Text Analytics Applications to Support Decision Making and Performance Management – A Systematic Literature Review
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-36121-0_36
Reference18 articles.
1. Aggarwal, C.C.: Machine Learning for Text, vol. 848. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-73531-3
2. Allahyari, M., et al.: A brief survey of text mining: classification, clustering and extraction techniques. arXiv preprint arXiv:1707.02919 (2017)
3. Singh, A., Jenamani, M., Thakkar, J.: Do online consumer reviews help to evaluate the performance of automobile manufacturers? J. Enterp. Inf. Manag. (2020)
4. Ching, M.R.D., de Dios Bulos, R.: Improving restaurants’ business performance using yelp data sets through sentiment analysis. In: Proceedings of the 2019 3rd International Conference on E-commerce, E-Business and E-Government, pp. 62–67 (2019)
5. Yang, J., Anwar, A.M.: Social media analysis on evaluating organisational performance a railway service management context. In: 2016 IEEE 14th International Conference on Dependable, Autonomic and Secure Computing, 14th International Conference on Pervasive Intelligence and Computing, 2nd International Conference on Big Data Intelligence and Computing and Cyber Science and Technology Congress (DASC/PiCom/DataCom/CyberSciTech), pp. 835–841. IEEE (2016)
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