Intelligent Information Retrieval Approach using Discrete Wavelet Transform for Holy Quran in Smartphone Application

Abstract

Answering mobile users’ queries intelligently is one of the significant challenges in information retrieval (IR) in intelligent systems. Current popular Quranic retrieval application ranks the document by counting the occurrences of each of the terms and ignoring any other information in the document to solve the Verses of Quran retrieval problem. Considering the proximity between the query terms assists in the efficiency of ranking results and increases IR performance. The Spectral-Based Information Retrieval Model (SBIRM) considers the query terms’ proximity by examining the term patterns that occur in the documents. To do this, SBIRM utilizes term signal representation and discrete wavelet transform (DWT). In this paper, we solve the Verses of Quran retrieval problem by proposing a novel document model, termed the Dynamic Document Model with Discrete Wavelet Transforms (DDMDWT). The DDMDWT exploits the variations in Verses of Quran length and mathematical transforms for document representation. The proposed model will enhance the existing term signal concept by additionally taking into consideration differing lengths of Verses of Quran. We designed and implemented an intelligent Quranic retrieval (IQR) Android application. In this IQR, the DDMDWT model contributes to reducing the time complexity of SBIRM and decreasing the index size by 20.98%, all while achieving improvement in precision, recall, F-measure, and MAP with compared to SBIRM. This paper also demonstrates how the DDMDWT model delivers a notable increase in the precision of the P@1 and P@3.