial Intelligence PY - 2003 SP - 1567 EP - 1571 UR - https://ijcai.org/proceedings/2003/274 ER -Copied
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