26701472
Interface descriptions for enterprise architecture
This paper describes our experiences in implementing a repository-based system that records and manages architectural information for an organization-wide set of enterprise information systems. The system is called Interface Descriptions for Enterprise Architecture (IDEA). The IDEA system business case and system creation are discussed, and the use of the system is exemplified by applying it to a set of information systems within a large corporation. We show how the existence of a managed enterprise architecture description enables an important set of analyses: risk analyses, architecture analyses, and change management analyses. Finally, we discuss how the IDEA system has the potential to catalyze even more profound change by changing how the various systems' stakeholders interact.
44852271
Managing Misalignments between Business and IT Architectures: A BITAM Case Study
42930138
Evaluating an Infectious Disease Information Sharing and Analysis System
Infectious disease informatics is a subfield of security informatics that focuses on information analysis and management issues critical to the prevention, detection, and management of naturally occurring or terrorist-engineered infectious disease outbreaks. We have developed a research prototype called BioPortal which provides an integrated environment to support cross-jurisdictional and cross-species infectious disease information sharing, integration, analysis, and reporting. This paper reports a pilot study evaluating BioPortal's usability, user satisfaction, and potential impact on practice.
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.
16942431
A graph model for E-commerce recommender systems
Information overload on the Web has created enormous challenges to customers selecting products for online purchases and to online businesses attempting to identify customers' preferences efficiently. Various recommender systems employing different data representations and recommendation methods are currently used to address these challenges. In this research, we developed a graph model that provides a generic data representation and can support different recommendation methods. To demonstrate its usefulness and flexibility, we developed three recommendation methods: direct retrieval, association mining, and high-degree association retrieval. We used a data set from an online bookstore as our research test-bed. Evaluation results showed that combining product content information and historical customer transaction information achieved more accurate predictions and relevant recommendations than using only collaborative information. However, comparisons among different methods showed that high-degree association retrieval did not perform significantly better than the association mining method or the direct retrieval method in our test-bed.
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.
31295380
Intelligent Agents for Mobile and Embedded Devices
The pervasive computing environments of the near future will involve the interactions, coordination and cooperation of numerous, casually accessible, and often invisible computing devices. These devices, whether carried on our person or embedded in our homes, businesses and classrooms, will connect via wireless and wired links to one another and to the global networking infrastructure. The result will be a networking milieu with a new level of openness. The localized and dynamic nature of their interactions raises many new issues that draw on and challenge the disciplines of agents, distributed systems, and security. This paper describes recent work by the UMBC Ebiquity research group which addresses some of these issues.