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A topic (or feature) is a duplet <F, T>, F is the set of features of the domain and T is the candidate set of terms representing F. CFSLDA model selects T = {tc | tc is correlated with tp}, where tp is the higher probable term of F selected by the model. The contextual relationship between this duplet is represented by the triplet <F, T, M>, where M represents the mapping between F and T. The Ontology development or update procedure is shown:

Ontology tree is constructed with different levels for each <F, T> such that F forms the higher level, and T forms the next level for the corresponding F, as shown in Figure 1.9.

Figure 1.9 Domain ontology modeling for features.

The LDA weight of each term is included in the Ontology representation. Ontology is used to construct the index through concept reasoning.