Differential evolution-based fusion for results diversification of web search

Abstract

Results diversification has been a key research issue on web search in the last couple of years. Some recent research work suggests that data fusion, especially linear combination of multiple results, is a good option of dealing with this problem. However, there are many different ways of setting weights. In this paper, we propose a differential evolution-based method to find optimal weights in the weight space for the linear combination method. Experimental results show that the proposed method is effective compared with the state-of-the-art techniques.