The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Text Mining: Use of TF-IDF to Examine the Relevance of Words to Documents
Open accessAbstract
In this paper, the use of TF-IDF stands for (term frequencyinverse document frequency) is discussed in examining the relevance of key-words to documents in corpus.The study is focused on how the algorithm can be applied on number of documents.First, the working principle and steps which should be followed for implementation of TF-IDF are elaborated.Secondly, in order to verify the findings from executing the algorithm, results are presented, then strengths and weaknesses of TD-IDF algorithm are compared.This paper also talked about how such weaknesses can be tackled.Finally, the work is summarized and the future research directions are discussed.
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Citations
Cites
Document clustering: TF-IDF approach
Bafna, P., Pramod, D., & Vaidya, A. (2016) · 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT) · doi:10.1109/iceeot.2016.7754750 · Cited by 290
Cited by
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Liu, X., Wang, S., Lu, S., Yin, Z., Li, X., Yin, L., Tian, J., & Zheng, W. (2023) · Systems · doi:10.3390/systems11090483 · Cited by 336
Raj, C., Agarwal, A., Bharathy, G., Narayan, B., & Prasad, M. (2021) · Electronics · doi:10.3390/electronics10222810 · Cited by 128
Cyberbullying Sexism Harassment Identification by Metaheurustics-Tuned eXtreme Gradient Boosting
Dobrojevic, M., Jovanovic, L., Babic, L., Cajic, M., Zivkovic, T., Zivkovic, M., Muthusamy, S., Antonijevic, M., & Bacanin, N. (2024) · Computers, Materials & Continua · doi:10.32604/cmc.2024.054459 · Cited by 75
Flaharty, K. A., Hu, P., Hanchard, S. L., Ripper, M. E., Duong, D., Waikel, R. L., & Solomon, B. D. (2024) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2024.07.011 · Cited by 26
An Empirical Study to Detect Cyberbullying with TF-IDF and Machine Learning Algorithms
Rahman, S., Talukder, K. H., & Mithila, S. K. (2021) · 2021 International Conference on Electronics, Communications and Information Technology (ICECIT) · doi:10.1109/icecit54077.2021.9641251 · Cited by 15
Metadata
- Authors
- Qaiser, S., & Ali, R.
- Venue
- International Journal of Computer Applications
- Publisher
- Foundation of Computer Science
- Published
- 2018-07-16
- Volume
- 181
- Issue
- 1
- Pages
- 25-29
- ISSN
- 0975-8887 (ISSN-L)
- OpenAlex
- W2883730939
- Cited by
- 827
- References
- 1
- FWCI
- 25.89
- Type
- journal article
- Language
- en
- Open access
- diamond
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- Qaiser, S., & Ali, R. (2018). Text Mining: Use of TF-IDF to Examine the Relevance of Words to Documents. International Journal of Computer Applications. https://doi.org/10.5120/ijca2018917395
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
