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Large-scale collective entity matching

Rastogi Vibhor, Dalvi Nilesh, Garofalakis Minos

Απλή Εγγραφή

URIhttp://purl.tuc.gr/dl/dias/284C74C9-4024-4E15-9E13-754BFF15CE0D-
Αναγνωριστικόhttp://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.190.2980&rep=rep1&type=pdf-
Αναγνωριστικόhttps://doi.org/10.14778/1938545.1938546-
Γλώσσαen-
Μέγεθος12 pagesen
ΤίτλοςLarge-scale collective entity matchingen
ΔημιουργόςRastogi Vibhoren
ΔημιουργόςDalvi Nileshen
ΔημιουργόςGarofalakis Minosen
ΔημιουργόςΓαροφαλακης Μινωςel
ΕκδότηςAssociation for Computing Machineryen
ΠερίληψηThere 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.en
ΤύποςΠλήρης Δημοσίευση σε Συνέδριοel
ΤύποςConference Full Paperen
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-11-30-
Ημερομηνία Δημοσίευσης2009-
Θεματική ΚατηγορίαDatabase managementen
Βιβλιογραφική ΑναφοράV. Rastogi, N. Dalvi and M. Garofalakis, "Large-scale collective entity matching", in 35th International Conference on Very Large Data Bases, 2009.en

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