A CLP-Based, Diagnosticity-Driven System for Concept Combinations
Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 1585-1585.
Abstract
Diagnosticity operates as an important selection criterion for several computational models of concept combination. Unfortunately, it has not been clear how the diagnosticity of property and relational predicates of the concepts combined can be formalized and quantified. Using an information retrieval method we compute, in a uniform manner, diagnosticity values of concepts predicates. We go on to present a reasoning system that attempts to create meaningful interpretations of novel nounnoun combinations. The system is based solely on diagnostic predicates values and a set of constraint satisfaction rules. We show the effectiveness and plausibility of our methods and discuss their potential.
@inproceedings{ijcai2005p335,
title = {A CLP-Based, Diagnosticity-Driven System for Concept Combinations},
author = {Tagalakis, Georgios and Ferrari, Daniela and Keane, Mark T.},
booktitle = {Proceedings of the Nineteenth International Joint Conference on
Artificial Intelligence, {IJCAI-05}},
publisher = {International Joint Conferences on Artificial Intelligence},
pages = {1585--1585},
year = {2005},
url = {https://ijcai.org/proceedings/2005/335},
}
TY - CPAPER TI - A CLP-Based, Diagnosticity-Driven System for Concept Combinations AU - Tagalakis, Georgios AU - Ferrari, Daniela AU - Keane, Mark T. T2 - Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05 PB - International Joint Conferences on Artificial Intelligence PY - 2005 SP - 1585 EP - 1585 UR - https://ijcai.org/proceedings/2005/335 ER -Copied
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