Thesis supervisor: Attila Tasnádi
Location of studies (in Hungarian): CUB Abbreviation of location of studies: BCE
Description of the research topic:
The applications of voting rules are extended to new areas in management science, computer science, artificial intelligence and expert systems. Analogous to standard voting situations are for instance the ranking of cities based on their attractiveness, automated decision making, or the ranking of figure skaters by judges. Surprisingly, only Dwork et al. (2002) started the work on rankings based on partial lists of voters in which the unranked alternatives are not treated as lowest ranked alternatives. This problem is essential for ranking algorithms for the World Wide Web (like the PageRank algorithm). The mentioned aggregation problem is a problem of ranking under incomplete information for which quite a number of methods are available. We compare and investigate the relationship between these alternative methods and apply them to real-life problems.