This paper experimentally studies approaches to the problem of ranking information resources w.r.t. user queries in peer-to-peer information retrieval. In distributed environments...
This paper studies document ranking under uncertainty. It is tackled in a general situation where the relevance predictions of individual documents have uncertainty, and are depen...
In this paper, we propose a Bayesian learning approach to promoting diversity for information retrieval in biomedicine and a re-ranking model to improve retrieval performance in t...
We introduce a multi-stage ensemble framework, ErrorDriven Generalist+Expert or Edge, for improved classification on large-scale text categorization problems. Edge first trains a ...
Social tagging is becoming increasingly popular in many Web 2.0 applications where users can annotate resources (e.g. Web pages) with arbitrary keywords (i.e. tags). A tag recomme...
Ziyu Guan, Jiajun Bu, Qiaozhu Mei, Chun Chen, Can ...