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ICPR
2006
IEEE
14 years 8 months ago
Scalable Representative Instance Selection and Ranking
Finding a small set of representative instances for large datasets can bring various benefits to data mining practitioners so they can (1) build a learner superior to the one cons...
Xindong Wu, Xingquan Zhu
AAAI
2004
13 years 8 months ago
Error Detection and Impact-Sensitive Instance Ranking in Noisy Datasets
Given a noisy dataset, how to locate erroneous instances and attributes and rank suspicious instances based on their impacts on the system performance is an interesting and import...
Xingquan Zhu, Xindong Wu, Ying Yang
SIGIR
2010
ACM
13 years 11 months ago
Multilabel classification with meta-level features
Effective learning in multi-label classification (MLC) requires an ate level of abstraction for representing the relationship between each instance and multiple categories. Curren...
Siddharth Gopal, Yiming Yang
COLING
2010
13 years 2 months ago
The Role of Queries in Ranking Labeled Instances Extracted from Text
A weakly supervised method uses anonymized search queries to induce a ranking among class labels extracted from unstructured text for various instances. The accuracy of the extrac...
Marius Pasca
WSDM
2009
ACM
104views Data Mining» more  WSDM 2009»
14 years 2 months ago
Top-k aggregation using intersections of ranked inputs
There has been considerable past work on efficiently computing top k objects by aggregating information from multiple ranked lists of these objects. An important instance of this...
Ravi Kumar, Kunal Punera, Torsten Suel, Sergei Vas...