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Understanding Search Engines: Mathematical Modeling and Text Retrieval (Software, Environments, Tools), Second Edition

Michael W. Berry and Murray Browne (Author)
3.1 out of 5 stars  See all reviews (7 customer reviews)
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Editorial Reviews

Review

'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 'Berry and Browne describe most of what you need to know to design your own search engine. Their strength is the description of the solid mathematical underpinnings at a level that is understandable to competent engineering undergraduates, perhaps with a bit of instructor guidance. They discuss the algorithms used by most commercial search engines, so you may find your use of Google and its kind becomes more effective, too.' George Corliss, Marquette University. 'This book gives a valuable, generally non-technical, insight into how search engines work, how to improve the users' success in Information Retrieval (IR), and an in-depth analysis of a mathematical algorithm for improving a search engine's performance. ...Written in an informal style, the book is easy to read and is a good introduction on how search engines operate...' Christopher Dean, Mathematics Today 'Anyone interested in building their own search engine, or looking for a compact and readable introduction to the field of modern information retrieval will find this book to be an excellent first introduction.' Tony Donaldson, MAA Reviews

‘Anyone interested in building their own search engine, or looking for a compact and readable introduction to the field of modern information retrieval will find this book to be an excellent first introduction.’ Tony Donaldson, MAA Reviews

‘Berry and Browne describe most of what you need to know to design your own search engine. Their strength is the description of the solid mathematical underpinnings at a level that is understandable to competent engineering undergraduates, perhaps with a bit of instructor guidance. They discuss the algorithms used by most commercial search engines, so you may find your use of Google and its kind becomes more effective, too.’ George Corliss, Marquette University.

‘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

‘This book gives a valuable, generally non-technical, insight into how search engines work, how to improve the users' success in Information Retrieval (IR), and an in-depth analysis of a mathematical algorithm for improving a search engine's performance. …Written in an informal style, the book is easy to read and is a good introduction on how search engines operate…’ Christopher Dean, Mathematics Today

Product Description

“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. “Berry and Browne describe most of what you need to know to design your own search engine. Their strength is the description of the solid mathematical underpinnings at a level that is understandable to competent engineering undergraduates, perhaps with a bit of instructor guidance. They discuss the algorithms used by most commercial search engines, so you may find your use of Google and its kind becomes more effective, too.” --George Corliss, Marquette University. “This book gives a valuable, generally non-technical, insight into how search engines work, how to improve the users' success in Information Retrieval (IR), and an in-depth analysis of a mathematical algorithm for improving a search engine's performance. …Written in an informal style, the book is easy to read and is a good introduction on how search engines operate…” —Christopher Dean, Mathematics Today, October 1999. 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. Readers will find that the second edition includes significant changes that bring the text up to date on current information retrieval methods. For example, the authors have added a completely new chapter on link-structure algorithms used in search engines such as Google, and the chapter on user interface has been rewritten to specifically focus on search engine usability. To reflect updates in the literature on information retrieval, the authors have added new recommendations for further reading and expanded the bibliography. In addition, the index has been updated and streamlined to make it more reader friendly. Instructors will find that the book serves as an excellent companion text for courses in information retrieval, applied linear algebra, and scientific computing. Because of the authors’ informal, conversational tone, readers with nonmathematical backgrounds also will appreciate the less technical chapters of the text.
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Product Details

  • Paperback: 117 pages
  • Publisher: SIAM, Society for Industrial and Applied Mathematics; 2 edition (April 28, 2005)
  • Language: English
  • ISBN-10: 0898715814
  • ISBN-13: 978-0898715811
  • Product Dimensions: 8.9 x 5.8 x 0.3 inches
  • Shipping Weight: 5.6 ounces (View shipping rates and policies)
  • Average Customer Review: 3.1 out of 5 stars  See all reviews (7 customer reviews)
  • Amazon.com Sales Rank: #222,594 in Books (See Bestsellers in Books)

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Michael W. Berry
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Search Inside This Book:
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First Sentence:
We expect a lot from our search engines. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
item normalization, major commercial search engines, nonzero cosines, inversion list, vector space modeling, processing tokens, hub scores, document vectors, query vector, query matching, web graph, document matrix, relevance feedback, query terms, stop lists
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Bread Search, Child Proofing, Child Home Safety, Symbol Name Formula
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Customer Reviews

