---
title: "A Revised Algorithm for Latent Semantic Analysis"
authors:
  - "Xiangen Hu"
  - "Zhiqiang Cai"
  - "Max M. Louwerse"
  - "Andrew Olney"
  - "Phanni Penumatsa"
  - "Arthur C. Graesser"
doi: ""
url: "https://ijcai.org/proceedings/2003/246"
pdf: "https://ijcai.org/proceedings/2003/0246.pdf"
venue: "Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence"
year: 2003
pages: "1489-1490"
track: ""
keywords:
---

# A Revised Algorithm for Latent Semantic Analysis

Xiangen Hu, Zhiqiang Cai, Max M. Louwerse, Andrew Olney, Phanni Penumatsa, Arthur C. Graesser

*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.