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Journal article mining: the scholarly publishers' perspective

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The essence of text mining and data mining is that a machine and software are used for content analysis of large digital corpora. The Publishing Research Consortium commissioned a study on content mining of scholarly journal articles with 29 expert interviews and an international survey among publishers. The main results are: (i) content mining developments appear to be accelerating with more applications in more areas; (ii) third-party demand for content mining is widespread but still at low levels of frequency; (iii) publishers' permissions for content mining are quite liberal, especially for research-driven mining requests; (iv) half of the publisher respondents undertake mining of their own content; and (v) content mining is on the rise – publishers and third parties both report an increase in planned mining activities. As content mining of journal articles spreads and intensifies, cross-publisher solutions can better help facilitate content mining. The study investigated the interest and willingness of publishers to support a set of different solutions, from one shared content mining platform to commonly agreed access terms for mining and standardization of mining-friendly content formats.
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Document Type: Research Article

Publication date: 2012-01-01

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  • Editor in Chief: Pippa Smart
    North American Editor: Judy Luther

    Learned Publishing is the journal of the Association of Learned and Professional Society Publishers, published in collaboration with the Society for Scholarly Publishing. The journal is published quarterly in January/April/July/October.

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    Learned Publishing will be moving to Wiley-Blackwell as of January 1, 2016. Please contact the publisher at [email protected] for information on how to continue access to this title.
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