Ranking is a key problem in many information retrieval (IR) applications, such as document retrieval and collaborative filtering. In this paper, we address the issue of learning ...
Label ranking is the task of inferring a total order over a predefined set of labels for each given instance. We present a general framework for batch learning of label ranking f...
Machine-learned ranking techniques automatically learn a complex document ranking function given training data. These techniques have demonstrated the effectiveness and flexibilit...
Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, ...
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...