Building and Using a Knowledge Graph to Combat Human Trafficking
There is a huge amount of data spread across the web and stored in databases that we can use to build knowledge graphs. However, exploiting this data to build knowledge graphs is difficult due to the heterogeneity of the sources, scale of the amount of da
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Information Sciences Institute, University of Southern California, Marina Del Rey, CA, USA {pszekely,knoblock}@isi.edu 2 InferLink Corporation, El Segundo, CA, USA 3 Next Century Corporation, Columbia, MD, USA 4 Columbia University, New York, USA 5 Universitt Innsbruck, Innsbruck, Austria 6 Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
Abstract. There is a huge amount of data spread across the web and stored in databases that we can use to build knowledge graphs. However, exploiting this data to build knowledge graphs is difficult due to the heterogeneity of the sources, scale of the amount of data, and noise in the data. In this paper we present an approach to building knowledge graphs by exploiting semantic technologies to reconcile the data continuously crawled from diverse sources, to scale to billions of triples extracted from the crawled content, and to support interactive queries on the data. We applied our approach, implemented in the DIG system, to the problem of combating human trafficking and deployed it to six law enforcement agencies and several non-governmental organizations to assist them with finding traffickers and helping victims. Keywords: Linked data · Knowledge graphs integration · Information extraction
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Introduction
Human trafficking is a form of modern slavery where people profit from the control and exploitation of others, forcing them to engage in commercial sex or to provide services against their will. The statistics of the problem are shocking. In 2014 the International Labor Organization on The Economics of Forced Labour1 1
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reported that $99 billion came from commercial sexual exploitation. Polaris2 reports that in the United States 100,000 children are estimated to be involved in the sex trade each year, and that the total number of victims is likely much larger when estimates of both adults and minors as well as sex trafficking and labor trafficking are aggregated. Estimates indicate that traffickers control an average of six victims and derive $150,000 from each victim per year. The sex trafficking industry is estimated to spend about $30 million in online advertising each year. These advertisements appear in hundreds of web sites that advertise escort services, massage parlors, etc. The total number of such advertisements is unknown, but our database of escort ads crawled from the most popular sites contains over 50 million ads. The objective of our work is to create generic technology to enable rapid construction of knowledge graphs for specific domains together with query, visualization and analysis capabilities that enable end-users to solve complex problems. The challenge is to exploit all available sources, including web pages, document collections, databases, delimited text files, structured data such as XML or JSON, images, and videos. Thi
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