The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.
Document-level sentiment classification: An empirical comparison between SVM and ANN
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LIBSVM: A library for support vector machines
Chang, C.-C., & Lin, C.-J. (2011) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1961189.1961199 · Cited by 40,918
Neural Networks: A Comprehensive Foundation
Haykin, S. (1998) · Cited by 30,070
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162
Book Review: Pattern Recognition and Machine Learning
Nasrabadi, N. M. (2007) · Journal of Electronic Imaging · doi:10.1117/1.2819119 · Cited by 22,066
Artificial intelligence: a modern approach
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A Tutorial on Support Vector Machines for Pattern Recognition
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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
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Cited by
Sentiment analysis algorithms and applications: A survey
Medhat, W., Hassan, A., & Korashy, H. (2014) · Ain Shams Engineering Journal · doi:10.1016/j.asej.2014.04.011 · Cited by 3,248
A survey on sentiment analysis methods, applications, and challenges
Wankhade, M., Rao, A. C. S., & Kulkarni, C. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10144-1 · Cited by 1,528
A survey on opinion mining and sentiment analysis: Tasks, approaches and applications
Ravi, K., & Ravi, V. (2015) · Knowledge-Based Systems · doi:10.1016/j.knosys.2015.06.015 · Cited by 1,306
A review on sentiment analysis and emotion detection from text
Nandwani, P., & Verma, R. (2021) · Social Network Analysis and Mining · doi:10.1007/s13278-021-00776-6 · Cited by 869
ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis
Basiri, M. E., Nemati, S., Abdar, M., Cambria, E., & Acharya, U. R. (2021) · Future Generation Computer Systems · doi:10.1016/j.future.2020.08.005 · Cited by 745
Metadata
- Authors
- Moraes, R., Valiati, J. F., & Gavião Neto, W. P.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2013-02
- Volume
- 40
- Issue
- 2
- Pages
- 621-633
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2012070465
- Cited by
- 733
- References
- 64
- FWCI
- 28.81
- Type
- journal article
- Language
- en
- Open access
- closed
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- Moraes, R., Valiati, J. F., & Gavião Neto, W. P. (2013). Document-level sentiment classification: An empirical comparison between SVM and ANN. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2012.07.059
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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.
