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» A New Email Retrieval Ranking Approach
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WWW
2008
ACM
14 years 10 months ago
Learning to rank relational objects and its application to web search
Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
WWW
2007
ACM
14 years 10 months ago
Dynamic personalized pagerank in entity-relation graphs
Extractors and taggers turn unstructured text into entityrelation (ER) graphs where nodes are entities (email, paper, person, conference, company) and edges are relations (wrote, ...
Soumen Chakrabarti
PVLDB
2010
108views more  PVLDB 2010»
13 years 8 months ago
Retrieving Top-k Prestige-Based Relevant Spatial Web Objects
The location-aware keyword query returns ranked objects that are near a query location and that have textual descriptions that match query keywords. This query occurs inherently i...
Xin Cao, Gao Cong, Christian S. Jensen
CIKM
2009
Springer
14 years 4 months ago
A general magnitude-preserving boosting algorithm for search ranking
Traditional boosting algorithms for the ranking problems usually employ the pairwise approach and convert the document rating preference into a binary-value label, like RankBoost....
Chenguang Zhu, Weizhu Chen, Zeyuan Allen Zhu, Gang...
WSDM
2010
ACM
210views Data Mining» more  WSDM 2010»
14 years 7 months ago
Towards Recency Ranking in Web Search
In web search, recency ranking refers to ranking documents by relevance which takes freshness into account. In this paper, we propose a retrieval system which automatically detect...
Anlei Dong, Yi Chang, Zhaohui Zheng, Gilad Mishne,...