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» Patterns for decoupling data structures and algorithms
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SSPR
2004
Springer
14 years 29 days ago
Learning from General Label Constraints
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...
Tijl De Bie, Johan A. K. Suykens, Bart De Moor
ICDE
2003
IEEE
161views Database» more  ICDE 2003»
14 years 9 months ago
Structural Join Order Selection for XML Query Optimization
Structural join operations are central to evaluating queries against XML data, and are typically responsible for consuming a lion's share of the query processing time. Thus, ...
Yuqing Wu, Jignesh M. Patel, H. V. Jagadish
ACL
2011
12 years 11 months ago
Template-Based Information Extraction without the Templates
Standard algorithms for template-based information extraction (IE) require predefined template schemas, and often labeled data, to learn to extract their slot fillers (e.g., an ...
Nathanael Chambers, Dan Jurafsky
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
14 years 8 months ago
Mining data records in Web pages
A large amount of information on the Web is contained in regularly structured objects, which we call data records. Such data records are important because they often present the e...
Bing Liu, Robert L. Grossman, Yanhong Zhai
CVPR
2008
IEEE
14 years 9 months ago
Context-aware clustering
Most existing methods of semi-supervised clustering introduce supervision from outside, e.g., manually label some data samples or introduce constrains into clustering results. Thi...
Junsong Yuan, Ying Wu