Semantic Textual Similarity (STS) Task

A Semantic Textual Similarity (STS) Task is a Semantic Similarity Modelling Task which outputs is a semantic similarity measure between two text items.

• Example(s):
  • a Semantic Word Similarity Task,
  • a Semantic Sentence Similarity Task,
  • a Semantic Subword Similarity Task,
  • …
• Counter-Example(s):
  • Gene Semantic Similarity Task.
• See: Word Embedding, Natural Language Processing, Vector Space Model, Word Similarity Dataset.

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References

2021

• (Chandrasekaran & Mago, 2021) ⇒ Dhivya Chandrasekaran, and Vijay Mago. (2021). “Evolution of Semantic Similarity - A Survey.” In: ACM Computing Surveys, 54(2).
  • QUOTE: Semantic similarity methods usually give a ranking or percentage of similarity between texts, rather than a binary decision as similar or not similar. Semantic similarity is often used synonymously with semantic relatedness. However, semantic relatedness not only accounts for the semantic similarity between texts but also considers a broader perspective analyzing the shared semantic properties of two words. For example, the words ‘coffee’ and ‘mug’ may be related to one another closely, but they are not considered semantically similar whereas the words ‘coffee’ and ‘tea’ are semantically similar. Thus, semantic similarity may be considered, as one of the aspects of semantic relatedness. The semantic relationship including similarity is measured in terms of semantic distance, which is inversely proportional to the relationship (...)

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