Existing methods for single document keyphrase extraction usually make use of only the information contained in the specified document. This paper proposes to use a small number o...
Multimedia ranking algorithms are usually user-neutral and measure the importance and relevance of documents by only using the visual contents and meta-data. However, users’ int...
Liang Gou, Hung-Hsuan Chen, Jung-Hyun Kim, Xiaolon...
Document ranking is well known to be a crucial process in information retrieval (IR). It presents retrieved documents in an order of their estimated degrees of relevance to query. ...
This paper proposes an approach of extracting simple and effective features that enhances multilingual document ranking (MLDR). There is limited prior research on capturing the co...
Most learning to rank research has assumed that the utility of different documents is independent, which results in learned ranking functions that return redundant results. The fe...
Aleksandrs Slivkins, Filip Radlinski, Sreenivas Go...