In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Though children frequently use web search engines to learn, interact, and be entertained, modern web search engines are poorly suited to children's needs, requiring relativel...
Personalization of web search results as a technique for improving user satisfaction has received notable attention in the research community over the past decade. Much of this wo...
In this paper, we attempt to improve the effectiveness and the efficiency of query-dependent link-based ranking algorithms such as HITS, MAX and SALSA. All these ranking algorith...
Background: Finding relevant articles from PubMed is challenging because it is hard to express the user’s specific intention in the given query interface, and a keyword query ty...
Hwanjo Yu, Taehoon Kim, Jinoh Oh, Ilhwan Ko, Sungc...