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» Magnitude-preserving ranking algorithms
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COMAD
2009
15 years 7 months ago
Vector-based Ranking Techniques for Identifying the Topical Anchors of a Context
Terms in textual documents tend to occur more in contexts to which they are related. We can exploit this bias by modelling terms and their cooccurrences s, resembling the abstract...
Aditya Ramana Rachakonda, Srinath Srinivasa
SIGIR
2010
ACM
15 years 6 months ago
Learning to rank query reformulations
Query reformulation techniques based on query logs have recently proven to be effective for web queries. However, when initial queries have reasonably good quality, these techniqu...
Van Dang, Michael Bendersky, W. Bruce Croft
CORR
2007
Springer
129views Education» more  CORR 2007»
15 years 6 months ago
A Rank-Metric Approach to Error Control in Random Network Coding
It is shown that the error control problem in random network coding can be reformulated as a generalized decoding problem for rank-metric codes. This result allows many of the too...
Danilo Silva, Frank R. Kschischang, Ralf Koetter
CIKM
2010
Springer
15 years 4 months ago
Context modeling for ranking and tagging bursty features in text streams
Bursty features in text streams are very useful in many text mining applications. Most existing studies detect bursty features based purely on term frequency changes without takin...
Wayne Xin Zhao, Jing Jiang, Jing He, Dongdong Shan...
CORR
2011
Springer
209views Education» more  CORR 2011»
14 years 10 months ago
Analysis and Improvement of Low Rank Representation for Subspace segmentation
We analyze and improve low rank representation (LRR), the state-of-the-art algorithm for subspace segmentation of data. We prove that for the noiseless case, the optimization mode...
Siming Wei, Zhouchen Lin