# Document (#13237)

Editor
Berry, M.W.
Title
Computational information retrieval
Source
Workshop held in October 2000 in Raleigh, North Carolina
Imprint
Year
2001
Pages
XII,185 S
Isbn
0-89871-500-8
Abstract
This volume contains selected papers that focus on the use of linear algebra, computational statistics, and computer science in the development of algorithms and software systems for text retrieval. Experts in information modeling and retrieval share their perspectives on the design of scalable but precise text retrieval systems, revealing many of the challenges and obstacles that mathematical and statistical models must overcome to be viable for automated text processing. This very useful proceedings is an excellent companion for courses in information retrieval, applied linear algebra, and applied statistics. Computational Information Retrieval provides background material on vector space models for text retrieval that applied mathematicians, statisticians, and computer scientists may not be familiar with. For graduate students in these areas, several research questions in information modeling are exposed. In addition, several case studies concerning the efficacy of the popular Latent Semantic Analysis (or Indexing) approach are provided.
Theme
Retrievalalgorithmen
Object
Latent Semantic Indexing

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4. Mather, L.A.: ¬A linear algebra measure of cluster quality (2000) 0.18
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5. Wang, Y.; Lee, J.-S.; Choi, I.-C.: Indexing by Latent Dirichlet Allocation and an Ensemble Model (2016) 0.17
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