This paper uncovers a new phenomenon in web search that we call domain bias — a user’s propensity to believe that a page is more relevant just because it comes from a particul...
Samuel Ieong, Nina Mishra, Eldar Sadikov, Li Zhang
Finding topic experts on microblogging sites with millions of users, such as Twitter, is a hard and challenging problem. In this paper, we propose and investigate a new methodolog...
In this paper, we cast the image-ranking problem into the task of identifying "authority" nodes on an inferred visual similarity graph and propose an algorithm to analyz...
Users often try to accumulate information on a topic of interest from multiple information sources. In this case a user's informational need might be expressed in terms of an...
Current search engines rely on centralized page ranking algorithms which compute page rank values as single (global) values for each Web page. Recent work on topic-sensitive PageRa...
Paul-Alexandru Chirita, Daniel Olmedilla, Wolfgang...