LSA model building for email classification
To create a SVM classifier that predicts in which class (interesting/uninteresting) incoming articles fall. The SVM algorithms is modelled using text concept features based on LSA or LDA.
We have used Latent Semantic Analysis (LSA) or Latent Dirichlet allocation (LDA) to get hidden concepts of text articles. We did this for articles a user have read (reads) and articles a user hasn’t read (unreads). We have used a Support Vector Machine (SVM) to create a classification model that can be used to predict in which class a new, incoming article falls.