Abstract
Data for automated prediction comes from many sources. In previous chapters, discussions centered on pure text mining. Here, we expand our horizons to encompass both text and structured numerical data. Initially, we review the ideal data representations for prediction using either numerical or text data. We consider numerous sources of data including databases, the web, and hybrid forms of text and numerical data. Prototypical examples of blended numerical and text data are given. Using the web as a source of data for prediction is examined. Among the examples presented of web-sourced data are downloaded scientific publications formatted in XML, stock price data and related newswire headlines. Sentiment and opinion analysis are considered with examples from online product reviews. Predictive mining of electronic medical records mining is presented as an example of mixed-data mining.
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Weiss, S.M., Indurkhya, N., Zhang, T. (2010). Data Sources for Prediction: Databases, Hybrid Data and the Web. In: Fundamentals of Predictive Text Mining. Texts in Computer Science. Springer, London. https://doi.org/10.1007/978-1-84996-226-1_7
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DOI: https://doi.org/10.1007/978-1-84996-226-1_7
Publisher Name: Springer, London
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