Trend Mining on Bibliographic Data

Most times, current and emerging trends in scientific communities are only discernible for active domain experts. Trend mining on bibliographic data may give insight for politicians, entrepreneurs and new scientists. This work outlines a research agenda for approaching this problem.

Content

Author and article information

Contributors

Christin Katharina Kreutz

Conference

Publication date: September 2017

Publication date (Print): September 2017

Pages: 1-4

Affiliations

[0001]Trier University

54286 Trier, DE

Article

DOI: 10.14236/ewic/FDIA2017.11

SO-VID: d3280cb2-fd8c-4f37-9592-3ab450e0b1b3

License:

This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Conference name: Seventh BCS-IRSG Symposium on Future Directions in Information Access

Conference acronym: FDIA

Conference number: 7

Conference location: Barcelona, Spain

Conference date: 5 September 2017

Conference sponsor: Electronic Workshops in Computing (eWiC)

Conference theme: Future Directions in Information Access

History

Product

1477-9358 BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/FDIA2017.11

Self URI (journal page): https://ewic.bcs.org/

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Trend Mining on Bibliographic Data

Abstract