Machine-based mapping of innovation portfolios

Research output: Contribution to conferencePaperpeer-review


Machine learning techniques show a great promise for improving innovation portfolio management. In this paper we experiment with different methods to classify innovation projects of a high-tech firm as either explorative or exploitative, and compare the results with a manual, theory-based mapping of these projects and with expert classification. We find that by combining a high-information extraction method with a decision tree or maximum entropy algorithm, higher levels of accuracy can be reached. Opportunities and limitations of different methods are discussed.
Original languageEnglish
Number of pages4
Publication statusPublished - 10 Sep 2017
Event18th International CINet Conference - Potsdam, Germany
Duration: 10 Sep 201712 Sep 2017
Conference number: 18


Conference18th International CINet Conference
Internet address


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