Features of Semantic Similarity Assessment

Abstract

Semantic similarity is a fundamental concept in computational linguistics. The models used for the representation of text have a major role in similarity computation. The text with multilingual and multimodal components shows the need for computing similarity based on different characteristics of text. This chapter studies various aspects of semantic similarity of linguistic units, cross-level similarity, semantic models, and similarity measures. One of the main motivations of this chapter is to analyze semantic similarity models such as geometric models, feature-based models, graph-based models, vector space models, and formal concept analysis models. In addition, a composite summary score based on words and hashtags is applied for the tweet summarization task which is effective when compared with other measures.