11 citations · 17 across the 3 of their papers we have counts for
4 papers
Principled Graph Matching Algorithms for Integrating Multiple Data Sources
Duo Zhang, Benjamin I. P. Rubinstein, Jim Gemmell
This paper explores combinatorial optimization for problems of max-weight graph matching on multi-partite graphs, which arise in integrating multiple data sources. Entity resolutio…
Scaling Multiple-Source Entity Resolution using Statistically Efficient Transfer Learning
Sahand Negahban, Benjamin I. P. Rubinstein, Jim Gemmell
We consider a serious, previously-unexplored challenge facing almost all approaches to scaling up entity resolution (ER) to multiple data sources: the prohibitive cost of labeling…
A Bayesian Approach to Discovering Truth from Conflicting Sources for Data Integration
Bo Zhao, Benjamin I. P. Rubinstein, Jim Gemmell +1
In practical data integration systems, it is common for the data sources being integrated to provide conflicting information about the same entity. Consequently, a major challenge…
Improving Entity Resolution with Global Constraints
Jim Gemmell, Benjamin I. P. Rubinstein, Ashok K. Chandra
Some of the greatest advances in web search have come from leveraging socio-economic properties of online user behavior. Past advances include PageRank, anchor text, hubs-authoriti…