Automatic Combination of Multiple Ranked Retrieval Systems

Abstract

Retrieval performance can often be improved significantly by using a number of different retrieval algorithms and combining the results, in contrast to using just a single retrieval algorithm. This is because different retrieval algorithms, or retrieval experts, often emphasize different document and query features when determining relevance and therefore retrieve different sets of documents. However, it is unclear how the different experts are to be combined, in general, to yield a superior overall estimate. We propose a method by which the relevance estimates made by different experts can be automatically combined to result in superior retrieval performance. We apply the method to two expert combination tasks. The applications demonstrate that the method can identify high performance combinations of experts and also is a novel means for determining the combined effectiveness of experts. 1 Introduction In text retrieval, two heads are definitely better than one. Retrieval performanc...