Semantic similarity refers to the degree to which two words, phrases, or concepts share meaning. It is often measured using various techniques, such as comparing definitions, context, or relationships in a semantic network. For example, the words "car" and "automobile" are semantically similar because they refer to the same type of vehicle. In natural language processing, semantic similarity helps computers understand and interpret human language more effectively. By analyzing the meanings of words and their relationships, algorithms can improve tasks like information retrieval, machine translation, and text summarization. This understanding allows for more accurate communication between humans and machines.