Enhancing Thematic Holy Quran Verse Retrieval through Vector Space Model and Query Expansion for Effective Query Answering

The Quran provides valuable insights into various aspects of life, including information about the natural world, such as animals and plants. Developing an information retrieval system can greatly facilitate the search for specific content within the Quran. This system utilizes a cosine similarity approach and query expansion techniques to rank and expand the retrieved documents according to the user's needs. In this research, the Term Frequency-Inverse Document Frequency (TF-IDF) weighting method is employed, following preprocessing steps for both the documents and queries. The primary objectives of this study are to assess accuracy, precision, and recall values. Notably, the inclusion of query expansion has led to an improved recall value compared to previous research, resulting in a 99.32% accuracy rate, a 5.83% increase in precision (from 83.93%), and a system's ability to capture 8.75% of the relevant verse (compared to the previous 93.51%). This signifies that all verses can be invoked, displayed, or expanded, providing a more comprehensive query experience.