Paper Title :Machine Learning using Instruments for Text Selection: Predicting Innovation Performance
Author :Kian-Guan Lim, Michelle S.J. Lim
Article Citation :Kian-Guan Lim ,Michelle S.J. Lim ,
(2019 ) " Machine Learning using Instruments for Text Selection: Predicting Innovation Performance " ,
International Journal of Management and Applied Science (IJMAS) ,
pp. 37-40,
Volume-5,Issue-12
Abstract : In machine learning we utilize the idea of employing instrumental variable such as patent records to train the texts. Patent records are highly correlated with R&D expenditures, but are not necessarily correlated with performance residuals not linked to R&D. Thus, using instrumental patent records to train word counts of selected texts to serve as a proxy for firm R&D expenditure, we show that the texts and associated word counts provide effective prediction of firm innovation performances such as firm market value and total sales growth.
Keywords - Machine Learning; R&D Reporting; Textual Analyses; Firm Innovation
Type : Research paper
Published : Volume-5,Issue-12
DOIONLINE NO - IJMAS-IRAJ-DOIONLINE-16780
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Copyright: © Institute of Research and Journals
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Published on 2020-02-07 |
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