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Semantic indexing module builds indexer for the review documents with the support of CFS_LDA model. The topic modeling technique CFS_LDA is used in the feature selection process to extract the features (or topics) and their related terms. Those terms that are grouped under the same topic are selected and tagged to represent the features of domain (or concept). Finally, the index is built using the keywords representing the features and feature terms with their context.

Definition 1: Context is defined as a triplet < F, T, M >. F is the set of features, T is set of terms and their LDA scores, and M is the relationship between T and F, known as Ontology mapping. In other words, T is the set of terms used to describe F features of concept. Their contextual relationship is identified by M, a mapping function between T and F using the score.