HITS based network algorithm for evaluating the professional skills of wine tasters

Abstract

Two popular and widely used webpage ranking algorithms are PageRank and HITS. We considered the 2009 Szeged Wine Fest data and another reliable data set of wines from the famous region Villány and, on basis of each data set, constructed a directed and weighted bipartite graph of wine tasters and wines. We applied an extended version of PageRank and HITS, the Co-HITS algorithm to wine tasting graph in order to rank tasters according to their ability and professional skill. The results of our technique were compared to other simple statistical methods. In general we observed that our ranking method performed better: it can filter out incompetent tasters, who, for example, gave the average score of some other tasters for the wines she or he tasted. Furthermore, our method gives a clearer picture about the competence of wine tasters.