Читать книгу Semantic Web for Effective Healthcare Systems - Группа авторов - Страница 31

Ontology querying involves direct extract of feature from its repository instead of doing similarity measures as other techniques like Naive Bayes algorithm do. The similarity between the terms is incorporated into the model during the CFS_LDA modelling technique itself rather than the querying phase. It is very much required as the lexicon-based indexing technique just uses the keywords with one-to-one mapping and it does not look for synonymous terms and contextually related terms. OnSI model retrieves these types of terms from the document collection for the features or topics, which in turn improves the recall value. 100% accuracy may not be attained sometimes, as some of the terms present in query documents may not be present in the Ontology and it may need to be updated. In the next iteration, the value gets improved.