Performance prediction of data fusion for information retrieval

The data fusion technique has been investigated by many researchers and has been used in implementing several information retrieval systems. However, the results from data fusion vary in different situations. To find out under which condition data fusion may lead to performance improvement is an important issue. In this paper, we present an analysis of the behaviour of several well-known methods such as CombSum and CombMNZ for fusion of multiple information retrieval results. Based on this analysis, we predict the performance of the data fusion methods. Experiments are conducted with three groups of results submitted to TREC 6, TREC 2001, and TREC 2004. The experiments show that the prediction of the performance of data fusion is quite accurate, and it can be used in situations very different from the training examples. Compared with previous work, our result is more accurate and in a better position for applications since various number of component systems can be supported while only two was used previously.