Understanding Search Engines
Mathematical Modeling and Text Retrieval
Series: Software, Environments and Tools; 17;
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Product details:
- Edition number 2, New edition
- Publisher Society for Industrial and Applied Mathematics
- Date of Publication 1 May 2005
- Number of Volumes Paperback
- ISBN 9780898715811
- Binding Paperback
- No. of pages184 pages
- Size 228x152x9 mm
- Weight 193 g
- Language English 0
Categories
Short description:
This text covers design issues for building search engines, emphasizing the role that applied mathematics plays in improving information retrieval.
MoreLong description:
The second edition of Understanding Search Engines: Mathematical Modeling and Text Retrieval follows the basic premise of the first edition by discussing many of the key design issues for building search engines and emphasizing the important role that applied mathematics can play in improving information retrieval. The authors discuss important data structures, algorithms, and software as well as user-centered issues such as interfaces, manual indexing, and document preparation. Significant changes bring the text up to date on current information retrieval methods: for example the addition of a new chapter on link-structure algorithms used in search engines such as Google. The chapter on user interface has been rewritten to specifically focus on search engine usability. In addition the authors have added new recommendations for further reading and expanded the bibliography, and have updated and streamlined the index to make it more reader friendly.
'There is no other information retrieval/search book where the heart is the mathematical foundations. This book is greatly needed to further establish information retrieval as a serious academic, as well as practical and industrial, area.' Jaime Carbonell, Carnegie Mellon University
Table of Contents:
Preface to the second edition; Preface to the first edition; 1. Introduction; 2. Document file preparation; 3. Vector space models; 4. Matrix decompositions; 5. Query management; 6. Ranking and relevance feedback; 7. Searching by link structure; 8. User interface considerations; 9. Further reading; Bibliography; Index.
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