Time-aware and trend-based authority ranking

This thesis devises time-aware and trend-based ranking techniques. The time-aware techniques exploit temporal information, present in networks like the World Wide Web, to produce rankings reflecting authority with regard to a temporal interest. The trendbased techniques produce rankings based on the relative change of authority with regard to a temporal interest. We describe mathematics behind the approaches and review efforts having related aims. On this basis, two time-aware and two trend-based methods are proposed. The time-aware methods extend PageRank and are defined incrementally. The trend-based methods are defined independently, one extending PageRank and the other based on a comparison of precomputed authority rankings. The methods were implemented in a prototype system using Java and extensively evaluated in a series of experiments on bibliographic and Web data. Results on the bibliographic data indicate that the methods produce meaningful rankings. Moreover, a user study, examining results obtained on Web data, gives strong evidence that the resulting rankings are preferred by the users and closer to their expectations.