33593406
CrimeLink Explorer: Using Domain Knowledge to Facilitate Automated Crime Association Analysis
Link (association) analysis has been used in law enforcement and intelligence domains to extract and search associations between people from large datasets. Nonetheless, link analysis still faces many challenging problems, such as information overload, high search complexity, and heavy reliance on domain knowledge. To address these challenges and enable crime investigators to conduct automated, effective, and efficient link analysis, we proposed three techniques which include: the concept space approach, a shortest-path algorithm, and a heuristic approach that captures domain knowledge for determining importance of associations. We implemented a system called CrimeLink Explorer based on the proposed techniques. Results from our user study involving ten crime investigators from the Tucson Police Department showed that our system could help subjects conduct link analysis more efficiently. Additionally, subjects concluded that association paths found based on the heuristic approach were more accurate than those found based on the concept space approach.
7877784
On the Topology of the Dark Web of Terrorist Groups
In recent years, terrorist groups have used the WWW to spread their ideologies, disseminate propaganda, and recruit members. Studying the terrorist websites may help us understand the characteristics of these websites and predict terrorist activities. In this paper, we propose to apply network topological analysis methods on systematically collected the terrorist website data and to study the structural characteristics at the Web page level. We conducted a case study using the methods on three collections of Middle-Eastern, US domestic, and Latin-American terrorist websites. We found that these three networks have the small-world and scale-free characteristics. We also found that smaller size websites which share same interests tend to make stronger inter-website linkage relationships.
43179863
Analyzing Terrorist Networks: A Case Study of the Global Salafi Jihad Network
It is very important for us to understand the functions and structures of terrorist networks to win the battle against terror. However, previous studies of terrorist network structure have generated little actionable results. This is mainly due to the difficulty in collecting and accessing reliable data and the lack of advanced network analysis methodologies in the field. To address these problems, we employed several advance network analysis techniques ranging from social network analysis to Web structural mining on a Global Salafi Jihad network dataset collected through a large scale empirical study. Our study demonstrated the effectiveness and usefulness of advanced network techniques in terrorist network analysis domain. We also introduced the Web structural mining technique into the terrorist network analysis field which, to the best our knowledge, has never been used in this domain. More importantly, the results from our analysis provide not only insights for terrorism research community but also empirical implications that may help law-reinforcement, intelligence, and security communities to make our nation safer.
215893227
CrimeNet explorer: a framework for criminal network knowledge discovery
Knowledge about the structure and organization of criminal networks is important for both crime investigation and the development of effective strategies to prevent crimes. However, except for netw...
16185032
Using Social Contextual Information to Match Criminal Identities
Criminal identity matching is crucial to crime investigation in law enforcement agencies. Existing techniques match identities that refer to the same individuals based on simple identity features. These techniques are subject to several problems. First, there is an effectiveness trade-off between the false negative and false positive rates. The improvement of one rate usually lowers the other. Second, in some situations such as identity theft, simple-feature-based techniques are unable to match identities that have completely different identity feature values. We argue that the information about the social context of an individual may provide additional information for revealing the individual’s identity, helping improve the effectiveness of identity matching techniques. We define two types of social contextual features: role-based personal features and social group features. Experiments showed that social contextual features, especially the structural similarity and the relational similarity, significantly improved the precision without lowering the recall of criminal identity matching tasks.
1639751
Expertise visualization: An implementation and study based on cognitive fit theory
Expertise management systems are being widely adopted in organizations to manage tacit knowledge. These systems have successfully applied many information technologies developed for document management to support collection, processing, and distribution of expertise information. In this paper, we report a study on the potential of applying visualization techniques to support more effective and efficient exploration of the expertise information space. We implemented two widely applied dimensionality reduction visualization techniques, the self-organizing map (SOM) and multidimensional scaling (MDS), to generate compact but distorted (due to the dimensionality reduction) map visualizations for an expertise data set. We tested cognitive fit theory in our context by comparing the SOM and MDS displays with a standard table display for five tasks selected from a low-level, domain-independent visual task taxonomy. The experimental results based on a survey data set of research expertise of the business school professors suggested that using both SOM and MDS visualizations is more efficient than using the table display for the associate, compare, distinguish, and cluster tasks, but not the rank task. Users generally achieved comparable effectiveness for all tasks using the tabular and map displays in our study. © 2006 Elsevier B.V. All rights reserved.
