A revised algorithm for latent semantic analysis

Xiangen Hu, Zhiqiang Cai, M Louwerse, Andrew Olney, P. Penumatsa, AC Graesser

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

18 Citations (Scopus)

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 be applied to other natural language understanding applications.
Original languageEnglish
Title of host publicationIJCAI'03 Proceedings of the 18th International Joint Conference on Artificial Intelligence
Place of PublicationSan Francisco
PublisherMorgan Kaufman Publishers
Pages1489-1491
Publication statusPublished - 2003
Externally publishedYes
Event18th International Joint Conference of Artificial Intelligence - Acapulco, Mexico
Duration: 9 Aug 200315 Aug 2003
Conference number: 18

Conference

Conference18th International Joint Conference of Artificial Intelligence
Abbreviated titleIJCAI'03
CountryMexico
CityAcapulco
Period9/08/0315/08/03

Fingerprint Dive into the research topics of 'A revised algorithm for latent semantic analysis'. Together they form a unique fingerprint.

Cite this