Abstract:
Country risk - the likelihood that a state will weaken or fail - and the methods of assessing it continue to be of serious concern to the international community. Country risk has traditionally been assessed by monitoring economic and financial indicators. However, social media (such as forums, blogs, and websites) are now important transporters of citizens' daily conversations and opinions, and as such may carry discernible indicators of risk, but they have been as yet little-used for this task. The Geopolitical Web project is a research effort with the ultimate goal of developing computational approaches for monitoring public opinion in regions of conflict, assessing country risk indicators in the social media of fragile or weakening states, and correlating these risk signals with commonly accepted quantitative geopolitical risk assessments. This paper presents the initial motivation for this data-driven project, collection procedures adopted, preliminary results of an automated topical analysis of the collection's content, and expected future work. By catching and deciphering possible signals of country risk in social discourse we hope to offer the international community an additional means of assessing the need for intervention in or support for fragile or weakening states. © 2011 IEEE.
Abstract:
The security of border and transportation systems is a critical component of the national strategy for homeland security. The security concerns at the border are not independent of law enforcement in border-area jurisdictions because information known by local law enforcement agencies may provide valuable leads useful for securing the border and transportation infrastructure. The combined analysis of law enforcement information and data generated by vehicle license plate readers at the international borders can be used to identify suspicious vehicles at ports of entry. This not only generates better quality leads for border protection agents but may also serve to reduce wait times for commerce, vehicles, and people as they cross the border. In this paper we use the mutual information concept to identify vehicles that frequently cross the border with vehicles that are involved in criminal activity. We find that the mutual information measure can be used to identify vehicles that can be potentially targeted at the border. © 2005 IEEE.
Abstract:
In light of such overwhelming interest from governments and academia in adopting and advancing IT for effective healthcare, there are great opportunities for researchers and practitioners alike to invest efforts in conducting innovative and high-impact healthcare IT research. This IEEE Intelligent Systems Trends and Controversies (T&C) Department hopes to raise awareness and highlight selected recent research that helps move us toward such goals. This T&C department includes three articles on Smart Health and Wellbeing from distinguished experts in computer science, information systems, and medicine. Each article presents unique perspectives, advanced computational methods, and selected results and examples. © 2011 IEEE.
Abstract:
Classifying and organizing documents in repositories is an active research topic in digital library studies. Manually classifying the large volume of patents and patent applications managed by patent offices is a labor-intensive task. Many previous studies have employed patent contents for patent classification with the aim of automating this process. In this research we propose to use patent citation information, especially the citation network structure information, to address the patent classification problem. We adopt a kernel-based approach and design kernel functions to capture content information and various citation-related information in patents. These kernels. performances are evaluated on a testbed of patents related to nanotechnology. Evaluation results show that our proposed labeled citation graph kernel, which utilized citation network structures, significantly outperforms the kernels that use no citation information or only direct citation information. Copyright 2007 ACM.
