32790214
Federating Diverse Collections of Scientific Literature
The Digital Library Initiative (DLI) project at the University of Illinois at Urbana-Champaign is developing the information infrastructure to effectively search technical documents on the Internet. The authors are constructing a large testbed of scientific literature, evaluating its effectiveness under significant use, and researching enhanced search technology. They are building repositories (organized collections) of indexed multiple-source collections and federating (merging and mapping) them by searching the material via multiple views of a single virtual collection. Developing widely usable Web technology is also a key goal. Improving Web search beyond full-text retrieval will require using document structure in the short term and document semantics in the long term. Their testbed efforts concentrate on journal articles from the scientific literature, with structure specified by the Standard Generalized Markup Language (SGML). Research efforts extract semantics from documents using the scalable technology of concept spaces based on context frequency. They then merge these efforts with traditional library indexing to provide a single Internet interface to indexes of multiple repositories.
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.
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.
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.
2898024
Using OWL in a Pervasive Computing Broker
Computing is moving toward a pervasive context-aware environment in which agents with limited resources will require external support to help them become context-aware. In this paper, we describe an agent based architecture called Context Broker Architecture (CoBrA) to help these agents to acquire, reason about and share context knowledge. A key component in our architecture is an explicit context ontology defined using the Web Ontology Language (OWL). This ontology models the basic concepts of people, agents, places, and presentation events. We also describe a use case scenario and prototype design of CoBrA in an intelligent meeting room environment.
10326556
Orthogonal and Straight-Line Drawings of Graphs with Succinct Representations
The concept of a hierarchical design has played an important role in various areas of computer science and engineering, including software engineering, CAD, among others. Graphs with hierarchical structures, which are capable of describing large-scale regular structures in a succinct manner, have naturally become an interesting and important modeling tool for facilitating such a hierarchical design. In the literature, a number of succinct models for representing graphs with hierarchical structures have been proposed. See, e.g., [4,5]. In each of such hierarchical graph models, a succinct description is capable of representing a graph (which can be thought of as the expansion of the description) whose size is exponential in the length of the description.
5569010
A Fast Efficient Parallel Hough Transform Algorithm on LARPBS
A parallel algorithm for Hough transform on a linear array with reconfigurable pipeline bus system (LARPBS) is presented. Suppose the number of θ-values to be considered is m, for an image with n × n pixels, the algorithm can complete Hough transform in O(1) time using mn2 processors and achieve optimal speed and efficiency. We also illustrate how to partition data and perform the algorithm on a LARPBS with fewer than mn2 processors, and hence show that the algorithm is highly scalable.
14045822
Optimizing search by showing results in context
We developed and evaluated seven interfaces for integrating semantic category information with Web search results. List interfaces were based on the familiar ranked-listing of search results, sometimes augmented with a category name for each result. Category interfaces also showed page titles and/or category names, but re-organized the search results so that items in the same category were grouped together visually. Our user studies show that all Category interfaces were more effective than List interfaces even when lists were augmented with category names for each result. The best category performance was obtained when both category names and individual page titles were presented. Either alone is better than a list presentation, but both together provide the most effective means for allowing users to quickly examining search results. These results provide a better understanding of the perceptual and cognitive factors underlying the advantage of category groupings and provide some practical guidance to Web search interface designers.
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.