Abstract

Developing scalable, semi-automatic approaches to derive insights from a domain-specific Web corpus is a longstanding research problem in the knowledge discovery community. The problem is particularly challenging in illicit fields, such as human trafficking, where traditional assumptions concerning information representation are frequently violated. In this article, we describe an end-to-end investigative knowledge discovery system for illicit Web domains. We built and evaluated a prototype, involving separate components for information extraction, semantic modeling and query execution, on a real-world human trafficking Web corpus containing 1.3 million pages, with promising results.

Date

May 8, 2018

Authors

Mayank Kejriwal, Pedro Szekely, Craig Knoblock

Journal

IEEE Intelligent Systems

Volume

33

Issue

1

Pages

53-63

Publisher

IEEE