8292124
Effective retrieval with distributed collections
Abstract : This paper evaluates the retrieval effectiveness of distributed information retrieval systems in realistic environments. We find that when a large number of collections are available, the retrieval effectiveness is significantly worse than that of centralized systems, mainly because typical queries are not adequate for the purpose of choosing the right collections. We propose two techniques to address the problem. One is to use phrase information in the collection selection index and the other is query expansion. Both techniques enhance the discriminatory power of typical queries for choosing the right collections and hence significantly improve retrieval results. Query expansion, in particular, brings the effectiveness of searching a large set of distributed collections close to that of searching a centralized collection.
17686330
Protein Threading by Linear Programming
Protein three-dimensional structure prediction through threading approach has been extensively studied and various models and algorithms have been proposed. In order to further explore ways to improve accuracy and efficiency of the threading process, this paper investigates the effectiveness of a new method: protein threading via linear programming. Based on the contact map model of protein 3D structure, we formulate the protein threading problem as a large scale integer programming problem, then relax to a linear programming problem, and finally solve the integer program by a branch-and-bound method. The final solution is optimal with respect to energy functions incorporating pairwise interaction and allowing variable gaps. The algorithm has been implemented as software package RAPTOR--RApid Protein Threading predictOR. Experimental results for fold recognition show that RAPTOR significantly outperforms other programs at the fold similarity level. The RAPTOR webserver is at http://www.cs.uwaterloo.ca/-j3xu/RAPTOR_form.htm.
2583878
A data streaming algorithm for estimating subpopulation flow size distribution
Statistical information about the flow sizes in the traffic passing through a network link helps a network operator to characterize network resource usage, infer traffic demands, detect traffic anomalies, and improve network performance through traffic engineering. Previous work on estimating the flow size distribution for the complete population of flows has produced techniques that either make inferences from sampled network traffic, or use data streaming approaches. In this work, we identify and solve a more challenging problem of estimating the size distribution and other statistical information about arbitrary subpopulations of flows. Inferring subpopulation flow statistics is more challenging than the complete population counterpart, since subpopulations of interest are often specified a posteriori (i.e., after the data collection is done), making it impossible for the data collection module to "plan in advance".Our solution consists of a novel mechanism that combines data streaming with traditional packet sampling to provide highly accurate estimates of subpopulation flow statistics. The algorithm employs two data collection modules operating in parallel --- a NetFlow-like packet sampler and a streaming data structure made up of an array of counters. Combining the data collected by these two modules, our estimation algorithm uses a statistical estimation procedure that correlates and decodes the outputs (observations) from both data collection modules to obtain flow statistics for any arbitrary subpopulation. Evaluations of this algorithm on real-world Internet traffic traces demonstrate its high measurement accuracy.
2595430
A new approach to intranet search based on information extraction
This paper is concerned with 'intranet search'. By intranet search, we mean searching for information on an intranet within an organization. We have found that search needs on an intranet can be categorized into types, through an analysis of survey results and an analysis of search log data. The types include searching for definitions, persons, experts, and homepages. Traditional information retrieval only focuses on search of relevant documents, but not on search of special types of information. We propose a new approach to intranet search in which we search for information in each of the special types, in addition to the traditional relevance search. Information extraction technologies can play key roles in such kind of 'search by type' approach, because we must first extract from the documents the necessary information in each type. We have developed an intranet search system called 'Information Desk'. In the system, we try to address the most important types of search first - finding term definitions, homepages of groups or topics, employees' personal information and experts on topics. For each type of search, we use information extraction technologies to extract, fuse, and summarize information in advance. The system is in operation on the intranet of Microsoft and receives accesses from about 500 employees per month. Feedbacks from users and system logs show that users consider the approach useful and the system can really help people to find information. This paper describes the architecture, features, component technologies, and evaluation results of the system.
2775894
Rigorous development of a safety-critical system based on coordinated atomic actions
This paper describes our experience using coordinated atomic (CA) actions as a system structuring tool to design and validate a sophisticated control system for a complex industrial application that has high reliability and safety requirements. Our study is based on the "Fault-Tolerant Production Cell", which represents a manufacturing process involving redundant mechanical devices (provided in order to enable continued production in the presence of machine faults). The challenge posed by the model specification is to design a control system that maintains specified safety and liveness properties even in the presence of a large number and variety of device and sensor failures. We discuss in this paper: i) a design for a control program that uses CA actions to deal with both safety-related and fault tolerance concerns, and ii) the formal verification of this design based on the use of model-checking. We found that CA action structuring facilitated both the design and verification tasks by enabling the various safety problems (e.g. clashes of moving machinery) to be treated independently. The formal verification activity was performed in parallel with the design activity the interaction between them resulted in a combined exercise in "design for validation".