• DOI:10.1145/3327964.3328499
Corpus ID: 195357229

Fast and Accurate Entity Linking via Graph Embedding

@article{Parravicini2019FastAA,
  title={Fast and Accurate Entity Linking via Graph Embedding},
  author={A. Parravicini and Rhicheek Patra and D. B. Bartolini and M. Santambrogio},
  journal={Proceedings of the 2nd Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)},
  year={2019}
}

A. Parravicini, Rhicheek Patra, +1 author M. Santambrogio

Published 2019

Computer Science

Proceedings of the 2nd Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)

Entity Linking, the task of mapping ambiguous Named Entities to unique identifiers in a knowledge base, is a cornerstone of multiple Information Retrieval and Text Analysis systems. So far, no single entity linking algorithm has been able to offer the accuracy and scalability required to deal with the ever-increasing amount of data in the web and become a de-facto standard. In this paper, we propose a framework for entity linking that leverages graph embeddings to perform collective… CONTINUE READING

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