Text mining for science and technology: A review – Part II‑citation and discovery

Journal of Scientometric Research,2013,2,1,3-14.
Published:January 2013
Type:Review Article
Authors:
Author(s) affiliations:

Ronald N. Kostoff*

School of Public Policy, Georgia Institute of Technology, 13500 Tallyrand Way, Gainesville, VA 20155, USA

Abstract:

This second part of a two‑part review addressed three complementary components of text mining: Citation scientometrics, seminal literature reviews (SLR), and literature‑related discovery and innovation (LRDI). All three have at their core the development of very comprehensive and precise queries for retrieving the data of interest. For any literature of interest, the citation scientometrics approach analyzes in detail the papers that cite the literature of interest (citation mining), and/ or the papers that are cited by the literature of interest. The SLR uses the highly‑cited references in a retrieved literature of interest to map out the intellectual heritage of that literature. The LRDI integrates (a) discovery generation from disparate literatures with (b) the wealth of knowledge contained in the prior art to (c) potentially solve technical problems that appear intractable. The review highlights each of the approaches drawing from studies undertaken by author and his research group.

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Kostoff RN. Text mining for science and technology: A review – Part II‑citation and discovery. Journal of Scientometric Research. 2013;2(1):3-14. doi:10.4103/2320-0057.115862.