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A framework for identifying and evaluating technologies of interest for effective business strategy: Using text analytics to augment technology forecasting
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0002-0819-2516
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0003-2973-3112
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0001-8884-2154
2017 (English)In: 5th International Symposium on Computational and Business Intelligence (ISCBI 2017), IEEE, 2017, p. 110-115, article id 8053555Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
IEEE, 2017. p. 110-115, article id 8053555
Keywords [en]
text analytics, technology intelligence, forecasting, emerging technologies, technology forecasting, trend analysis
National Category
Computer and Information Sciences
Research subject
Skövde Artificial Intelligence Lab (SAIL); INF301 Data Science
Identifiers
URN: urn:nbn:se:his:diva-14647DOI: 10.1109/ISCBI.2017.8053555ISI: 000427097000023Scopus ID: 2-s2.0-85034807729ISBN: 978-1-5386-1772-4 (electronic)ISBN: 978-1-5386-1771-7 (print)ISBN: 978-1-5386-1770-0 (electronic)ISBN: 978-1-5386-1773-1 (print)OAI: oai:DiVA.org:his-14647DiVA, id: diva2:1172512
Conference
5th International Symposium on Computational and Business Intelligence (ISCBI), August 11-14, 2017, Dubai, United Arab Emirates
Available from: 2018-01-10 Created: 2018-01-10 Last updated: 2018-06-11Bibliographically approved

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Rana, RakeshKarlsson, AlexanderFalkman, Göran

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