Data Mining


Data mining is the practice of extracting data from published data sets, websites, or text to form new data sets by using pattern recognition or other knowledge discovery techniques. “The functions or models of data mining can be categorized according to the task performed: association, classification, clustering, and regression” (Siguenza-Guzman, et al., 2015).

Further Resources

Brook M, Murray-Rust P, & Oppenheim C. (2014). The Social, Political and Legal Aspects of Text and Data Mining (TDM)(link is external). D-Lib Magazine, 20(11/12).

Demigha S. (2016). Mining Knowledge of the Patient Record: “The Bayesian Classification to Predict and Detect Anomalies in Breast Cancer”(link is external). Electronic Journal of Knowledge Management, 14(3), 128–139.

Kristianto GY, Topić G, & Aizawa A. (2014). Extracting Textual Descriptions of Mathematical Expressions in Scientific Papers(link is external). D-Lib Magazine, 20(11/12).

Murray-Rust P, Smith-Unna R, & Mounce R. (2014). AMI-diagram: Mining Facts from Images(link is external). D-Lib Magazine, 20(11/12).

Siguenza-Guzman L, Saquicela V, Avila-Ordóñez E, Vandewalle J, & Cattrysse D. (2015). Literature Review of Data Mining Applications in Academic Libraries(link is external). Journal of Academic Librarianship, 41(4), 499–510.

Smith-Unna R, Murray-Rust P. (2014). The ContentMine Scraping Stack: Literature-scale Content Mining with Community-maintained Collections of Declarative Scrapers(link is external). D-Lib Magazine, 20(11/12).

Tourassi G, Yoon H-J, Xu S, & Han X. (2016). The utility of web mining for epidemiological research: studying the association between parity and cancer risk(link is external). Journal of the American Medical Informatics Association, 23(3), 588–595.

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