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Forecasting Technology Migrations by means of the Technology-Topic Framework

Osborne, Francesco; Mannocci, Andrea and Motta, Enrico (2017). Forecasting Technology Migrations by means of the Technology-Topic Framework. In: International Semantic Web Conference (ISWC) 2017, 21-25 Oct 2017, Vienna, Austria.

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Technologies such as algorithms, applications and formats usually originate in the context of a specific research area and then spread to several other fields, sometimes with transformative effects. However, this can be a slow and inefficient process, since it not easy for researchers to be aware of all interesting approaches produced by unfamiliar research communities. We address this issue by introducing the Technology-Topic Framework, a novel approach which uses a semantically enhanced technology-topic model and machine learning to forecast the propagation of technologies across research areas. The aim is to foster the knowledge flow by suggesting to scholars technologies that may become relevant to their research field. The system was evaluated on a manually curated set of 1,118 technologies in Semantic Web and Artificial Intelligence and the results of the evaluation confirmed the validity of our approach.

Item Type: Conference or Workshop Item
Keywords: Scholarly Data, Semantic Web, Technology Propagation, Technology Spreading, Bibliographic Data, Scholarly Ontologies
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 50890
Depositing User: Francesco Osborne
Date Deposited: 22 Sep 2017 15:17
Last Modified: 06 May 2019 21:16
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These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

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