In this paper we propose a novel algorithm called Rank-Based Broadcast (RBB) for discovery of local resources in mobile P2P networks. With RBB, each moving object periodically bro...
In this paper we demonstrate that in an ideal Distributed Information Retrieval environment, taking the ability of each collection server to return relevant documents into account...
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...
The purpose of this paper is to apply and evaluate the bibliometric method Bradfordizing for information retrieval (IR) experiments. Bradfordizing is used for generating core docu...
We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...