| 摘要 |
Methods to enable optimization of discontinuous rank metrics are described. The search scores associated with a number of search objects are written as score distributions and these are converted into rank distributions for each object in an iterative process. Each object is selected in turn and the score distribution of the selected object is compared to the score distributions of each other object in turn to generate a probability that the selected object is ranked in a particular position. For example, with three documents the rank distribution may give a 20% probability that a document is ranked first, a 60% probability that the document is ranked second and a 20% probability that the document is ranked third. In some embodiments, the rank distributions may then be used in the optimization of discontinuous rank metrics.
|
