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» Learning Models for Ranking Aggregates
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KDD
2004
ACM
164views Data Mining» more  KDD 2004»
16 years 1 months ago
Ordering patterns by combining opinions from multiple sources
Pattern ordering is an important task in data mining because the number of patterns extracted by standard data mining algorithms often exceeds our capacity to manually analyze the...
Pang-Ning Tan, Rong Jin
153
Voted
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
13 years 3 months ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
112
Voted
SIGIR
2010
ACM
15 years 4 months ago
How good is a span of terms?: exploiting proximity to improve web retrieval
Ranking search results is a fundamental problem in information retrieval. In this paper we explore whether the use of proximity and phrase information can improve web retrieval ac...
Krysta Marie Svore, Pallika H. Kanani, Nazan Khan
97
Voted
AIRS
2010
Springer
14 years 11 months ago
Relevance Ranking Using Kernels
This paper is concerned with relevance ranking in search, particularly that using term dependency information. It proposes a novel and unified approach to relevance ranking using ...
Jun Xu, Hang Li, Chaoliang Zhong
99
Voted
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 1 months ago
Real-time ranking with concept drift using expert advice
In many practical applications, one is interested in generating a ranked list of items using information mined from continuous streams of data. For example, in the context of comp...
Hila Becker, Marta Arias