We describe a new family of topic-ranking algorithms for multi-labeled documents. The motivation for the algorithms stems from recent advances in online learning algorithms. The a...
The assumptions underlying the Probability Ranking Principle (PRP) have led to a number of alternative approaches that cater or compensate for the PRP’s limitations. In this pos...
Guido Zuccon, Leif Azzopardi, C. J. van Rijsbergen
We present a simulation model used to evaluate a distributed search engine by modelling its performance. The model is designed to aid performance-driven evolution of the system. W...
Thomas Phelan, Ahmed Patel, Seamus O. Ciardhu&aacu...
In this paper, we demonstrate a novel landmark photo search and browsing system, Agate, which ranks landmark image search results considering their relevance, diversity and qualit...
Yuheng Ren, Mo Yu, Xin-Jing Wang, Lei Zhang, Wei-Y...
We present an algorithm which partitions a data set in two parts with equal size and experimentally nearly the same distribution measured through the likelihood of a Parzen kernel ...