In this paper, we present an extensible approach to the adaptation of Web information delivery according to different and possibly heterogeneous contexts. The approach is based o...
Recent work on language models for information retrieval has shown that smoothing language models is crucial for achieving good retrieval performance. Many different effective smo...
Companies, government agencies, and other organizations are making their data available to the world over the Internet. They often use large online relational tables for this purp...
Traditional boosting algorithms for the ranking problems usually employ the pairwise approach and convert the document rating preference into a binary-value label, like RankBoost....
Chenguang Zhu, Weizhu Chen, Zeyuan Allen Zhu, Gang...
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...