Large-scale collective entity matchingLarge-scale collective entity matching Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2015-11-302009enThere have been several recent advancements in Machine Learning community on the Entity Matching (EM) problem. However, their lack of scalability has prevented them from being applied in practical settings on large real-life datasets. Towards this end, we propose a principled framework to scale any generic EM algorithm. Our technique consists of running multiple instances of the EM algorithm on small neighborhoods of the data and passing messages across neighborhoods to construct a global solution. We prove formal properties of our framework and experimentally demonstrate the effectiveness of our approach in scaling EM algorithms.http://creativecommons.org/licenses/by/4.0/35th International Conference on Very Large Data Bases Rastogi Vibhor Dalvi Nilesh Garofalakis Minos Γαροφαλακης Μινως Association for Computing Machinery Database management