Dhivya Chandrasekaran and Vijay Mago. 2021. Evolution of Semantic Similarity—A Survey. ACM Comput. Surv. 54, 2, Article 41 (February 2021), 37 pages. https://doi.org/10.1145/3440755 In the early days, two text snippets were considered similar if they contain the same words/characters. The techniques such as Bag ofWords (BoW), Term Frequency-Inverse Document Frequency (TF-IDF) were used to represent text, as real value vectors to aid calculation of semantic similarity. However, these techniques did not attribute to the fact that words have different meanings and different words can be used to represent a similar concept. To address these drawbacks of the lexical measures various semantic similarity techniques were proposed over the past three decades. 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 pro
