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Handbook of Latent Semantic Analysis (University of Colorado Institute of Cognitive Science Series)From Psychology Press
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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 of its kind to deliver such a comprehensive analysis, this volume explores every area of the method and combines theoretical implications as well as practical matters of LSA.
Readers are introduced to a powerful new way of understanding language phenomena, as well as innovative ways to perform tasks that depend on language or other complex systems. The Handbook clarifies misunderstandings and pre-formed objections to LSA, and provides examples of exciting new educational technologies made possible by LSA and similar techniques. It raises issues in philosophy, artificial intelligence, and linguistics, while describing how LSA has underwritten a range of educational technologies and information systems. Alternate approaches to language understanding are addressed and compared to LSA.�
This work is essential reading for anyone―newcomers to this area and experts alike―interested in how human language works or interested in computational analysis and uses of text. Educational technologists, cognitive scientists, philosophers, and information technologists in particular will consider this volume especially useful.
- Sales Rank: #1872820 in Books
- Published on: 2014-06-11
- Released on: 2014-06-10
- Original language: English
- Dimensions: 9.02" h x 1.23" w x 5.98" l, 1.64 pounds
- Binding: Paperback
- 544 pages
About the Author
Thomas K. Landauer has been elected into the CHI Academy by The Association for Computing Machinery's Special Interest Group on Computer-Human Interaction (ACM SIGCHI) in recognition of his outstanding leadership and service in the field of computer-human interaction.
Most helpful customer reviews
5 of 5 people found the following review helpful.
Roots of Latent Semantic Analysis
By John M. Ford
"Latent semantic analysis (LSA) is a theory and method for extracting and representing the meaning of words. Meaning is estimated using statistical computations applied to a large corpus of text." This book's editors launched wide interest in LSA and its applications in psychology and education. They have assembled twenty-three chapters from others who have used and improved this technique. These chapters are intended to dispel misconceptions about LSA and make it available to a wider audience.
The chapters are grouped into six sections. In the first two, readers learn about the theoretical and mathematical underpinnings of LSA and how it has been used to model psychological processes. The next two sections describe applications of LSA in education and information retrieval. Chapters in the fifth section look ahead, exploring how LSA techniques can be extended to use word order and other sources of information. In a final single-chapter section, the editors describe their vision for future development of LSA.
Three particularly useful chapters are:
Thomas Landauer's "LSA as a Theory of Meaning" is a readably-brief overview of how LSA extracts meaning from text, what limitations it has, and how its models should be interpreted. Those with no prior LSA exposure need to read it.
Simon Dennis's "How to Use the LSA Web Site" enables readers to explore applications of LSA without building their own semantic spaces. The referenced web site contains demonstrations that allow users to explore the similarity of different samples of text using LSA algorithms.
Jose Quesada's "Creating Your Own LSA Spaces" takes the next step in empowering readers to use LSA. It outlines how to create a semantic space based on a new text sample that may better match their purposes than those on the LSA web site.
The book is a good introduction to the fundamentals and historical origins of LSA. Readers interested in more current treatments will find them in information retrieval journals and in recent papers on chapter authors' web sites. Those wishing to experiment with LSA might find the R statistics package useful, along with several of its LSA-related external modules. This software is free under an open source license. Happy modeling!
0 of 0 people found the following review helpful.
Five Stars
By Alejandro Romero
excelent for LSA starters...
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