Semantic feature analysis (SFA) is a data mining technique that mining for semantic features in text data. Semantic feature analysis is used to identify the semantic contents of text documents.
Text data can be analyzed for semantic features by applying the following four steps:
1. Create a dictionary of all the words in the text.
2. Analyze the text for the presence of each of the dictionary words.
3. Calculate the semantic similarity of each word to all other words in the dictionary.
4. Use the semantic similarity of each word to create a semantic feature vector.
Semantic feature analysis can be used to find relationships between words and concepts in a text. This information can be used to create models of the semantic structure of a text. Semantic feature analysis can also be used to find the topics of a text.