A Text Mining Approach to Extract and Rank Innovation Insights from Research Projects
Open innovation is a new paradigm embraced by companies to introduce transformations. It assumes that firms can and should use external and internal ideas to innovate. Recently, commercial and research projects have undergone an exponential growth, leadin
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Data Science and Big Data Analytics Unit, EURECAT - Centre Tecn` ogic de Catalunya, Carrer de Bilbao 72, 08005 Barcelona, Spain [email protected], [email protected] Department of Mathematics and Computer Science, University of Cagliari, Via Ospedale 72, 09124 Cagliari, Italy {francescam.malloci,fenu}@unica.it
Abstract. Open innovation is a new paradigm embraced by companies to introduce transformations. It assumes that firms can and should use external and internal ideas to innovate. Recently, commercial and research projects have undergone an exponential growth, leading the open challenge of identifying possible insights on interesting aspects to work on. The existing literature has focused on the identification of goals, topics, and keywords in a single piece of text. However, insights do not have a clear structure and cannot be validated by comparing them with a straightforward ground truth, thus making their identification particularly challenging. Besides the extraction of insights from previously existing initiatives, the issue of how to present them to a company in a ranking also emerges. To overcome these two issues, we present an approach that extracts insights from a large number of projects belonging to distinct domains, by analyzing their abstract. Then, our method is able to rank these results, to support project preparation, by presenting first the most relevant and timely/recent insights. Our evaluation on real data coming from all the Horizon 2020 European projects, shows the effectiveness of our approach in a concrete case study. Keywords: Information extraction
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· Ranking · Text mining
Introduction
Open innovation is a strategy that combines internal knowledge and skills with those of other external entities, for sharing, integrating, and acquiring ideas in collaboration with other interested parties (consumers, users, employees, other All authors equally contributed to this research. c Springer Nature Switzerland AG 2020 Z. Huang et al. (Eds.): WISE 2020, LNCS 12343, pp. 143–154, 2020. https://doi.org/10.1007/978-3-030-62008-0_10
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companies, technology or research centers, universities, etc.) [5,15,21]. The key role of this process is represented by the consultants, who act as facilitators and accelerators for the whole process. However, consultants spend a lot of time reading similar projects to shape their idea until the product is launched. A key role in these activities is represented by the manual extraction of insights, i.e., aspects that haven been identified in previous projects has open issues, challenges, and interesting aspects to work on. Relying on previous initiatives is a central aspect to provide foundations that an aspect is worth working on. Indeed, these insights have the dual role of providing (i) consultants with ideas and (ii) references of existing projects in the same area, to highlight and contextualize the work. Given the incredible amount of both private and public projects being created and approved on a daily basis, a man
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