What is semantic similarity?

Semantic similarity refers to the degree to which two pieces of text have related meanings. In the context of natural language processing, it involves analyzing and comparing words, phrases, sentences, or entire documents to determine how alike they are in terms of their semantic meaning. This can include understanding synonyms, context, and the overall concepts conveyed in the text.

The correct understanding of semantic similarity allows machines to better interpret human language, enabling more effective search engines, recommendation systems, and dialogue systems. For example, knowing that "car" and "automobile" share similar meanings helps improve the quality of search results when one term is used over the other.

The other choices do not align with the concept of semantic similarity. Text length pertains to the number of characters or words in a document, while text compression is focused on reducing the size of textual data without losing meaning or essential content. Text summarization involves creating a shorter version of a document that captures its main ideas, which is distinct from comparing meanings between two pieces of text.