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» Learning to Rank Using an Ensemble of Lambda-Gradient Models
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KDD
2009
ACM
245views Data Mining» more  KDD 2009»
14 years 8 months ago
Mining rich session context to improve web search
User browsing information, particularly their non-search related activity, reveals important contextual information on the preferences and the intent of web users. In this paper, ...
Guangyu Zhu, Gilad Mishne
WSDM
2010
ACM
160views Data Mining» more  WSDM 2010»
14 years 5 months ago
Learning Concept Importance Using a Weighted Dependence Model
Modeling query concepts through term dependencies has been shown to have a significant positive effect on retrieval performance, especially for tasks such as web search, where rel...
Michael Bendersky, Donald Metzler, W. Bruce Croft
ICDE
2011
IEEE
200views Database» more  ICDE 2011»
12 years 11 months ago
Deriving probabilistic databases with inference ensembles
— Many real-world applications deal with uncertain or missing data, prompting a surge of activity in the area of probabilistic databases. A shortcoming of prior work is the assum...
Julia Stoyanovich, Susan B. Davidson, Tova Milo, V...
ML
2010
ACM
141views Machine Learning» more  ML 2010»
13 years 6 months ago
Relational retrieval using a combination of path-constrained random walks
Scientific literature with rich metadata can be represented as a labeled directed graph. This graph representation enables a number of scientific tasks such as ad hoc retrieval o...
Ni Lao, William W. Cohen
MM
2006
ACM
181views Multimedia» more  MM 2006»
14 years 1 months ago
Towards content-based relevance ranking for video search
Most existing web video search engines index videos by file names, URLs, and surrounding texts. These types of video roughly describe the whole video in an abstract level without ...
Wei Lai, Xian-Sheng Hua, Wei-Ying Ma