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SIGIR
2010
ACM
15 years 9 months ago
Positional relevance model for pseudo-relevance feedback
Pseudo-relevance feedback is an effective technique for improving retrieval results. Traditional feedback algorithms use a whole feedback document as a unit to extract words for ...
Yuanhua Lv, ChengXiang Zhai
COLT
2005
Springer
15 years 11 months ago
Analysis of Perceptron-Based Active Learning
We start by showing that in an active learning setting, the Perceptron algorithm needs Ω( 1 ε2 ) labels to learn linear separators within generalization error ε. We then prese...
Sanjoy Dasgupta, Adam Tauman Kalai, Claire Montele...
PVLDB
2010
104views more  PVLDB 2010»
15 years 4 months ago
MCDB-R: Risk Analysis in the Database
Enterprises often need to assess and manage the risk arising from uncertainty in their data. Such uncertainty is typically modeled as a probability distribution over the uncertain...
Peter J. Haas, Christopher M. Jermaine, Subi Arumu...
VLDB
2002
ACM
138views Database» more  VLDB 2002»
15 years 5 months ago
Adaptable Similarity Search using Non-Relevant Information
Many modern database applications require content-based similarity search capability in numeric attribute space. Further, users' notion of similarity varies between search se...
T. V. Ashwin, Rahul Gupta, Sugata Ghosal
SIGIR
2012
ACM
13 years 8 months ago
Content-based retrieval for heterogeneous domains: domain adaptation by relative aggregation points
We introduce the problem of domain adaptation for content-based retrieval and propose a domain adaptation method based on relative aggregation points (RAPs). Content-based retriev...
Makoto P. Kato, Hiroaki Ohshima, Katsumi Tanaka