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» Label Ranking Methods based on the Plackett-Luce Model
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ICTAI
2006
IEEE
15 years 5 months ago
Improve Decision Trees for Probability-Based Ranking by Lazy Learners
Existing work shows that classic decision trees have inherent deficiencies in obtaining a good probability-based ranking (e.g. AUC). This paper aims to improve the ranking perfor...
Han Liang, Yuhong Yan
CVPR
2009
IEEE
16 years 6 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
CISIS
2010
IEEE
15 years 5 months ago
iweightings: Enhancing Structure-based Ontology Alignment by Enriching Models with Importance Weighting
—Structural ontology matching methods analyze mainly two factors: entity labels and relationships among entities. We propose to additionally consider an importance and relevance ...
Alexandra Mazak, Bernhard Schandl, Monika Lanzenbe...
114
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SEMWEB
2009
Springer
15 years 6 months ago
TripleRank: Ranking Semantic Web Data by Tensor Decomposition
Abstract. The Semantic Web fosters novel applications targeting a more efficient and satisfying exploitation of the data available on the web, e.g. faceted browsing of linked open...
Thomas Franz, Antje Schultz, Sergej Sizov, Steffen...
RSFDGRC
2005
Springer
110views Data Mining» more  RSFDGRC 2005»
15 years 5 months ago
A Rough Set Based Model to Rank the Importance of Association Rules
Abstract. Association rule algorithms often generate an excessive number of rules, many of which are not significant. It is difficult to determine which rules are more useful, int...
Jiye Li, Nick Cercone