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Text Mining

  • Reference work entry
Encyclopedia of Database Systems

Synonyms

Knowledge discovery in text (KDT)

Definition

Text mining is the art of data mining from text data collections. The goal is to discover knowledge (or information, patterns) from text data, which are unstructured or semi-structured. It is a subfield of Data Mining (DM), which is also known as Knowledge Discovery in Databases (KDD). KDD is to discover knowledge from various data sources, including text data, relational databases, Web data, user log data, etc. Text Mining is also related to other research fields, including Machine Learning (ML), Information Retrieval (IR), Natural Language Processing (NLP), Information Extraction (IE), Statistics, Pattern Recognition (PR), Artificial Intelligence (AI), etc.

Historical Background

The phrase of Knowledge Discovery in Databases (KDD) was first used at 1st KDD workshop in 1989. Marti Hearst [4] first used the term of text data mining (TDM) and differentiated it with other concepts such as information retrieval and natural language...

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Recommended Reading

  1. Andreas H., Andreas N., and Gerhard P. A brief survey of text mining. J. Computat. Linguistics Lang. Technol., 20(1):19–62, 2005.

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  2. Bing L. Web Data Mining: Exploring Hyperlinks, Contents and Usage Data. Springer, Berlin, pp. 411–447.2007,

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  3. Dipanjan D. and Martins A.F.T. A Survey on Automatic Text Summarization. Literature Survey for the Language and Statistics II course at Carnegie Mellon University, November, 2007.

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  4. Hearst M. Untangling text data mining. In Proc. 27th Annual Meeting of the Assoc. for Computational Linguistics, 1999.

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  5. Informative and indicative summarization. Available at: http://www1.cs.columbia.edu/~min/papers/sigirDuc01/node2.html

  6. Liebman M. Bioinformatics: an editorial perspective. Available at: (http://www.netsci.org/Science/Bioinform/feature01.html)

  7. Usama F., Gregory P.-S., and Padhraic S. From data mining to knowledge discovery in databases. AI Mag., 17(3):37–54, 1996.

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  8. Wayne C.L. Multilingual topic detection and tracking: successful research enabled by corpora and evaluation. In Proc. Conf. on Language Resources and Evaluation, 2000.

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  9. Witten I.H. Text mining. In Practical Handbook of Internet Computing, M.P. Singh (eds.). Chapman and Hall/CRC Press, Boca Raton, FL, 2005, pp. 14-1–14-22.

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Author information

Authors and Affiliations

  1. Shanghai Jiao Tong University, Shanghai, China

    Yanli Cai

  2. Microsoft Research Asia, Beijing, China

    Jian-Tao Sun

Authors
  1. Yanli Cai
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  2. Jian-Tao Sun
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Editor information

Editors and Affiliations

  1. College of Computing, Georgia Institute of Technology, 266 Ferst Drive, 30332-0765, Atlanta, GA, USA

    LING LIU (Professor) (Professor)

  2. Database Research Group David R. Cheriton School of Computer Science, University of Waterloo, 200 University Avenue West, N2L 3G1, Waterloo, ON, Canada

    M. TAMER ÖZSU (Professor and Director, University Research Chair) (Professor and Director, University Research Chair)

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© 2009 Springer Science+Business Media, LLC

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Cai, Y., Sun, JT. (2009). Text Mining. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_418

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