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WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
12 years 4 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...
ICML
2008
IEEE
14 years 9 months ago
Optimizing estimated loss reduction for active sampling in rank learning
Learning to rank is becoming an increasingly popular research area in machine learning. The ranking problem aims to induce an ordering or preference relations among a set of insta...
Pinar Donmez, Jaime G. Carbonell
EWCBR
2004
Springer
14 years 1 months ago
Improving Recommendation Ranking by Learning Personal Feature Weights
The ranking of offers is an issue in e-commerce that has received a lot of attention in Case-Based Reasoning research. In the absence of a sales assistant, it is important to provi...
Lorcan Coyle, Padraig Cunningham
ACL
2009
13 years 6 months ago
Graph Ranking for Sentiment Transfer
With the aim to deal with sentiment-transfer problem, we proposed a novel approach, which integrates the sentiment orientations of documents into the graph-ranking algorithm. We a...
Qiong Wu, Songbo Tan, Xueqi Cheng
ICASSP
2011
IEEE
13 years 9 days ago
Emotion classification from speech using evaluator reliability-weighted combination of ranked lists
In emotion recognition, a widely-used method to reconciliate disagreement between multiple human evaluators is to perform majority-voting on their assigned class labels. Instead, ...
Kartik Audhkhasi, Shrikanth S. Narayanan