Biomedical researchers rely on keyword-based search engines to retrieve superficially relevant documents, from which they must filter out irrelevant information manually. Hence, t...
Richard Tzong-Han Tsai, Hong-Jie Dai, Hsi-Chuan Hu...
This paper presents a new pooling method for constructing the assessment sets used in the evaluation of retrieval systems. Our proposal is based on RankBoost, a machine learning v...
Planning problems are often formulated as heuristic search. The choice of the heuristic function plays a significant role in the performance of planning systems, but a good heuris...
This paper describes an efficient reduction of the learning problem of ranking to binary classification. The reduction guarantees an average pairwise misranking regret of at most t...
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...