Abstract

In domains such as humanitarian assistance and disaster relief (HADR), events, rather than named entities, are the primary focus of analysts and aid officials. An important problem that must be solved to provide situational awareness to aid providers is automatic clustering of sub-events that refer to the same underlying event. An effective solution to the problem requires judicious use of both domain-specific and semantic information, as well as statistical methods like deep neural embeddings. In this paper, we present an approach, AugSEER (Augmented feature sets for Structured Event Entity Resolution), that combines advances in deep neural embeddings both on text and graph data with minimally supervised inputs from domain experts. AugSEER can operate in both online and batch scenarios. On five real-world HADR datasets, AugSEER is found, on average, to outperform the next best baseline …

Date

2018

Authors

Mayank Kejriwal, Jing Peng, Haotian Zhang, Pedro Szekely

Conference

The Semantic Web–ISWC 2018: 17th International Semantic Web Conference, Monterey, CA, USA, October 8–12, 2018, Proceedings, Part I 17

Pages

233-249

Publisher

Springer International Publishing