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» Maximum Margin Ranking Algorithms for Information Retrieval
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CLEF
2005
Springer
14 years 1 months ago
CLEF 2005: Multilingual Retrieval by Combining Multiple Multilingual Ranked Lists
: We participated in two tasks: Multi-8 two-years-on retrieval and Multi-8 results merging. For our multi-8 two-years-on retrieval work, simple multilingual ranked lists are first ...
Luo Si, Jamie Callan
SIGIR
2012
ACM
11 years 10 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
WWW
2007
ACM
14 years 8 months ago
A cautious surfer for PageRank
This work proposes a novel cautious surfer to incorporate trust into the process of calculating authority for web pages. We evaluate a total of sixty queries over two large, real-...
Lan Nie, Baoning Wu, Brian D. Davison
SIGMOD
2009
ACM
111views Database» more  SIGMOD 2009»
14 years 7 months ago
Language-model-based ranking in entity-relation graphs
We propose a language-model-based ranking approach for SPARQLlike queries on entity-relationship graphs. Our ranking model supports exact matching, approximate structure matching,...
Shady Elbassuoni, Maya Ramanath, Gerhard Weikum
CIKM
2011
Springer
12 years 7 months ago
A probabilistic method for inferring preferences from clicks
Evaluating rankers using implicit feedback, such as clicks on documents in a result list, is an increasingly popular alternative to traditional evaluation methods based on explici...
Katja Hofmann, Shimon Whiteson, Maarten de Rijke