Improving the Precision of Al-Quran Retrieval Using Latent Semantic Indexing with Background Knowledge

The aim of this study is to test the effectiveness of Al-Quran precision retrieval using LSI with background knowledge. The primary data used during the testing is the English translation of the Al-Quran where as the English translated hadith is used as the secondary data which acts as the background knowledge. SVD that is an LSI algorithm, indexes training data to be accessed by query. Experiments conducted are encircled around the two models i.e. LSI with the background knowledge and LSI without the background knowledge. The retrieval effectiveness is measured using the standard precision and recall measures