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» Describing Semistructured Data
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ICML
2003
IEEE
16 years 7 months ago
Learning on the Test Data: Leveraging Unseen Features
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
Benjamin Taskar, Ming Fai Wong, Daphne Koller
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 7 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
KDD
2007
ACM
186views Data Mining» more  KDD 2007»
16 years 7 months ago
An Ad Omnia Approach to Defining and Achieving Private Data Analysis
We briefly survey several privacy compromises in published datasets, some historical and some on paper. An inspection of these suggests that the problem lies with the nature of the...
Cynthia Dwork
DEXA
2009
Springer
151views Database» more  DEXA 2009»
16 years 1 months ago
Automatic Extraction of Ontologies Wrapping Relational Data Sources
Describing relational data sources (i.e. databases) by means of ontologies constitutes the foundation of most of the semantic based approaches to data access and integration. In sp...
Lina Lubyte, Sergio Tessaris
165
Voted
DASFAA
2007
IEEE
187views Database» more  DASFAA 2007»
16 years 1 months ago
OntoDB: An Ontology-Based Database for Data Intensive Applications
Recently, several approaches and systems were proposed to store in the same database data and the ontologies describing their meanings. We call these databases, ontology-based data...
Dehainsala Hondjack, Guy Pierra, Ladjel Bellatrech...