The DOI matches its Crossref record.
A Survey of Text Mining Techniques and Applications
Abstract
Text Mining has become an important research area. Text Mining is the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources. In this paper, a Survey of Text Mining techniques and applications have been s presented.
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Citations
Cited by
Aldowah, H., Al-Samarraie, H., & Fauzy, W. M. (2019) · Telematics and Informatics · doi:10.1016/j.tele.2019.01.007 · Cited by 564
Naseem, U., Razzak, I., Khan, S. K., & Prasad, M. (2021) · ACM Transactions on Asian and Low-Resource Language Information Processing · doi:10.1145/3434237 · Cited by 194
Ferreira‐Mello, R., André, M., Pinheiro, A., Costa, E., & Romero, C. (2019) · WIREs Data Mining and Knowledge Discovery · doi:10.1002/widm.1332 · Cited by 193
Olorisade, B. K., Brereton, P., & Andras, P. (2017) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2017.07.010 · Cited by 54
Twitter usage in Tourism: Literature Review
Ćurlin, T., Jaković, B., & Miloloža, I. (2019) · Business Systems Research Journal · doi:10.2478/bsrj-2019-0008 · Cited by 49
Automatic classification of literature in systematic reviews on food safety using machine learning
van den Bulk, L. M., Bouzembrak, Y., Gavai, A., Liu, N., van den Heuvel, L. J., & Marvin, H. J. P. (2022) · Current Research in Food Science · doi:10.1016/j.crfs.2021.12.010 · Cited by 38
“When it comes to text as input, a specialized part of machine learning called text mining has been on the rise (Gupta and Lehal, 2009; Talib et al., 2016; Hassani et al., 2020; Jung and Lee, 2020).”
BackgroundTextual aggregation approaches in OLAP context: A survey
Bouakkaz, M., Ouinten, Y., Loudcher, S., & Strekalova, Y. (2017) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2017.06.005 · Cited by 16
Metadata
- Authors
- Gupta, V., & Lehal, G. S.
- Venue
- Journal of Emerging Technologies in Web Intelligence
- Published
- 2009-08-01
- Volume
- 1
- Issue
- 1
- ISSN
- 1798-0461 (ISSN-L)
- OpenAlex
- W2061941130
- Cited by
- 699
- References
- 0
- FWCI
- 14.82
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