7 Reviews
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3.1 out of 5 stars (7 customer reviews)
 
 
 
 
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26 of 30 people found the following review helpful:
4.0 out of 5 stars Appreciations from a novice., June 29, 2000
By A Customer
This review is from: Understanding Search Engines: Mathematical Modeling and Text Retrieval (Software, Environments, Tools) (Paperback)
I read this book because I am starting academic research on search engines. It was one of my first books on the subject. It actually deals with two aspects: (1) relevant issues in search engine design, and (2) a mathematically sound approach in building and querying large index strucutres. The explanation in the book on both aspects is short but to the point and explained in an understandable way. It also contains a short list + description of some key references. Great !
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7 of 7 people found the following review helpful:
4.0 out of 5 stars Good Introduction, May 7, 2007
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There are better books in the market, and even the author would be the first to recognize it. However, this book is one of the most clear and readable introduction to the subject that you can find.

The author fully acomplishes the objective: teach his reader, at undergratuate level, how search engines work. Even some difficult subject, such as LSI, are treated at a level one can easilly understand.

One of the most important characteristics of the book is that it does math. Every formula has an example, usually using small matrix that allow the reader to easilly follow them.

The book is suitable for an objective introduction to the field. It is not very "academic", in the sense it is rather informal. If it is not a textbook, it could help some bewildered student to grasp the inner workings. It could also help a teacher to find clearer ways for explanations and good examples for classroom.

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1 of 1 people found the following review helpful:
5.0 out of 5 stars Linear Algebra, Numerical Linear Algebra, and Search Engine, January 19, 2009
By Man Kam Tam (Calexico, CA USA) - See all my reviews
(REAL NAME)   
Other than showing the readers how to design a search engine, the authors, Michael W. Berry and Murray Browne of "Understanding Search Engines: Mathematical Modeling, and Text Retrieval," intend to fill the gap between applied mathematics and information management. In a latent semantic index (LSI) system, mathematics plays a major role in search engine performance. The term-by-document matrix of the system would be transformed to a lower rank matrix for conceptual indexing. However, nobody knows how low the rank should be for the best performance. The best technique so far for lower rank approximation is called singular value decomposition. In such a system, vectors model both documents and queries. The angle between the document vector and the query vector determines the rank-order of the document. The elements of the vectors are usually the weighted frequency of the term occurrence. Thus the searchers should list as many terms as possible in their queries for better search results.

LSI search engine is good for small document system only. Other searching methods such as HITS and PageRank are introduced. For the readers who have the background on linear algebra, numerical linear algebra, and search engine should find this book interesting.

Generally speaking, the book is brief. It has 117 pages and 9 chapters. The nine chapters are Introduction, Document File Preparation, Vector Space Models, Matrix Decompositions, Query Management, Ranking and Relevance Feedback, Searching by Link Structure, User Interface Considerations, and Further Reading. Chapter two (Document File Preparation) reminds the readers that the documents of the system needed to be "clean-up" and index. The works may require plenty of manual labor.
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Most Recent Customer Reviews

2.0 out of 5 stars Understanding Search Engines
This book is condensed knowladge about the topic of search engines - but only the basics. I am very dissapointed because I thought I will see something special, inspiring... Read more
Published 12 months ago by Daniel Pawelec

2.0 out of 5 stars A mix of good and bad
As others have pointed out, this book is very short. As a consequence, it leaves out a lot of details and forces the reader to refer to another book. Read more
Published 12 months ago by Ray

4.0 out of 5 stars Good introduction
Good first (and short) book on the subject. Easy to follow and understand. Most suitable for reader who has some exposures to numerical analysis and/or numerical linear algebra... Read more
Published 15 months ago by Pat Choi

1.0 out of 5 stars Read at the bookstore, no need to buy
This little booklet is best to be read at the bookstore.

There is no need to buy. In fact, buying it is a waste
of money, given the $[money] price tag. Read more

Published on May 18, 2002

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