Artificial Intelligence

Final Call for Papers: IEEE Joint Intelligence and Security Informatics Conference (JISIC) 2014 (deadline approaching soon)

IEEE Joint Intelligence and Security Informatics Conference (JISIC) 2014 will include a special track on BORDER CONTROL.

The possibility exists for Industry to visit Frontex and brief Frontex experts on its portfolios of products and services in the field of border security. For this purpose, a Visit Proposal Form available at http://btn.frontex.europa.eu/form/visit-proposal-form must be completed and submitted.

Frontex invites European Industry and Academia which are implementing projects intended for developing new products/technologies/solutions for border security to send their applications by filling in the form available at: http://btn.frontex.europa.eu/form/application-form-workshop-newongoing-p..., by 15 September 2014.

Call for Papers: IEEE Joint Intelligence and Security Informatics Conference (JISIC) 2014

IEEE Joint Intelligence and Security Informatics Conference (JISIC) 2014 will include a special track on BORDER CONTROL.
Conference Paper
External
Date of publication: 
Mon, 04/07/2011
Discovering and gathering information from multiple disparate sources, assessing the veracity of that information, and determining how and when to utilize the information in each stream is one of the most perplexing challenges that governments and businesses face. This symposium explores how governments and businesses can increase the fidelity and use of information streams. Assessing the credibility of information and increasing the quality of information streams is critical in many venues (e.g., law enforcement scenarios, border security, fraud investigations, intelligence gathering, etc.).
Article
External
Date of publication: 
Fri, 02/03/2012
Using video analyzed from a novel deception experiment, this paper introduces computer vision research in progress that addresses two critical components to computational modeling of deceptive behavior : 1) individual non verbal behavior differences, and 2) deceptive ground truth. Video interviews analyzed for this research were participants recruited as potential hooligans (extreme sports fans) who lied about support for their rival team. From these participants, we will process and extract features representing their faces that will be submitted to slow feature analysis. From this analysis we will identify each person’s unique facial expression and behaviors, and look for systemic variation between truth and deception.
Article
External
Date of publication: 
Tue, 11/10/2011
Deception detection remains novel, challenging, and important in natural language processing, machine learning, and the broader LIS community. Computational tools capable of alerting users to potentially deceptive content in computer-mediated messages are invaluable for supporting undisrupted, computer-mediated communication, information seeking, credibility assessment and decision making. The goal of this ongoing research is to inform creation of such automated capabilities.
Conference Paper
External
Date of publication: 
Fri, 05/08/2005
This article presents a Group decision support systems (GDSS) framework for deception detection based on collaborative process patterns, thinkLets. The focus of research is on designing group processes to aid deception detection from various information sources such as text transcripts, video clips, and audio clips. Architecture of a prototype under development based on the proposed framework is outlined

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