Text Data Encoding Task

An Text Data Encoding Task is a data encoding task for text data.

• Context:
  • It can (typically) involve converting raw text data into high-dimensional text embeddings.
  • It can (typically) be performed by a Text Encoding System (that implements a text encoding algorithm).
  • It can range from encoding short text snippets to entire documents or corpora.
  • It can produce outputs that serve as inputs for downstream tasks like text classification, sentiment analysis, or machine translation.
  • It can handle various languages and scripts, enabling applications in multilingual NLP.
  • It can leverage pretrained language models like BERT, GPT, or Word2Vec for efficient encoding.
  • It can improve with advancements in neural network architectures and language modeling techniques.
  • It can utilize contextual embeddings to capture the meaning of words based on their usage in sentences.
  • ...
• Example(s):
  • Word2Vec Encoding that encodes words into vectors for semantic similarity analysis.
  • BERT-based text encoding that encodes ...
  • JSON Encoding.
  • ...
• Counter-Example(s):
  • Image Data Encoding, which involve converting images into image embeddings.
  • Audio Data Encoding, which focus on encoding audio signals into audio feature vectors.
  • Text Embedding Decoding, ...
• See: Image Data Encoding, Audio Data Encoding, Feature Extraction, BERT, GPT, Word2Vec

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References

2018

• (Devlin et al., 2018) ⇒ Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. (2018). “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.” In: arXiv. doi:10.48550/arXiv.1810.04805

2013

• (Mikolov et al., 2013) ⇒ Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. (2013). “Efficient Estimation of Word Representations in Vector Space.” In: arXiv. doi:10.48550/arXiv.1301.3781

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