International Journal of Management and Applied Science (IJMAS)
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current issues
Volume-6,Issue-5  ( May, 2020 )
Past issues
  1. Volume-6,Issue-5  ( May, 2020 )
  2. Volume-6,Issue-4  ( Apr, 2020 )
  3. Volume-6,Issue-3  ( Mar, 2020 )
  4. Volume-6,Issue-2  ( Feb, 2020 )
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  6. Volume-5,Issue-12  ( Dec, 2019 )
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  8. Volume-5,Issue-10  ( Oct, 2019 )
  9. Volume-5,Issue-9  ( Sep, 2019 )
  10. Volume-5,Issue-8  ( Aug, 2019 )

Statistics report
Jul. 2020
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 75
Paper Published : 4404
No. of Authors : 9054
  Journal Paper




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


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