Text mining innovation for business
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Author (Corporation)
Publication date
2020
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Type
04A - Book part
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Parent work
New trends in business information systems and technology. Digital innovation and digital business Transformation
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Volume
Issue / Number
Pages / Duration
49-61
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Publisher / Publishing institution
Springer
Place of publication / Event location
Cham
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Practice partner / Client
Abstract
This chapter reflects on the business innovation supported by developing text-mining solutions to meet the business needs communicated by Swiss companies. Two related projects from different industries and with different challenges are discussed in order to identify common procedures and methodologies that can be used. One of the partners, in the gig work sector, offers a platform solution for employee recruitment for temporary work. The work assessment is performed using short reviews for which a method for sentiment assessment based on machine learning has been developed. The other partner, in the financial advice sector, operates an information extraction service for business documents, including insurance policies. This requires automation in the extraction of structured information from pdf files. The common path to innovation in such projects includes business process modeling and the implementation of novel technological solutions, including text-mining techniques.
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ISBN
978-3-030-48331-9
978-3-030-48332-6
978-3-030-48332-6
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Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
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Open access category
Closed
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Citation
Pustulka, E., & Hanne, T. (2020). Text mining innovation for business. In R. Dornberger (Ed.), New trends in business information systems and technology. Digital innovation and digital business Transformation (pp. 49–61). Springer. https://doi.org/10.1007/978-3-030-48332-6_4