Abstract
The data mining techniques used in knowledge discovery as described in Chapter 5 were originally designed to extract information from structured data. However, most data on the Web is unstructured, stored in documents or in non-alpha-numeric form such as images. Most is textual, found in memos, e-mail messages, or similar documents. Previously developed techniques for data mining are unsuitable for analyzing such unstructured textual information. In this chapter, we present the main ideas of knowledge discovery in textual information, which is called text mining.
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© 2001 Springer Science+Business Media New York
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Chang, G., Healey, M.J., McHugh, J.A.M., Wang, J.T.L. (2001). Text Mining. In: Mining the World Wide Web. The Information Retrieval Series, vol 10. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1639-2_6
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DOI: https://doi.org/10.1007/978-1-4615-1639-2_6
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5654-7
Online ISBN: 978-1-4615-1639-2
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