Integrating Information About Entities Progressively

TL;DR

ProgMap is a scalable, collaborative entity-matching framework that uses minimal user feedback to integrate information from diverse data sources efficiently.

Contribution

It introduces a novel on-demand, collaborative approach for entity matching that reduces expert intervention and leverages user feedback for improved accuracy.

Findings

Effective integration with minimal user feedback

Collaborative learning improves matching accuracy

Scalable to increasing data sources

Abstract

Users often have to integrate information about entities from multiple data sources. This task is challenging as each data source may represent information about the same entity in a distinct form, e.g., each data source may use a different name for the same person. Currently, data from different representations are translated into a unified one via lengthy and costly expert attention and tuning. Such methods cannot scale to the rapidly increasing number and variety of available data sources. We demonstrate ProgMap, a entity-matching framework in which data sources learn to collaborate and integrate information about entities on-demand and with minimal expert intervention. The data sources leverage user feedback to improve the accuracy of their collaboration and results. ProgMap also has techniques to reduce the amount of required user feedback to achieve effective matchings.