Paper Info
Title
Catchem: A Browser Plugin for the Panama Papers Using Approximate String Matching
Abstract
The Panama Papers is a collection of 11.5 million leaked records that contain information for more than 214,488 offshore entities. This collection is growing rapidly as more leaked records become available online. In this paper, we present a work in progress on a web browser plugin that detects company names from the Panama Papers and alerts the user by means of unobtrusive visual cues. We matched a random sample of company names from the Public Works and Government Services Canada registry against the Panama Papers using three different string matching techniques. Monge-Elkan is found to provide the best matching results but at increased computational cost. Levenshtein-based approach is found to provide the best tradeoff between matching and computational cost, while Jacquard index like approach is found to be less sensitive to slight textual change.
Year
DOI
Venue
2017
10.1109/EISIC.2017.28
2017 European Intelligence and Security Informatics Conference (EISIC)
Keywords
Field
DocType
Corruption,organised crime,string matching,Panama Papers
String searching algorithm,Sensory cue,Panama,Web browser,Information retrieval,Work in process,Computer science,Memory management,Approximate string matching,Plug-in
Conference
ISSN
ISBN
Citations 
2572-3723
978-1-5386-2386-2
0
PageRank 
References 
Authors
0.34
2
4
Name
Order
Citations
PageRank
Panos A. Kostakos154.88
Miika Moilanen200.34
Arttu Niemela300.34
Mourad Oussalah434476.14