Journal

A Framework for Efficient Document Ranking Using Order and Non-Order Based Fitness Function

This paper explores the use of Genetic Algorithms (GAs) to enhance information retrieval by optimizing similarity measures. A combined similarity measure was defined, with GAs learning optimal weights for its components. Both order-based and non-order-based fitness functions were evaluated, showing that incorporating retrieval order improves performance. Experiments on TREC data demonstrated the effectiveness of this approach compared to traditional similarity measures.