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.
350148
Visualization tools for self-organizing maps
Various statistical and pattern recognition techniques, such as concept spaces and category maps in the Illinois Digital Library project, has been explored to solve the semantic interoperability problem in DLI-1. Self-organizing category map is identified as a powerful tool for information summarization. However, visualizing a large-scale self-organizing map in a restricted size of window is difficult. For smaller regions, displaying labels is infeasible. In this paper, two visualization tools, fisheye view and fractal view, are presented. It assists users to visualize a largescale self-organizing map geographically and semantically.
7975073
A Collection of Visual Thesauri for Browsing Large Collections of Geographic Images
Digital libraries of geo-spatial multimedia content are currently deficient in providing fuzzy, concept-based retrieval mechanisms to users. The main challenge is that indexing and thesaurus creation are extremely laborintensive processes for text documents and especially for images. Recently, 800,000 declassified satellite photographs were made available by the United States Geological Survey. Additionally, millions of satellite and aerial photographs are archived in national and local map libraries. Such enormous collections make human indexing and thesaurus generation methods impossible to utilize. In this article we propose a scalable method to automatically generate visual thesauri of large collections of geo-spatial media using fuzzy, unsupervised machine-learning techniques.
18485323
Using Coplink to Analyze Criminal-Justice Data
The paper discusses the Coplink system. The system applies a concept space-a statistics-based, algorithmic technique that identifies relationships between suspects, victims, and other pertinent data-to accelerate criminal investigations and enhance law enforcement efforts. The Coplink concept space application, which began as a research project, has evolved into a real-time system being used in everyday police work. Coplink CS has been successfully deployed at the Tucson Police Department, where crime analysts, officers, detectives, and sergeants from 16 departmental units use the technology voluntarily as part of their daily investigative routine.
40149048
An International Perspective on Fighting Cybercrime
Cybercrime is becoming ever more serious. Findings from the 2002Computer Crime and Security Survey show an upward trend that demonstrates aneed for a timely review of existing approaches to fighting this new phenomenonin the information age. In this paper, we provide an overview of cybercrimeand present an international perspective on fighting cybercrime. We review currentstatus of fighting cybercrime in different countries, which rely on legal, organizational,and technological approaches, and recommend four directions forgovernments, lawmakers, intelligence and law enforcement agencies, and researchersto combat cybercrime.
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.
8882088
Design of Nearest Neighbor Classifiers Using an Intelligent Multi-objective Evolutionary Algorithm
The goal of designing optimal nearest neighbor classifiers is to maximize classification accuracy while minimizing the sizes of both reference and feature sets. A usual way is to adaptively weight the three objectives as an objective function and then use a single-objective optimization method for achieving this goal. This paper proposes a multi-objective approach to cope with the weight tuning problem for practitioners. A novel intelligent multi-objective evolutionary algorithm IMOEA is utilized to simultaneously edit compact reference and feature sets for nearest neighbor classification. Two comparison studies are designed to evaluate performance of the proposed approach. It is shown empirically that the IMOEA-designed classifiers have high classification accuracy and small sizes of reference and feature sets. Moreover, IMOEA can provide a set of good solutions for practitioners to choose from in a single run. The simulation results indicate that the IMOEA-based approach is an expedient method to design nearest neighbor classifiers, compared with an existing single- objective approach.
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.
1463101
RDF/RDFS-based Relational Database Integration
We study the problem of answering queries through a RDF/RDFS ontology, given a set of view-based mappings between one or more relational schemas and this target ontology. Particularly, we consider a set of RDFS semantic constraints such as rdfs:subClassof, rdfs:subPropertyof, rdfs:domain, and rdfs:range, which are present in RDF model but neither XML nor relational models. We formally define the query semantics in such an integration scenario, and design a novel query rewriting algorithm to implement the semantics. On our approach, we highlight the important role played by RDF Blank Node in representing incomplete semantics of relational data. A set of semantic tools supporting relational data integration by RDF are also introduced. The approach have been used to integrate 70 relational databases at China Academy of Traditional Chinese Medicine.
1212877
The expressive rate of constraints
In reasoning tasks involving logical formulas, high expressiveness is desirable, although it often leads to high computational complexity. We study a simple measure of expressiveness: the number of formulas expressible by a language, up to semantic equivalence. In the context of constraints, we prove a dichotomy theorem on constraint languages regarding this measure.
18742334
Arithmetic Constant-Depth Circuit Complexity Classes
The boolean circuit complexity classes AC 0 ⊆ AC 0[m] ⊆ TC 0 ⊆ NC 1 have been studied intensely. Other than NC 1, they are defined by constant-depth circuits of polynomial size and unbounded fan-in over some set of allowed gates. One reason for interest in these classes is that they contain the boundary marking the limits of current lower bound technology: such technology exists for AC 0 and some of the classes AC 0[m], while the other classes AC 0[m] as well as TC 0 lack such technology.