Abstract
The goal of the paper is to give an overview on the state of the art of data mining and text mining approaches which are useful for bibliometrics and patent databases. The paper explains the basics of data mining in a non-technical manner. Basic approaches from statistics and machine learning are introduced in order to clarify the groundwork of data mining methods. Text mining is introduced as a special case of data mining. Data and text mining applications especially useful for bibliometrics and querying of patent databases are reviewed and three case studies are described.
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Leopold, E., May, M., Paaß, G. (2004). Data Mining and Text Mining for Science & Technology Research. In: Moed, H.F., Glänzel, W., Schmoch, U. (eds) Handbook of Quantitative Science and Technology Research. Springer, Dordrecht. https://doi.org/10.1007/1-4020-2755-9_9
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DOI: https://doi.org/10.1007/1-4020-2755-9_9
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