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Forecasting the Spreading of Technologies in Research Communities

Osborne, Francesco; Mannocci, Andrea and Motta, Enrico (2017). Forecasting the Spreading of Technologies in Research Communities. In: Ninth International Conference on Knowledge Capture (K-CAP 2017), December 4th-6th, 2017, Austin, Texas, United States.

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Abstract

Technologies such as algorithms, applications and formats are an important part of the knowledge produced and reused in the research process. Typically, a technology is expected to originate in the context of a research area and then spread and contribute to several other fields. For example, Semantic Web technologies have been successfully adopted by a variety of fields, e.g., Information Retrieval, Human Computer Interaction, Biology, and many others. Unfortunately, the spreading of technologies across research areas may be a slow and inefficient process, since it is easy for researchers to be unaware of potentially relevant solutions produced by other research communities. In this paper, we hypothesise that it is possible to learn typical technology propagation patterns from historical data and to exploit this knowledge i) to anticipate where a technology may be adopted next and ii) to alert relevant stakeholders about emerging and relevant technologies in other fields. To do so, we propose the Technology-Topic Framework, a novel approach which uses a semantically enhanced technology-topic model to forecast the propagation of technologies to research areas. A formal evaluation of the approach on a set of technologies in the Semantic Web and Artificial Intelligence areas has produced excellent results, confirming the validity of our solution.

Item Type: Conference or Workshop Item
Copyright Holders: 2017 The Authors
Keywords: Scholarly Data; Semantic Web; Technology; Ontology
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: 51198
Depositing User: Francesco Osborne
Date Deposited: 05 Oct 2017 08:35
Last Modified: 11 Jan 2018 16:35
URI: http://oro.open.ac.uk/id/eprint/51198
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