AI-Supported Innovation Monitoring

Barteld Braaksma, Piet Daas, Stephan Raaijmakers, Amber Geurts, André Meyer-Vitali

Research output: Chapter in book/volumeChapterScientificpeer-review

1 Citation (Scopus)

Abstract

Small and medium enterprises (SMEs) are a driving force for innovation. Stimulation of innovation in these SMEs is often the target of policy interventions, both regionally and nationally. Which technical areas should be in the focus and how to identify and monitor them? In this position paper, we propose hybrid AI methods for innovation monitoring, using natural language processing (NLP) and a dynamic knowledge graph that combines learning, reasoning and knowledge sharing in collaboration with innovation experts.
Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Science+Business Media
Pages220-226
Number of pages7
ISBN (Print)9783030739584
DOIs
Publication statusPublished - 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12641 LNAI

Keywords

  • Human-machine interaction
  • Hybrid AI
  • Innovation
  • Knowledge graph
  • Natural Language Processing
  • Policy-making

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