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Erschienen in:
Stay on Topic, Please: Aligning User Comments to the Content of a News Article Kapitel lesen Erstes Kapitel lesen

2021 | OriginalPaper | Buchkapitel

Valuation of Startups: A Machine Learning Perspective

verfasst von : Mariia Garkavenko, Hamid Mirisaee, Eric Gaussier, Agnès Guerraz, Cédric Lagnier

Erschienen in: Advances in Information Retrieval

Verlag: Springer International Publishing

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Abstract

We address the problem of startup valuation from a machine learning perspective with a focus on European startups. More precisely, we aim to infer the valuation of startups corresponding to the funding rounds for which only the raised amount was announced. To this end, we mine Crunchbase, a well-established source of information on companies. We study the discrepancy between the properties of the funding rounds with and without the startup’s valuation announcement and show that the Domain Adaptation framework is suitable for this task. Finally, we propose a method that outperforms, by a large margin, the approaches proposed previously in the literature.

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Vorheriges Kapitel Classifying Scientific Publications with BERT - Is Self-attention a Feature Selection Method?
Nächstes Kapitel Disparate Impact in Item Recommendation: A Case of Geographic Imbalance
Fußnoten
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The list of European countries, referred to as Europe and abbreviated as EU hereafter, is detailed in [1] for space reasons.
 
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Metadaten
Titel
Valuation of Startups: A Machine Learning Perspective
verfasst von
Mariia Garkavenko
Hamid Mirisaee
Eric Gaussier
Agnès Guerraz
Cédric Lagnier
Copyright-Jahr
2021
Buch
Advances in Information Retrieval

Print ISBN: 978-3-030-72112-1

Electronic ISBN: 978-3-030-72113-8

Copyright-Jahr: 2021

DOI
https://doi.org/10.1007/978-3-030-72113-8_12

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