A Revised Algorithm for Latent Semantic Analysis
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence. Pages 1489-1490.
Abstract
The intelligent tutoring system AutoTutor uses latent semantic analysis to evaluate student answers to the tutor's questions. By comparing a student's answer to a set of expected answers, the system determines how much information is covered and how to continue the tutorial . Despite the success of LSA in tutoring conversations, the system sometimes has difficulties determining at an early stage whether or not an expectation is covered . A new LSA algorithm significantly improves the precision of AutoTutor's natural language understanding and can b e applied to other natural language understanding applications.
@inproceedings{ijcai2003p246,
title = {A Revised Algorithm for Latent Semantic Analysis},
author = {Hu, Xiangen and Cai, Zhiqiang and Louwerse, Max M. and Olney, Andrew and Penumatsa, Phanni and Graesser, Arthur C.},
booktitle = {Proceedings of the Eighteenth International Joint Conference on
Artificial Intelligence, {IJCAI-03}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Georg Gottlob},
pages = {1489--1490},
year = {2003},
url = {https://ijcai.org/proceedings/2003/246},
}
TY - CPAPER TI - A Revised Algorithm for Latent Semantic Analysis AU - Hu, Xiangen AU - Cai, Zhiqiang AU - Louwerse, Max M. AU - Olney, Andrew AU - Penumatsa, Phanni AU - Graesser, Arthur C. T2 - Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03 PB - International Joint Conferences on Artificial Intelligence PY - 2003 SP - 1489 EP - 1490 UR - https://ijcai.org/proceedings/2003/246 ER -Copied
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