Abstract

Entity resolution is the task of identifying all mentions that represent the same real-world entity within a knowledge base or across multiple knowledge bases. We address the problem of performing entity resolution on RDF graphs containing multiple types of nodes, using the links between instances of different types to improve the accuracy. For example, in a graph of products and manufacturers the goal is to resolve all the products and all the manufacturers. We formulate this problem as a multi-type graph summarization problem, which involves clustering the nodes in each type that refer to the same entity into one super node and creating weighted links among super nodes that summarize the inter-cluster links in the original graph. Experiments show that the proposed approach outperforms several state-of-the-art generic entity resolution approaches, especially in data sets with missing values and one-to …

Date

September 22, 2025

Authors

Linhong Zhu, Majid Ghasemi-Gol, Pedro Szekely, Aram Galstyan, Craig A Knoblock

Conference

The Semantic Web–ISWC 2016: 15th International Semantic Web Conference, Kobe, Japan, October 17–21, 2016, Proceedings, Part I 15

Pages

649-667

Publisher

Springer International Publishing