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Overview

The Handbook of Latent Semantic Analysis is the authoritative reference for the theory behind Latent Semantic Analysis (LSA), a burgeoning mathematical method used to analyze how words make meaning, with the desired outcome to program machines to understand human commands via natural language rather than strict programming protocols. The first book

Product Details

ISBN-13: 9781135603274
Publisher: Taylor & Francis
Publication date: 02/15/2007
Series: University of Colorado Institute of Cognitive Science Series
Sold by: Barnes & Noble
Format: eBook
Pages: 544
File size: 10 MB

About the Author

Thomas K. Landauer, Danielle S. McNamara, Simon Dennis, Walter Kintsch

Table of Contents

Contents: Part I: Introduction to LSA: Theory and Methods. T.K. Landauer, LSA as a Theory of Meaning. D. Martin, M. Berry, Mathematical Foundations Behind Latent Semantic Analysis. S. Dennis, How to Use the LSA Website. J. Quesada, Creating Your Own LSA Spaces. Part II: LSA in Cognitive Theory. W. Kintsch , Meaning in Context. M. Louwerse, Symbolic or Embodied Representations: A Case for Symbol Interdependency. M.W. Howard, K. Addis, B. Jing, M.K. Kahana, Semantic Structure and Episodic Memory. G. DenhiŠre, B. Lemaire, C. Bellissens, S. Jhean-Larose, A Semantic Space for Modeling Children's Semantic Memory. P. Foltz, Discourse Coherence and LSA. J. Quesada, Spaces for Problem Solving. Part III: LSA in Educational Applications. K. Millis, J. Magliano, K. Wiemer-Hastings, S. Todaro, D.S. McNamara, Assessing and Improving Comprehension With Latent Semantic Analysis. D.S. McNamara, C. Boonthum, I. Levinstein, K. Millis, Evaluating Self-Explanations in iSTART: Comparing Word-Based and LSA Algorithms. A. Graesser, P. Penumatsa, M. Ventura, Z. Cai, X. Hu, Using LSA in AutoTutor: Learning Through Mixed-Initiative Dialog in Natural Language. E. Kintsch, D. Caccamise, M. Franzke, N. Johnson, S. Dooley, Summary Streetr: Computer-Guided Summary Writing. L. Streeter, K. Lochbaum, N. LaVoie, J.E. Psotka, Automated Tools for Collaborative Learning Environments. Part IV: Information Retrieval and HCI Applications of LSA. S.T. Dumais, LSA and Information Retrieval: Getting Back to Basics. P.K. Foltz, T.K. Landauer, Helping People Find and Learn From Documents: Exploiting Synergies Between Human and Computer Retrieval With SuperManual. M.H. Blackmon, M. Kitajima, D.R. Mandalia, P.G. Polson, Automating Usability Evaluation Cognitive Walkthrough for the Web Puts LSA to Work on Real-World HCI Design Problems. Part V: Extensions to LSA. D.S. McNamara, Z. Cai, M.M. Louwerse, Optimizing LSA Measures of Cohesion. X. Hu, Z. Cai, P. Wiemer-Hastings, A.C. Graesser, D.S. McNamara, Strength, Weakness, and Extensions of LSA. M. Steyvers, T. Griffiths, Probabilistic Topic Models. S. Dennis, Introducing Word Order: Within the LSA Framework. Part VI: Conclusion. W. Kintsch, D.S. McNamara, S. Dennis, T.K. Landauer, LSA and Meaning: In Theory and Application.
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