Semantic Word Relatedness Measure
A Semantic Word Relatedness Measure is a Semantic Relatedness Measure that pertains to relatedness of two words.
- Example(s):
- $SRM(coffee, mug) \ne 0$, i.e. coffee and mug are semantically related, although they are not semantically similar.
- MEN Semantic Word Relatedness Measure,
- …
- Counter-Example(s):
- See: Natural Language Processing, Natural Language Understanding, Language Model, Semantics, Syntactic.
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 (...)
- 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 ‘