Читать книгу Semantic Web for Effective Healthcare Systems - Группа авторов - Страница 32
1.7.2 Discussion 2
ОглавлениеTime taken for modeling and querying (training and testing) text documents are measured. OnSI model takes 2.1 s for modeling (70% of DS1) and 0.35 s for querying (30% of DS1). The use of Sparql language in OnSI model greatly reduces the time for query processing. The time complexity of querying depends on the number of terms present in the documents and number of times each term conflicts with other topics. OnSI model of extracting features were compared with Naive Bayes classifier and k-Means clustering techniques, and the results are shown in Table 1.7.
Table 1.7 Performance evaluation.
| Technique | Recall | Accuracy | Time |
| Naive Bayes Classifier | 30% | 69% | 3.98 s |
| k-Means Clustering | 37% | 79% | 4.25 s |
| OnSI (Ontology-based CFSLDA) | 57% | 88% | 2.45 s |
