The document discusses using a genetic algorithm and machine learning classifier to select good expansion terms for improving query results. A genetic algorithm is trained using average precision as the fitness function to select expansion term combinations. A term classifier is then trained on the selected terms to classify new candidate terms without needing user relevance judgments. The classifier approach improved results by 18.9% compared to the baseline, demonstrating the potential of this method for automatic query expansion.