The term "semantic expansion" is correct and usable in written English.
You can use it to describe a linguistic system or description of a text that has been broadened or modified to allow for more interpretations or multiple meanings. For example, "The researcher applied semantic expansion to the text to increase its depth and complexity."
It generates a set of concept numbers for each text, which is then used to retrieve information in a process called semantic expansion, where a keyword query is also processed semantically.
These direct annotations are fed into semantic expansion components, which enhance the original annotations using semantics stored in one or more user-specified ontologies.
The mechanism is based on developing speaking skills in lexico-grammatical and semantic expansion of verbal information and intersemiotic translation of extralinguistic information into speech register.
The semantic expansion of 'soul' in the sixth and fifth centuries is reflected in the philosophical writings of the period.
From comparatively humble Homeric beginnings, the word 'soul' undergoes quite remarkable semantic expansion in sixth and fifth century usage.
There is, moreover, some reason to think that philosophical activity, notably Pythagorean speculation (beginning around mid-sixth century), contributed to the semantic expansion of 'soul'soul
The key step of semantic query expansion is to find out the semantic relationship between the keywords.
In this paper, from a new perspective, we propose a similar search solution based on semantic query expansion while supporting similarity ranking.
In the TREC 2016 CDS task, Harsha Gurulingappa et al. [15] proposed a semi-supervised method that takes the advantages of pseudo-relevance feedback, semantic query expansion and document similarity measures based on unsupervised word embeddings.
Advanced solutions incorporate controlled vocabularies or ontologies for semantic query expansion (Malone et al., 2010).
This paper presents a novel method based on Formal Concept Analysis (FCA) and Semantic Query Expansion (SQE) to assist the end-user in defining their seed queries and in refining the expanded search space that it encompasses.
