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WSDM
2010
ACM
266views Data Mining» more  WSDM 2010»
15 years 7 months ago
Gathering and Ranking Photos of Named Entities with High Precision, High Recall, and Diversity
Knowledge-sharing communities like Wikipedia and automated extraction methods like those of DBpedia enable the construction of large machine-processible knowledge bases with relat...
Bilyana Taneva, Mouna Kacimi, Gerhard Weikum
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
13 years 5 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...
ILP
1999
Springer
15 years 2 months ago
Probabilistic Relational Models
Most real-world data is heterogeneous and richly interconnected. Examples include the Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning...
Daphne Koller
NIPS
2008
14 years 11 months ago
Inferring rankings under constrained sensing
Motivated by applications like elections, web-page ranking, revenue maximization etc., we consider the question of inferring popular rankings using constrained data. More specific...
Srikanth Jagabathula, Devavrat Shah
ESANN
2007
14 years 11 months ago
Mixtures of robust probabilistic principal component analyzers
Mixtures of probabilistic principal component analyzers model high-dimensional nonlinear data by combining local linear models. Each mixture component is specifically designed to...
Cédric Archambeau, Nicolas Delannay, Michel...