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» Learning to rank for information retrieval
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WWW
2004
ACM
14 years 8 months ago
Random surfer with back step
We present a novel link-based ranking algorithm RBS, which may be viewed as an extension of PageRank by back-step feature. Categories and Subject Descriptors H.3.3 [Information Se...
Marcin Sydow
WWW
2010
ACM
13 years 11 months ago
Diversifying landmark image search results by learning interested views from community photos
In this paper, we demonstrate a novel landmark photo search and browsing system, Agate, which ranks landmark image search results considering their relevance, diversity and qualit...
Yuheng Ren, Mo Yu, Xin-Jing Wang, Lei Zhang, Wei-Y...
IR
2007
13 years 7 months ago
Regularizing query-based retrieval scores
In information retrieval, the cluster hypothesis states: closely related documents tend to be relevant to the same request. We exploit this hypothesis directly by adjusting queryb...
Fernando Diaz
GIR
2006
ACM
14 years 1 months ago
Relevance Ranking for Geographic IR
In this paper, we introduce a geographic similarity operator that computes the relatedness between two geographic places and describe how it is combined with textual ranking. The ...
Leonardo Andrade, Mário J. Silva
KDD
2002
ACM
169views Data Mining» more  KDD 2002»
14 years 8 months ago
Optimizing search engines using clickthrough data
This paper presents an approach to automatically optimizing the retrieval quality of search engines using clickthrough data. Intuitively, a good information retrieval system shoul...
Thorsten Joachims