33804192
Intelligent spider for Internet searching
As World Wide Web (WWW) based Internet services become more popular, information overload also becomes a pressing research problem. Difficulties with searching on the Internet get worse as the amount of information that is available increases. A scalable approach to support Internet search is critical to the success of Internet services and other current or future national information infrastructure (NII) applications. A new approach to build an intelligent personal spider (agent), which is based on automatic textual analysis of Internet documents, is proposed. Best first search and genetic algorithm have been tested to develop the intelligent spider. These personal spiders are able to dynamically and intelligently analyze the contents of the users' selected homepages as the starting point to search for the most relevant homepages based on the links and indexing. An intelligent spider must have the capability to make adjustments according to progress of searching in order to be an intelligent agent. However, the current searching engines do not have communication between the users and the robots. The spider presented in the paper uses Java to develop the user interface such that the users can adjust the control parameters according to the progress and observe the intermediate results. The performances of the genetic algorithm based and best first search based spiders are also reported.
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.
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.
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.
1567676
Bringing order to the Web: automatically categorizing search results
We developed a user interface that organizes Web search results into hierarchical categories. Text classification algorithms were used to automatically classify arbitrary search results into an existing category structure on-the-fly. A user study compared our new category interface with the typical ranked list interface of search results. The study showed that the category interface is superior both in objective and subjective measures. Subjects liked the category interface much better than the list interface, and they were 50% faster at finding information that was organized into categories. Organizing search results allows users to focus on items in categories of interest rather than having to browse through all the results sequentially.
33677672
A Study of Hybrid Neural Network Approaches and the Effects of Missing Data on Traffic Forecasting
In this paper we present an application of hybrid neural network approaches and an assessment of the effects of missing data on motorway traffic flow forecasting. Two hybrid approaches are developed using a Self-Organising Map (SOM) to initially classify traffic into different states. The first hybrid approach includes four Auto-Regressive Integrated Moving Average (ARIMA) models, whilst the second uses two Multi-Layer Perception (MLP) models. It was found that the SOM/ARIMA hybrid approach out-performs all individual ARIMA models, whilst the SOM/MLP hybrid approach achieves superior forecasting performance to all models used in this study, including three naïve models. The effects of different proportions of missing data on Neural Network (NN) performance when forecasting traffic flow are assessed and several initial substitution options to replace missing data are discussed. Over-all, it is shown that ARIMA models are more sensitive to the percentage of missing data than neural networks in this context.
15840540
Spike-Timing Dependent Competitive Learning of Integrate-and-Fire Neurons with Active Dendrites
Presented is a model of an integrate-and-fire neuron with active dendrites and a spike-timing dependent Hebbian learning rule. The learning algorithm effectively trains the neuron when responding to several types of temporal encoding schemes: temporal code with single spikes, spike bursts and phase coding. The neuron model and learning algorithm are tested on a neural network with a self-organizing map of competitive neurons. The goal of the presented work is to develop computationally efficient models rather than approximating the real neurons. The approach described in this paper demonstrates the potential advantages of using the processing functionalities of active dendrites as a novel paradigm of computing with networks of artificial spiking neurons.
60842612
Tooth contour extraction for matching dental radiographs
In dental biometrics, the contours of teeth in dental radiographs are utilized for human identification. However, in many images, the contours of teeth are fuzzy and only partially visible. To extract the contours from these images, we propose a method based on the active contour models. A new dynamic energy is proposed for the directional snake to discriminate boundaries of adjacent teeth. Matching result shows the contours extracted with this method perform better than traditional methods.
15665012
Progressive auction based resource allocation in service-oriented architecture
The emerging paradigm of distributed Web services has promised seamless business integration across the Internet that shares not only computing power but also applications. One major challenge is resource allocation to each end user in an economically efficient and low latency manner. A common solution is proportional sharing where each user gets his resource in proportion to the predetermined weight. However, this does not allow users to differentiate the value of their services and to dynamically adjust the weights. A resource reservation mechanism may improve the information and service sharing but usually introduces a high latency. In this paper, we propose a progressive auction based market mechanism for resource allocation that allows user differentiation of the service value and ensures the resource acquisition latency to be limited only to the communication delay in service-oriented architecture (SOA) systems. We present a service sharing prototype for selecting services for further business process composition or solution creation and show experimental results on the formation of reliable user ranking in resource sharing through the progressive auction.