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  1. Text mining : applications and theory

    Berry, Michael W.
    Hoboken, NJ : John Wiley & Sons, 2010.

    Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives. The contributors span several countries and scientific domains: universities, industrial corporations, and government laboratories, and demonstrate the use of techniques from machine learning, knowledge discovery, natural language processing and information retrieval to design computational models for automated text analysis and mining. This volume demonstrates how advancements in the fields of applied mathematics, computer science, machine.

    Online Wiley Online Library

  2. Understanding search engines : mathematical modeling and text retrieval

    Berry, Michael W.
    Philadelphia, PA : Society for Industrial and Applied Mathematics, c1999.

    A discussion of many of the key design issues for building search engines. It emphasizes the important roles that applied mathematics can play in improving information retrieval. The authors discuss not only important data structures, algorithms and software, but also user-centred issues such as interfaces, manual indexing, and document preparation. The authors bridge the gap between applied mathematics and information retrieval. They discuss some of the current problems in information retrieval that may not be familiar to applied mathematicians and computer scientists and present some of the driving computational methods (SVD, SDD) for automated conceptual indexing. This book introduces topics in a non-technical way and provides insights into common problems found in information retrieval. The more mathematical details are provided in sidebars or offset from the regular text.

  3. Understanding search engines [electronic resource] : mathematical modeling and text retrieval

    Berry, Michael W.
    2nd ed - Philadelphia, Pa. : Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104), 2005

    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 friendlyThe 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.

    Online SIAM Publications Online

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