6650752
Using Content-Based and Link-Based Analysis in Building Vertical Search Engines
This paper reports our research in the Web page filtering process in specialized search engine development. We propose a machine-learning-based approach that combines Web content analysis and Web structure analysis. Instead of a bag of words, each Web page is represented by a set of content-based and link-based features, which can be used as the input for various machine learning algorithms. The proposed approach was implemented using both a feedforward/backpropagation neural network and a support vector machine. An evaluation study was conducted and showed that the proposed approaches performed better than the benchmark approaches.
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.
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.
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.
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.
13538048
Error Free Self-assembly Using Error Prone Tiles
DNA self-assembly is emerging as a key paradigm for nano-technology, nano-computation, and several related disciplines. In nature, DNA self-assembly is often equipped with explicit mechanisms for both error prevention and error correction. For artificial self-assembly, these problems are even more important since we are interested in assembling large systems with great precision. 
 
We present an error-correction scheme, called snaked proof-reading, which can correct both growth and nucleation errors in a self-assembling system. This builds upon an earlier construction of Winfree and Bekbolatov [11], which could correct a limited class of growth errors. Like their construction, our system also replaces each tile in the system by a k × k block of tiles, and does not require changing the basic tile assembly model proposed by Rothemund and Winfree [8]. 
 
We perform a theoretical analysis of our system under fairly general assumptions: tiles can both attach and fall off depending on the thermodynamic rate parameters which also govern the error rate. We prove that with appropriate values of the block size, a seed row of n tiles can be extended into an n × n square of tiles without errors in expected time $\widetilde{O}(n)$, and further, this square remains stable for an expected time of $\widetilde{\Omega}(n)$. This is the first error-correction system for DNA self-assembly that has provably good assembly time (close to linear) and provable error-correction. The assembly time is thesame, up to logarithmic factors, as the time for an irreversible, error-free assembly. 
 
We also did a preliminary simulation study of our scheme. In simulations, our scheme performs much better (in terms of error-correction) than the earlier scheme of Winfree and Bekbolatov, and also much better than the unaltered tile system. 
 
Our basic construction (and analysis) applies to all rectilinear tile systems (where growth happens from south to north and west to east). These systems include the Sierpinski tile system, the square-completion tile system, and the block cellular automata for simulating Turing machines. It also applies to counters, a basic primitive in many self-assembly constructions and computations.
14347517
A Tiered System for Serving Differentiated Content
Contemporary Web sites typically consist of front–end Web servers, application servers, and back-end information systems such as database servers. There has been limited research on how to provide overload control and service differentiation for the back-end systems. In this paper we propose an architecture called tiered service (TS) for these purposes. In TS, there are several heterogeneous back-end systems to serve the Web applications. The Web applications communicate with a routing intermediary to intelligently route the queries to the appropriate back-end servers based on various policies such as client profiles and server load. In our system the back ends may store different qualities of data; lower quality data typically requires less overhead to serve. The main contributions of this paper include (i) a tiered content replication scheme that replicates tiered qualities of data on heterogeneous back ends with different capacity to satisfy clients with diverse requirements for latency and quality of data, and (ii) an application-transparent query routing architecture that automatically routes the queries to the appropriate back ends. The architecture was implemented in our test bed, and its performance was benchmarked. The experimental results demonstrate that TS offers significant performance improvement.
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.
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.
9276534
Setuid Demystified