View source for Deep Neural Network-based Text Segmentation Algorithm

A [[Deep Neural Network-based Text Segmentation Algorithm]] is a [[text segmentation algorithm]] that employs [[deep neural network]]s (to perform [[text segmentation task]])s.
* <B>Context:</B>
** It can be trained on large datasets to recognize complex patterns in text for accurate segmentation.
** It can be designed as a [[Supervised Learning Algorithm]], requiring labeled data for training.
** It can be support with techniques such as [[Transfer Learning]] and [[Word Embedding]]s.
** ...
* <B>Example(s):</B>
** a [[Bidirectional Encoder Representations from Transformers (BERT)-based Segmentation Algorithm]], which uses a [[BERT model]].
** a [[Long Short-Term Memory (LSTM)-based Segmentation Algorithm]].
** a [[Convolutional Neural Network-based Text Segmentation Algorithm]]
** a [[Recurrent Neural Network-based Text Segmentation Algorithm]].
** ...
* <B>Counter-Example(s):</B>
** a [[Rule-based Text Segmentation Algorithm]], which relies on predefined rules rather than learning from data.
** a [[Frequency-based Text Clustering Algorithm]], which groups text based on word frequencies and does not involve deep learning.
* <B>See:</B> [[Natural Language Processing (NLP)]], [[Deep Learning]], [[Text Analytics]].

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