Named Entity Resolution in Personal Knowledge Graphs

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.Comment: To appear as a book chapter by the same name in an upcoming (Oct. 2023) book `Personal Knowledge Graphs (PKGs): Methodology, tools and applications' edited by Tiwari et a

The Dark Web and Human Trafficking

This is a quantitative-comparative analysis that focuses on Artificial Intelligence (AI) platforms that assist law enforcement agencies as they combat human trafficking. Human trafficking is a Transnational Organized Crime (TOC) which means it can impact every country in the world, and in doing so, impact every person in the world. AI uses machine-learning capabilities to identify clusters, odd and/or unusual font, words, numbers, and other markers in advertisements that promote the sale of human beings. Human trafficking affects males, females, and children of all ages and can include different types of trafficking such as sex and labor trafficking. By using these AI platforms, law enforcement officers are able to identify and help more human beings than ever before in a quicker timeframe. This quantitative-comparative analysis compared Spotlight, Traffick Jam, Traffick Cam, and Domain Insight Graph (DIG) to determine if these platforms were helping law enforcement. The study revolved around the questions of accuracy, consistency, and effectiveness with each platform and found that the majority of AI platforms led the way to promote better, more efficient platforms by the same companies that learned how changes could assist law enforcement more in the future. While each platform assisted in their own ways, there were deltas in each area that leads to the need for future research in the area of AI and how it can be used to help victims of human trafficking and convict human traffickers more in later years