Sentence Classification Algorithm

A Sentence Classification Algorithm is a text-item classification algorithm that can be implemented into a sentence classification system to solve a sentence classification task.

• Context:
  • It can be a component of a Sentence Classification System.
  • It can range from simple Rule-based Sentence Classification Algorithm to being a Supervised Learning-based Sentence Classification Algorithm .
  • It can range from being a Single-label Sentence Classification Algorithm to being a Multi-label Sentence Classification Algorithm.
  • …
• Example(s):
  • Naive Bayes-based Sentence Classification Algorithm.
  • Decision Tree-based Sentence Classification Algorithm.
  • BERT-based Sentence Classification Algorithm models for advanced natural language understanding tasks.
  • Convolutional Neural Network-based Sentence Classification Algorithm for sentence classification in contexts where local patterns in text are significant.
  • …
• Counter-Example(s):
  • A Paragraph Classification Algorithm.
  • a Tokenization Algorithm.
  • a Word Embedding Model.
  • a Syntax Parsing Algorithm.
  • a Named Entity Recognition Algorithm.
  • a Language Generation Model.
  • …
• See: Machine Learning Algorithm, Natural Language Processing, Deep Learning, Supervised Learning, Unsupervised Learning.

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References

2015

• (Zhang & Wallace, 2015) ⇒ Ye Zhang, and Byron Wallace. (2015). “A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification.” arXiv preprint arXiv:1510.03820. [1]
  • NOTE: It explores the effectiveness of convolutional neural networks in sentence classification, questioning the utility of one-hot CNN models and discussing their potential limitations in such tasks.

2018

• (Hassan & Mahmood, 2018) ⇒ Abdalraouf Hassan, and Ausif Mahmood. (2018). “Convolutional Recurrent Deep Learning Model for Sentence Classification.” In: IEEE Access. [2]
  • NOTE: This paper introduces a hybrid model combining convolutional and recurrent neural networks for sentence classification, highlighting its significance in the domain of natural language processing and sentiment analysis.

2019

• (Wieting & Kiela, 2019) ⇒ John Wieting, and Douwe Kiela. (2019). “No Training Required: Exploring Random Encoders for Sentence Classification.” arXiv preprint arXiv:1901.10444. [3]
  • NOTE: This study investigates the use of random encoders in generating sentence representations, focusing on the potential of leveraging pre-trained word embeddings without further training for sentence classification.

2014

• (Kim, 2014) ⇒ Yoon Kim. (2014). “Convolutional Neural Networks for Sentence Classification.” arXiv preprint arXiv:1408.5882. [4]
  • NOTE: This seminal work by Yoon Kim examines the application of convolutional neural networks for sentence classification, demonstrating the effectiveness of CNNs trained on pre-trained word vectors for various sentence-level tasks.

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