Improving the User Query for the Boolean Model Using Genetic Algorithms

TL;DR

This paper explores optimizing user queries in Arabic information retrieval using genetic algorithms, focusing on the Boolean model and identifying the most effective strategies and fitness functions.

Contribution

It introduces a novel application of genetic algorithms to optimize Boolean queries specifically for Arabic data collections, an area with limited prior research.

Findings

GA (M2, Precision) is the most effective strategy.

Optimized queries improve retrieval precision.

Study advances Arabic IR query optimization techniques.

Abstract

The Use of genetic algorithms in the Information retrieval (IR) area, especially in optimizing a user query in Arabic data collections is presented in this paper. Very little research has been carried out on Arabic text collections. Boolean model have been used in this research. To optimize the query using GA we used different fitness functions, different mutation strategies to find which is the best strategy and fitness function that can be used with Boolean model when the data collection is the Arabic language. Our results show that the best GA strategy for the Boolean model is the GA (M2, Precision) method.