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» Discovering Test Set Regularities in Relational Domains
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ICML
2009
IEEE
15 years 10 months ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel
JASIS
2008
121views more  JASIS 2008»
14 years 10 months ago
Experiments with transitive dictionary translation and pseudo-relevance feedback using graded relevance assessments
Research on cross-language information retrieval (CLIR) has typically been restricted to settings using binary relevance assessments. In this paper, we present evaluation results f...
Raija Lehtokangas, Heikki Keskustalo, Kalervo J&au...
ADMA
2006
Springer
150views Data Mining» more  ADMA 2006»
15 years 4 months ago
Web Scale Competitor Discovery Using Mutual Information
Abstract. The web with its rapid expansion has become an excellent resource for gathering information and people’s opinion. A company owner wants to know who is the competitor, a...
Rui Li, Shenghua Bao, Jin Wang, Yuanjie Liu, Yong ...
AAAI
1990
14 years 11 months ago
Approximation Reformulations
Although computers are widely used to simulate complex physical systems, crafting the underlying models that enable computer analysis remains difficult. When a model is created fo...
Daniel S. Weld
CICLING
2005
Springer
15 years 3 months ago
A Machine Learning Approach to Information Extraction
Information extraction is concerned with applying natural language processing to automatically extract the essential details from text documents. A great disadvantage of current ap...
Alberto Téllez-Valero, Manuel Montes-y-G&oa...