The article describes a method combining two widely-used empirical approaches to learning from examples: rule induction and instance-based learning. In our algorithm (RIONA) decisi...
In this report, we give a brief explanation of how RiMOM obtains the results at OAEI 2009 Campaign, especially in the new Instance Matching track. At first, we show the basic alig...
Xiao Zhang, Qian Zhong, Feng Shi, Juanzi Li, Jie T...
Matching dependencies were recently introduced as declarative rules for data cleaning and entity resolution. Enforcing a matching dependency on a database instance identifies the ...
Leopoldo E. Bertossi, Solmaz Kolahi, Laks V. S. La...
We introduce a theoretical framework for discovering relationships between two database instances over distinct and unknown schemata. This framework is grounded in the context of ...
Instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. Feature selection aims at the reduction of redundant features i...