AIDBJul 22, 2023

Named Entity Resolution in Personal Knowledge Graphs

arXiv:2307.12173v12 citationsh-index: 20
Originality Synthesis-oriented
AI Analysis

It reviews existing techniques for entity resolution in the context of personal knowledge graphs, which is incremental as it applies known methods to a specific domain.

This chapter addresses the problem of named entity resolution in personal knowledge graphs, discussing its formal definition, necessary components, and challenges for Web-scale data, but does not present new results or concrete numbers.

Entity Resolution (ER) is the problem of determining when two entities refer to the same underlying entity. The problem has been studied for over 50 years, and most recently, has taken on new importance in an era of large, heterogeneous 'knowledge graphs' published on the Web and used widely in domains as wide ranging as social media, e-commerce and search. This chapter will discuss the specific problem of named ER in the context of personal knowledge graphs (PKGs). We begin with a formal definition of the problem, and the components necessary for doing high-quality and efficient ER. We also discuss some challenges that are expected to arise for Web-scale data. Next, we provide a brief literature review, with a special focus on how existing techniques can potentially apply to PKGs. We conclude the chapter by covering some applications, as well as promising directions for future research.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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