Abstract

Entity Resolution (ER) concerns identifying logically equivalent pairs of entities that may be syntactically disparate. Although ER is a long-standing problem in the artificial intelligence community, the growth of Linked Open Data, a collection of semi-structured datasets published and inter-connected on the Web, mandates a new approach. The thesis is that building a viable Entity Resolution solution for serving Big Data needs requires simultaneously resolving challenges of automation, heterogeneity, scalability and domain independence. The dissertation aims to build such a system and evaluate it on real-world datasets published already as Linked Open Data.

Date

2015

Authors

Mayank Kejriwal

Journal

Proceedings of the AAAI Conference on Artificial Intelligence

Volume

29

Issue

1