Concept embedding and network analysis of scientiﬁc innovations emergence

Brodiuk, Serhii

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2020
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dc.contributor.author	Brodiuk, Serhii
dc.date.accessioned	2020-02-24T15:37:15Z
dc.date.available	2020-02-24T15:37:15Z
dc.date.issued	2020
dc.identifier.citation	Brodiuk, Serhii. Concept embedding and network analysis of scientiﬁc innovations emergence : Master Thesis : manuscript rights / Serhii Brodiuk ; Supervisor: PhD. Vasyl Palchykov, Co-supervisor: Prof. Dr. Yurij Holovatch ; Ukrainian Catholic University, Department of Computer Sciences. – Lviv : [s.n.], 2020. – 32 p. : ill.	uk
dc.identifier.uri	http://er.ucu.edu.ua/handle/1/2043
dc.language.iso	en	uk
dc.subject	Concept embedding	uk
dc.subject	network analysis	uk
dc.subject	Topological features of concept networks	uk
dc.title	Concept embedding and network analysis of scientiﬁc innovations emergence	uk
dc.type	Preprint	uk
dc.status	Публікується вперше	uk
dc.description.abstracten	Novelty is an inherent part of innovations and discoveries. Such processes may be considered as the appearance of new ideas or as the emergence of atypical connections between existing ones. The importance of such connections hints for investigation of innovations through network or graph representation in the space of ideas. In such representation, a graph node corresponds to the relevant notion (idea), whereas an edge between two nodes means that the corresponding notions have been used in a common context. The question addressed in this research is the possibility to identify the edges between existing concepts where the innovations may emerge. To this end, a well-documented scientiﬁc knowledge landscape has been used. Namely, we downloaded 1.2M arXiv.org manuscripts dated starting from April 2007 and until September 2019; and extracted relevant concepts for them using ScienceWISE.info platform. Combining approaches developed in complex networks science and graph embedding the predictability of edges (links) on the scientiﬁc knowledge landscape where the innovations may appear is investigated. We argue that the conclusions drawn from this analysis may be used not only to the scientiﬁc knowledge analysis but are rather generic and may be applied to any domain that involves creativity within.	uk