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CIKM
2010
Springer
13 years 5 months ago
Online learning for recency search ranking using real-time user feedback
Traditional machine-learned ranking algorithms for web search are trained in batch mode, which assume static relevance of documents for a given query. Although such a batch-learni...
Taesup Moon, Lihong Li, Wei Chu, Ciya Liao, Zhaohu...
GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
13 years 7 months ago
Fitness importance for online evolution
To complement standard fitness functions, we propose "Fitness Importance" (FI) as a novel meta-heuristic for online learning systems. We define FI and show how it can be...
Philip Valencia, Raja Jurdak, Peter Lindsay
WWW
2009
ACM
14 years 7 months ago
Learning to recognize reliable users and content in social media with coupled mutual reinforcement
Community Question Answering (CQA) has emerged as a popular forum for users to pose questions for other users to answer. Over the last few years, CQA portals such as Naver and Yah...
Jiang Bian, Yandong Liu, Ding Zhou, Eugene Agichte...
TCS
2002
13 years 6 months ago
A unified language processing methodology
This paper discusses a mathematical concept of language that models both artificial and natural languages and thus provides a framework for a unified language processing methodolo...
Teodor Rus
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 7 months ago
Practical learning from one-sided feedback
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
D. Sculley