understanding search engines mathematical modeling and text retrieval

[...]... consider skimming or skipping Chapters 3 and 4 and Sections 7.1 and 7.2 However, we encourage those with applied mathematics or computer science backgrounds to read the less technical Chapters 1, 2, 5, and 8 because the exposure to the information science perspective of search engines is critical for both assessing performance and understanding how users see search engines In Chapter 9, we list background... experienced searcher Those trained in searching are often taught Boolean searching methods (especially in library and information sciences), i.e., the connection of search terms by AND and OR For example, if a Boolean searcher queries a CDROM encyclopedia on German shepherds and bloodhounds, the documents 8 Chapter 1 Introduction retrieved must have information about both German shepherds and bloodhounds... (1997) Information Retrieval Systems: Theory and Implementation, a broad overview XI xii Preface to the Second Edition of information retrieval systems, and Ricardo Baeza-Yates and Berthier Ribeiro-Neto's (1999) Modern Information Retrieval, a computer-science perspective of information retrieval, are all fine textbooks on the topic, but understandably they lack the gritty details of the mathematical computations... specializing in retrieval systems, the impact of certain decisions that are made at various junctures of this development One of the major decisions in developing information retrieval systems is selecting and implementing the computational approaches within an integrated software environment Applied mathematics plays a major role in search engine performance, and Understanding Search Engines (or USE)... the major decisions in developing information retrieval systems is selecting and implementing the computational approaches within an integrated software environment Applied mathematics plays a major role in search engine performance, and Understanding Search Engines (or USE] focuses on this area, bridging the gap between the fields of applied mathematics and information management, disciplines that... searchable tokens by addressing such areas as processing tokens and stemming Once these prerequisites are met, the documents are ready to be indexed 1.3 Vector Space Modeling SMART (system for the mechanical analysis and retrieval of text) , developed by Gerald Salton and his colleagues at Cornell University [73], was one of the first examples of a vector space IR model In such a model, both terms and/ or... information retrieval systems, are fine textbooks on the topic, but both understandably lack the gritty details of the mathematical computations needed to build more successful search engines With this in mind, USE does not provide an overview of information retrieval systems but prefers to assume a supplementary role to the aforementioned books Many of the ideas for USE were first presented and developed... marking 4 Chapter 1 Introduction where each document begins and ends, and handling parts of the documents that are not text (such as images), then most search engines will respond by returning the wrong document(s) or fragments of documents One misconception is that information that has been formatted through an hypertext markup language (HTML) editor and displayed in a browser is sufficiently formatted,... organized and displayed Obviously, hypertext documents are more than just text Any search engine on the Web must address the heterogeneity of HTML documents One of the changes in search engine development in the past few years is that instead of search engine developers adapting to the different types of webpages, webpage developers are adapting their webpages in order to woo the major commercial search engines. .. authors would also like to thank Katie Terpstra and Eric Clarkson for their work with the book cover artwork and design, respectively Hopefully, this book will help future developers, whether they be students or software engineers, to lessen the aggravation encountered with the current state of search engines It is a critical time for search engines and the future of the Web itself, as both ultimately . Environments, and Tools Michael W. Berry and Murray Browne, Understanding Search Engines: Mathematical Modeling and Text Retrieval, Second Edition Craig C. Douglas, Gundolf Haase, and . Edition Michael W. Berry and Murray Browne, Understanding Search Engines: Mathematical Modeling and Text Retrieval Jack J. Dongarra, lain S. Duff, Danny C. Sorensen, and Henk A. van. Dongarra, J. R. Bunch, C. B. Moler, and C, W, Stewart, linpack Users' Guide Understanding Search Engines Mathematical Modeling and Text Retrieval Second Edition Michael W. Berry University