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» Ranking queries on uncertain data
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WWW
2006
ACM
14 years 8 months ago
A pruning-based approach for supporting Top-K join queries
An important issue arising from large scale data integration is how to efficiently select the top-K ranking answers from multiple sources while minimizing the transmission cost. T...
Jie Liu, Liang Feng, Yunpeng Xing
SIGIR
2003
ACM
14 years 24 days ago
Exploiting query history for document ranking in interactive information retrieval
In this poster,we incorporate user query history, as context information, to improve the retrieval performance in interactive retrieval. Experiments using the TREC data show that ...
Xuehua Shen, ChengXiang Zhai
AIRS
2010
Springer
13 years 5 months ago
Learning to Rank with Supplementary Data
This paper is concerned with a new task of ranking, referred to as "supplementary data assisted ranking", or "supplementary ranking" for short. Different from c...
Wenkui Ding, Tao Qin, Xu-Dong Zhang
EDBT
2011
ACM
256views Database» more  EDBT 2011»
12 years 11 months ago
RanKloud: a scalable ranked query processing framework on hadoop
The popularity of batch-oriented cluster architectures like Hadoop is on the rise. These batch-based systems successfully achieve high degrees of scalability by carefully allocati...
K. Selçuk Candan, Parth Nagarkar, Mithila N...
SIGMOD
2011
ACM
219views Database» more  SIGMOD 2011»
12 years 10 months ago
Context-sensitive ranking for document retrieval
We study the problem of context-sensitive ranking for document retrieval, where a context is defined as a sub-collection of documents, and is specified by queries provided by do...
Liang Jeff Chen, Yannis Papakonstantinou