Named Entity Resolution in Personal Knowledge Graphs

TL;DR

This paper discusses the challenges and techniques for Named Entity Resolution in personal knowledge graphs, emphasizing its importance for Web-scale data and future research directions.

Contribution

It provides a formal definition of ER in PKGs, reviews existing techniques, and explores applications and future research avenues.

Findings

Highlights challenges of Web-scale ER in PKGs

Reviews existing ER techniques for PKGs

Suggests promising future research directions

Abstract

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.