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» Ranking Retrieval Systems with Partial Relevance Judgements
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SIGIR
2012
ACM
13 years 3 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
SIGIR
2008
ACM
15 years 1 months ago
Relevance judgments between TREC and Non-TREC assessors
This paper investigates the agreement of relevance assessments between official TREC judgments and those generated from an interactive IR experiment. Results show that 63% of docu...
Azzah Al-Maskari, Mark Sanderson, Paul Clough
BIBE
2008
IEEE
109views Bioinformatics» more  BIBE 2008»
15 years 7 months ago
Retrieval and ranking of biomedical images using boosted haar features
— Retrieving similar images from large repository of heterogeneous biomedical images has been a difficult research task. In this paper, we develop a retrieval system that uses H...
Chandan K. Reddy, Fahima A. Bhuyan
SIGIR
2006
ACM
15 years 7 months ago
Learning a ranking from pairwise preferences
We introduce a novel approach to combining rankings from multiple retrieval systems. We use a logistic regression model or an SVM to learn a ranking from pairwise document prefere...
Ben Carterette, Desislava Petkova
CIKM
2001
Springer
15 years 5 months ago
Evaluating Document Clustering for Interactive Information Retrieval
We consider the problem of organizing and browsing the top ranked portion of the documents returned by an information retrieval system. We study the effectiveness of a document o...
Anton Leuski