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  1. Text mining : applications and theory

    Chichester, U.K. : Wiley, ©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 learning.

    Online Wiley Online Library

  2. Text mining


  3. Text mining : concepts, implementation, and big data challenge

    Jo, Taeho
    Cham, Switzerland : Springer, 2019

    This book discusses text mining and different ways this type of data mining can be used to find implicit knowledge from text collections. The author provides the guidelines for implementing text mining systems in Java, as well as concepts and approaches. The book starts by providing detailed text preprocessing techniques and then goes on to provide concepts, the techniques, the implementation, and the evaluation of text categorization. It then goes into more advanced topics including text summarization, text segmentation, topic mapping, and automatic text management.

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  1. Text and data mining

    this is a page that describes text and data mining services at Stanford Libraries

  2. Digital Humanities

    Stanford Libraries' Digital Humanities collections include print and digital materials on digital humanities scholarship, as well as resources and services to support scholarly approaches that combine computational methods with humanistic inquiry.


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