In this paper, a new Cluster based Classification Model (CCM) for suspicious email detection and other text classification tasks, is presented. Comparative experiments of the proposed model against traditional classification models and the boosting algorithm are also discussed. Experimental results show that the CCM outperforms traditional classification models as well as the boosting algorithm for the task of suspicious email detection on terrorism domain email dataset and topic categorization on the Reuters-21578 and 20 Newsgroups datasets. The overall finding is that applying a cluster based approach to text classification tasks simplifies the model and at the same time increases the accuracy.

In this paper we present LanguageNet-a novel framework for processing unstructured text information from human generated content. The state of the art information processing frameworks have some shortcomings: modeled in generalized form, trained on fixed (limited) data sets, and leaving the specialization necessary for information consolidation to the end users. The proposed framework is the first major attempt to address these shortcomings. LanguageNet provides extended support of graphical methods contributing added value to the capabilities of information processing. We discuss the benefits of the framework and compare it with the available state of the art. We also describe how the framework improves the information gathering process and contribute towards building systems with better performance in the domain of Open Source Intelligence.

The abundance of information regarding any topic makes the Internet a very good resource. Even though searching the Internet is very easy, what remains difficult is to automate the process of information extraction from the available online information due to the lack of structure and the diversity in the sharing methods. Most of the times, information is stored in different proprietary formats, complying with different standards and protocols which makes tasks like data mining and information harvesting very difficult. In this paper, an information harvesting tool (heteroHarvest) is presented with objectives to address these problems by filtering the useful information and then normalizing the information in a singular non hypertext format. Finally we describe the results of experimental evaluation. The results are found promising with an overall error rate equal to 6.5% across heterogeneous formats.

This paper focuses on the problem of alias detection based on orthographic variations of Arabic names. Alias detection is the process to identify different variants of the same name. To detect aliases based on orthographic variations, the approximate string matching (ASM) algorithms are widely used that measure the similarities between two strings (i.e., the name and alias). ASM algorithms work well to detect various type of orthographic variations but still there is a need to develop techniques to detect correct aliases of Arabic names that occur due to the translation of Arabic names into English. An extension to widely used ASM algorithms is proposed to detect the name aliases that generate as a result of transliteration. This paper aims to improve the accuracy of the basic ASM algorithms in order to detect correct aliases. The experimental evaluation shows that proposed extension increases the accuracy of the basic algorithms to a considerable level.

A terrorist network is a special kind of social network with emphasis on both secrecy and efficiency. Such networks are intentionally structured to ensure efficient communication between members without being detected. A terrorist network can be modeled as a generalized network (graph) consisting of nodes and links. Techniques from social network analysis and graph theory can be used to identify key entities in the network, which is helpful for network destabilization purposes. Research on terrorist network analysis has mainly focuses on analysis of nodes, which is in contrast to the fact that the links between the nodes provide at least as much relevant information about the network as the nodes themselves. This paper presents a novel method to analyze the importance of links in terrorist networks inspired by research on transportation networks. The link importance measure is implemented in CrimeFighter Assistant and evaluated on known terrorist networks.

Model defects are a significant concern in the Model-Driven Development (MDD) paradigm, as model transformations and code generation may propagate errors to other notations where they are harder to detect and trace. Formal verification techniques can check the correctness of a model, but their high computational complexity can limit their scalability. In this paper, we consider a specific static model (UML class diagrams annotated with unrestricted OCL constraints) and a specific property to verify (satisfiability, i.e., "is it possible to create objects without violating any constraint?"). Current approaches to this problem have an exponential worst-case runtime. We propose a technique to improve their scalability by partitioning the original model into submodels (slices) which can be verified independently and where irrelevant information has been abstracted. The definition of the slicing procedure ensures that the property under verification is preserved after partitioning.

In the recent decades most of the big organizations have adopted maturity driven process improvement efforts (MDPI). Most of these efforts have been inspired of maturity models like the CMM (capability maturity model). The maturity of an organizationpsilas processes is measured through its maturity level. An organization availed a high maturity level is considered more trustworthy In this competitive business era making software process improvement (SPI) happen is a challenge for small organizations. The statistics provided by Software Engineering Institute (SEI) for software community striving for SPI by using CMM/CMM Iindicates that a large number of companies fail to achieve their process improvement goals. SPI efforts have mostly been prolonged, expensive, and not often delivered the effects back to the organizations in the same dimension as investigations.We wonder WHY? This research paper investigates strengths and weaknesses of maturity driven process improvement (e.g. CMM). The case studies in extant SPI literature are studied and focus group is used for data collection.The study suggests that process improvement initiatives should be tailored addressing organizational needs instead of blindly pursuing maturity models prescriptions.Furthermore, it is suggested to have an inception phase prior to an SPI initiative to decide whether a maturity driven process improvement approach should be opted or an effect driven process improvement approach.

Interoperability in telemedicine system is one of the major concern in telemedicine health care system. It is difficult to design exact and flexible interoperable architecture in telemedicine which transmit data and exchange information between systems to systems. The Service Oriented Architecture (SOA) is playing major role in the development of such system which helps to exchange the information between similar and dissimilar telemedicine applications. Using SOA and external Web services, the issue of interoperability can be resolved. The aim of this paper is to describe the importance of SOA in telemedicine through distributed system architecture design and implementation,which is developed in .Net platform using external Web services. The architecture of telemedicine system which we have developed is comprises of three layers that are presentation layer, business logic layer and data layer.

This paper focuses on police investigations conducted by small teams of officers as they usually work on solving violent crimes. Collaboration and communication are important aspects as well as connecting pieces of information that become known to the officers over time. This is an important application domain of knowledge management, and in particular hypertext. We present a prototypic application, Socs, that permits the intuitive connecting of information on a space. It supports emergent and dynamic knowledge structures, fosters communication, awareness and notification services, enables multiple trails of thought in parallel (i. e., thought experiments), as well as versioning with easy access to previous states. As a complement to the database and network analysis driven applications available today, we propose a tool for criminal profiling or crime scene analysis supporting small teams of officers in knowledge structuring and collaboration.

Distributed web-based applications have been progressively increasing in number and scale over the past decades. There is an intensification of the need for security frameworks in the era of web-based applications when we refer to distributed telemedicine interoperability architectures. In contrast, Service Oriented Architecture (SOA) is gaining popularity day by day when we specially consider the web applications. SOA is playing a major role to maintain the security standards of distributed applications. This paper proposes a secure web-based architectural design by using the standards of SOA for distributed web application that maintains the interoperability and data integration through certain secure channels. We have created CRUD (Create,Read, Update, Delete) operations that has an implication on our own created web services and we propose a secure architecture that is implemented on CRUD operations.

Based on the emergent nature of terrorist groups, we propose spatial hypertext as a tool for intelligence analysts for representing, reasoning upon, and communicating information. Furthermore, we evaluate awareness as an important feature for analysts to realise hidden associations between various people or objects. Finally, we discuss our prototype Socs, a general spatial structure application with high level support for awareness, under the umbrella of intelligence analysis requirements.

Summary form only given. A new model of dependence centrality is proposed. The centrality measure is based on shortest paths between the pair of nodes. We apply this measure with demonstration of small network example. The comparisons are made with betweenness centrality. We discuss how investigative world / intelligence agencies could be benefited from the proposed measure.