在线隔离人口贩运实例的实体解决方法

NUT@EMNLP Pub Date : 2015-09-22 DOI:10.18653/v1/W17-4411
Chirag Nagpal, K. Miller, Benedikt Boecking, A. Dubrawski
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引用次数: 27

摘要

人口贩运是一个具有挑战性的执法问题,这种活动的受害者的痕迹在各种在线论坛上以“护送广告”的形式出现。考虑到这些数据的庞大、异构和嘈杂的结构,建立模型来预测贩运实例是一项复杂的任务。在本文中,我们提出了一个使用代理标签概念的实体解析管道,以便从这些具有先前人口贩运活动历史的数据中提取聚类。我们将这种管道应用于来自backpage.com的5M条记录,并报告了这种方法的性能、可扩展性方面的挑战,以及我们解析实体的一些重要的领域特定特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Entity Resolution Approach to Isolate Instances of Human Trafficking Online
Human trafficking is a challenging law enforcement problem, and traces of victims of such activity manifest as ‘escort advertisements’ on various online forums. Given the large, heterogeneous and noisy structure of this data, building models to predict instances of trafficking is a convoluted task. In this paper we propose an entity resolution pipeline using a notion of proxy labels, in order to extract clusters from this data with prior history of human trafficking activity. We apply this pipeline to 5M records from backpage.com and report on the performance of this approach, challenges in terms of scalability, and some significant domain specific characteristics of our resolved entities.
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