![]() Methodological Developments in Searching for Studies for Systematic Reviews: Past, Present and Future? Systematic Reviews, 2. Lefebvre, C., Glanville, J., Wieland, L.Prospective comparison of search strategies for systematic reviews: An objective approach yielded higher sensitivity than a conceptual one. Hausner E, Guddat C, Hermanns T, Lampert U, Waffenschmidt S.Use of text mining tools in the development of search strategies – comparison of different approaches. Hausner E, Knelangen M, Waffenschmidt S.Do simple text mining tools have anything to offer Embase users? 2016 [Available from. Text mining in search strategy development Suggested references Programming tools such as the tm package in R or quanteda allow for much more flexibility than some of the tools covered here, but they are also much more difficult to use if one is not accustomed to programming. Some of the tools listed allow for customization of these procedures, while some are preconfigured. ![]() Preprocessing includes data cleaning and normalization techniques such as: Text mining, like data science in general, also involves a great deal of preprocessing, which tools may or may not handle. Decisions about cutoffs for high frequency terms, for example, and calculations to establish high frequencies require somewhat large sets of relevant references (which can be derived based on the included studies of relevant systematic reviews, for example) as well as a population set of random records against which one can test whether a term is high frequency across documents in general (for example, words that are high-frequency due to common check tags such as 'human') or in the relevant documents only. Using text mining techniques to increase the objectivity of search strategies requires a more sophisticated use of tools that librarians or other searchers may or may not be prepared to implement. ![]()
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