770502
Visualizing the archive of a computer mediated communication process
The archive of computer-mediated communication (CMC) process contains knowledge shared and information about participants' behavior patterns. However, most CMC systems focus only on organizing the content of discussions. We propose to demo a prototype system that integrates a social visualization technique with existing information analysis technologies to graphically summarize both the content and behavior of a CMC process.
21266732
User Misconceptions of Information Retrieval Systems
In this paper, we report results of an investigation where thirty subjects were observedperforming subject-based search in an online catalog system. The observationshave revealed a range of misconceptions users have when performing subject-basedsearch. We have developed a taxonomy that characterizes these misconceptions andhypotheses about the causes of the misconceptions. Directions for improving searchperformance are also suggested.
38977435
Sharing and Visualizing Infectious Disease Datasets Using the WNV-BOT Portal System
Infectious disease outbreaks are critical threats to public health and national security. Information systems play a central role in developing an effective comprehensive approach to prevent, detect, respond to, and manage infectious disease outbreaks of plants, animals, and humans.
35410760
Collaborative Workflow Management for Interagency Crime Analysis
To strengthen homeland security, there is a critical need for new tools that can facilitate real time collaboration among various law enforcement agencies. Through a field study, we find that law enforcement work is knowledge intensive and involves complex collaborative processes interrelating a large number of disparate units in a loosely defined virtual organization. To support knowledge intensive collaboration, we propose a new workflow centric framework to seamlessly integrate previously separate techniques from the fields of information retrieval and workflow management. Specifically, we develop a collaborative workflow management framework for interagency crime analysis. The key contribution of our research is that by integrating various state-of-the-art techniques innovatively, the proposed system can support real time collaboration processes in a virtual organization that evolves dynamically.
19452291
Cross-Jurisdictional Activity Networks to Support Criminal Investigations
Border and transportation security is a critical part of the Department of Homeland Security's (DHS) national strategy. DHS strategy calls for the creation of "smart borders" where information from local, state, federal, and international sources can be combined to support risk-based management tools for border-management agencies. Sharing cross-jurisdictional law enforcement data is important because criminals take advantage of the fact that information sharing between law enforcement jurisdictions is very limited. Challenges to information integration in this important domain include policy and privacy concerns, data security requirements, semantic or schema-level matching of legacy system data, and identity matching. The BorderSafe project leverages the skills and experiences of a diverse group of researchers, law enforcement officials, and government agencies to address data sharing needs in the Southwest United States. Our demo presents a framework for combining law enforcement data across jurisdictions to support criminal investigation and describes how that framework was used in combining three large, overlapping datasets to produce an integrated system for visualizing criminal activity networks.
40127439
Authorship Analysis in Cybercrime Investigation
Criminals have been using the Internet to distribute a wide range of illegal materials globally in an anonymous manner, making criminal identity tracing difficult in the cybercrime investigation process. In this study we propose to adopt the authorship analysis framework to automatically trace identities of cyber criminals through messages they post on the Internet. Under this framework, three types of message features, including style markers, structural features, and content-specific features, are extracted and inductive learning algorithms are used to build feature-based models to identify authorship of illegal messages. To evaluate the effectiveness of this framework, we conducted an experimental study on data sets of English and Chinese email and online newsgroup messages. We experimented with all three types of message features and three inductive learning algorithms. The results indicate that the proposed approach can discover real identities of authors of both English and Chinese Internet messages with relatively high accuracies.
6389142
Optimal confidence interval for the largest normal mean with unknown variance
A single-sample procedure for obtaining an optimal confidence interval for the largest or smallest mean of several independent normal populations is proposed. It is assumed that the common variance is unknown. It has been found that the optimal confidence interval is uniformly better than any other existing one-sample confidence interval in the sense of a reduced interval width. This optimal confidence interval is obtained by maximizing the coverage probability with the expected confidence width being fixed at a least favorable configuration of means. Tables of the critical values are given for the optimal confidence interval.
19964958
Near-optimal data allocation over multiple broadcast channels
Data broadcast is known as a scalable way to transmit database items to large client populations through a wireless channel. However, with a large set of items, the expected delay of receiving desired data increases due to the sequential nature of the broadcast channel. One possible solution is to increase the number of available channels and allocate items evenly over these channels, then cyclically broadcast data in each channel. In view of data access skew (the access frequencies of data are usually different), some channels may be reserved exclusively for those few frequently requested items, while the infrequently accessed bulk of data are allocated on other channels. In this paper, an O(N log K) restricted dynamic programming (RDP) algorithm is proposed to partition N items over K channels assuming data access is skewed with the object of minimizing the average expected delay (aed) of clients. To speed up the DP process, for any partition, we predict a possible location which may be very close to the optimal cut by using a low bound as the actual aed for the remaining items. Thus, the number of comparisons in DP can be restricted to a small interval around the predicted cut point. To further reduce the costs in DP, the hierarchical property of optimal solution is adopted. Simulation results show that, the hit rate obtained by RDP is higher than 90% and it also outperforms the existing algorithm 200%. We extend the work of RDP and develop an O(N log N log K) PKR algorithm; simulation results show that the solution is optimal.
6987127
3D model-assisted face recognition in video
Face recognition in video has gained wide attention as a covert method for surveillance to enhance security in a variety of application domains (e.g., airports). A video contains temporal information as well as multiple instances of a face, so it is expected to lead to better face recognition performance compared to still face images. However, faces appearing in a video have substantial variations in pose and lighting. These pose and lighting variations can be effectively modeled using 3D face models. Combining the advantages of 2D video and 3D face models, we propose a face recognition system that identifies faces in a video. The system utilizes the rich information in a video and overcomes the pose and lighting variations using 3D face model. The description of the proposed method and preliminary results are provided.
45911957
Hardware accelerated voxelization
Abstract This paper presents a hardware accelerated approach to the voxelization of a wide range of 3D objects, including curves/surfaces, solids, and volumetric CSG models. It allows 3D scenes to be modeled and manipulated in their own representations, and generates the volume representations of regions of interest on-the-fly for volumetric operations. The algorithms take advantages of graphics hardware features in modern graphics workstations, such as texture mapping and frame buffer blending functions, to generate slices of the volume representations for various 3D models. As a result, we are able to perform interactive object manipulations and Boolean operations in an intermixed environment of geometric and volumetric objects under a unified volume graphics framework.
16963632
Agents Making Sense of the Semantic Web
Effective use of the vast quantity of available information and services on the Internet will require multi-agent systems to be tightly integrated with existing web infrastructure. This however will be impossible unless the information on the web is presented in a semantic language, such as the DARPA Agent Markup Language (DAML), which is one aim of the “Semantic Web”. As part of our exploration of Semantic Web technology, and DAML in particular, we have constructed ITTALKS, a web-based system for automatic and intelligent notification of information technology talks. In this paper, we describe the ITTALKS system, and discuss the numerous ways in which the use of Semantic Web concepts and DAML extend its ability to provide an intelligent online service to both the human community and, more interestingly, the agents assisting them.