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SIGIR
2012
ACM
11 years 10 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
ICDE
2009
IEEE
170views Database» more  ICDE 2009»
14 years 9 months ago
Semantics of Ranking Queries for Probabilistic Data and Expected Ranks
Abstract-- When dealing with massive quantities of data, topk queries are a powerful technique for returning only the k most relevant tuples for inspection, based on a scoring func...
Graham Cormode, Feifei Li, Ke Yi
ADHOC
2004
134views more  ADHOC 2004»
13 years 7 months ago
Scalable team multicast in wireless ad hoc networks exploiting coordinated motion
In this paper, we study a new multicast paradigm for large scale mobile ad hoc networks, namely team multicast. In team multicast the multicast group does not consist of individua...
Yunjung Yi, Mario Gerla, Katia Obraczka
ILP
2003
Springer
14 years 27 days ago
Disjunctive Learning with a Soft-Clustering Method
In the case of concept learning from positive and negative examples, it is rarely possible to find a unique discriminating conjunctive rule; in most cases, a disjunctive descripti...
Guillaume Cleuziou, Lionel Martin, Christel Vrain
JAIR
2008
173views more  JAIR 2008»
13 years 7 months ago
Creating Relational Data from Unstructured and Ungrammatical Data Sources
In order for agents to act on behalf of users, they will have to retrieve and integrate vast amounts of textual data on the World Wide Web. However, much of the useful data on the...
Matthew Michelson, Craig A. Knoblock