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  4. How to find similar companies using websites?
 
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2023
Journal Article
Title

How to find similar companies using websites?

Abstract
The selection of industry partners for Research and Development (R&D) is a challenging task for many organizations. Present methods for partner-selection, based on patents, publications or company databases, do often fail for highly specialized SMEs. Our approach aims at calculating the technological similarity for partner discovery. We apply methods from Natural Language Processing (NLP) on companies’ website texts. We show that the deep-learning language model BERT outperforms other methods at this task. Tested against expert-proven ground truth, it achieves an F1-score up to 0.90. Our results imply that website texts are useful for the purpose of estimating the similarity between companies. We see great potential in the scalability of the semantic analysis of company website texts.
Author(s)
Bergmann, Jan-Peter  
Fraunhofer-Zentrum für Internationales Management und Wissensökonomie IMW  
Amin, Miriam
Fraunhofer-Zentrum für Internationales Management und Wissensökonomie IMW  
Campbell Borges, Yuri Cassio
Fraunhofer-Zentrum für Internationales Management und Wissensökonomie IMW  
Trela, Karl  
Fraunhofer-Zentrum für Internationales Management und Wissensökonomie IMW  
Journal
World Patent Information  
DOI
10.1016/j.wpi.2023.102172
Language
English
Fraunhofer-Zentrum für Internationales Management und Wissensökonomie IMW  
Keyword(s)
  • BERT

  • Natural language processing

  • Partner selection

  • Semantic web

  • Web mining

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