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» The maximum entropy method for analyzing retrieval measures
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SIGIR
2008
ACM
13 years 6 months ago
Directly optimizing evaluation measures in learning to rank
One of the central issues in learning to rank for information retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures used in i...
Jun Xu, Tie-Yan Liu, Min Lu, Hang Li, Wei-Ying Ma
3DIM
2005
IEEE
14 years 10 days ago
Transform-Based Methods for Indexing and Retrieval of 3D Objects
We compare two transform-based indexing methods for retrieval of 3D objects. We apply 3D Discrete Fourier Transform (DFT) and 3D Radial Cosine Transform (RCT) to the voxelized dat...
Helin Dutagaci, Bülent Sankur, Yücel Yem...
SIGIR
2000
ACM
13 years 11 months ago
Evaluating evaluation measure stability
: This paper presents a novel way of examining the accuracy of the evaluation measures commonly used in information retrieval experiments. It validates several of the rules-of-thum...
Chris Buckley, Ellen M. Voorhees
ISDA
2009
IEEE
14 years 1 months ago
Clustering-Based Feature Selection in Semi-supervised Problems
— In this contribution a feature selection method in semi-supervised problems is proposed. This method selects variables using a feature clustering strategy, using a combination ...
Ianisse Quinzán, José Manuel Sotoca,...
WWW
2008
ACM
14 years 7 months ago
Facetnet: a framework for analyzing communities and their evolutions in dynamic networks
We discover communities from social network data, and analyze the community evolution. These communities are inherent characteristics of human interaction in online social network...
Yu-Ru Lin, Yun Chi, Shenghuo Zhu, Hari Sundaram, B...