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» Magnitude-preserving ranking algorithms
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KDD
2005
ACM
143views Data Mining» more  KDD 2005»
16 years 6 months ago
SVM selective sampling for ranking with application to data retrieval
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
Hwanjo Yu
SIGIR
2010
ACM
15 years 10 months ago
Context-aware ranking in web search
The context of a search query often provides a search engine meaningful hints for answering the current query better. Previous studies on context-aware search were either focused ...
Biao Xiang, Daxin Jiang, Jian Pei, Xiaohui Sun, En...
TREC
2003
15 years 7 months ago
Ranking Function Discovery by Genetic Programming for Robust Retrieval
Ranking functions are instrumental for the success of an information retrieval (search engine) system. However nearly all existing ranking functions are manually designed based on...
Li Wang, Weiguo Fan, Rui Yang, Wensi Xi, Ming Luo,...
ICWS
2009
IEEE
16 years 3 months ago
What are the Problem Makers: Ranking Activities According to their Relevance for Process Changes
Recently, a new generation of adaptive process management technology has emerged, which enables dynamic changes of composite services and process models respectively. This, in tur...
Chen Li, Manfred Reichert, Andreas Wombacher
ICML
2008
IEEE
16 years 6 months ago
Query-level stability and generalization in learning to rank
This paper is concerned with the generalization ability of learning to rank algorithms for information retrieval (IR). We point out that the key for addressing the learning proble...
Yanyan Lan, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang...