Detecting people of interest from internet data sources

Raymond A. Cardillo; John J. Salerno

doi:10.1117/12.665718

18 April 2006 Detecting people of interest from internet data sources

Proceedings Volume 6241, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2006; 62410H (2006) https://doi.org/10.1117/12.665718
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

In previous papers, we have documented success in determining the key people of interest from a large corpus of real-world evidence. Our recent efforts focus on exploring additional domains and data sources. Internet data sources such as email, web pages, and news feeds make it easier to gather a large corpus of documents for various domains, but detecting people of interest in these sources introduces new challenges. Analyzing these massive sources magnifies entity resolution problems, and demands a storage management strategy that supports efficient algorithmic analysis and visualization techniques. This paper discusses the techniques we used in order to analyze the ENRON email repository, which are also applicable to analyzing web pages returned from our "Buddy" meta-search engine.

Citation Download Citation

Raymond A. Cardillo and John J. Salerno "Detecting people of interest from internet data sources", Proc. SPIE 6241, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2006, 62410H (18 April 2006); https://doi.org/10.1117/12.665718

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