Community Information Management
We introduce Cimple, a joint project between the University of Illinois and the University of Wisconsin. Cimple aims to develop a software platform that can be rapidly deployed and customized to manage data-rich online communities. We first describe the envisioned working of such a software platform and our prototype, DBLife, which is a community portal being developed for the database research community. We then describe the technical challenges in Cimple and our solution approach. Finally, we discuss managing uncertainty and provenance, a crucial task in making our software platform practical.

title: Constraint-Based Entity Matching
abstract: Entity matching is the problem of deciding if two given mentions in the data, such as "Helen Hunt" and "H. M. Hunt", refer to the same real-world entity. Numerous solutions have been developed, but they have not considered in depth the problem of exploiting integrity constraints that frequently exist in the domains. Examples of such constraints include "a mention with age two cannot match a mention with salary 200K" and "if two paper citations match, then their authors are likely to match in the same order". In this paper we describe a probabilistic solution to entity matching that exploits such constraints to improve matching accuracy. At the heart of the solution is a generative model that takes into account the constraints during the generation process, and provides well-defined interpretations of the constraints. We describe a novel combination of EM and relaxation labeling algorithms that efficiently learns the model, thereby matching mentions in an unsupervised way, without the need for annotated training data. Experiments on several real-world domains show that our solution can exploit constraints to significantly improve matching accuracy, by 3-12% F-1, and that the solution scales up to large data sets.

title: Multi-Model Driven Collaborative Development Platform for Service-Oriented e-Business Systems
abstract: Service-oriented architecture can improve e-business applications to be integrated and flexible. This paper proposes a multi-model driven collaborative development platform for service-oriented e-business systems. The platform provides three views, i.e., business view, process view, and service view to support service-oriented software engineering, top-down business planning and bottom-up service-oriented application development. Business and technical consultants can collaborate from distributed sites of, e.g., clients and IT vendors to provide their clients' with rapid development and demonstration. The proposed platform is driven by three models, i.e., service meta model, process model and business model. All of the three models support semantic description and rational operations, and facilitate intelligent service discovery, process execution and business-business integration. Concepts and implementation issues about the proposed platform has been presented in this paper. The platform has been developed and deployed in an innovation centre to be evaluated by visiting customers

title: An agent-based Web service workflow model for inter-enterprise collaboration
abstract: The service-orientated computing paradigm is transforming traditional workflow management from a close and centralized control system into a worldwide dynamic business process. A complete workflow serving inter-enterprise collaboration should include both internal processes and ad hoc external processes. This paper presents an agent-based workflow model to address this challenge. In the proposed model, agent-based technology provides the workflow coordination at both inter- and intra-enterprise levels while Web service-based technology provides infrastructures for messaging, service description and workflow enactment. A proof-of-concept prototype system simulating the order entry, partner search and selection, and contracting in a virtual enterprise creation scenario is implemented to demonstrate the dynamic workflow definition and execution for inter-enterprise collaboration.

title: Segmentation and Evaluation of Adipose Tissue from Whole Body MRI Scans
abstract: Accurate quantification of total body and the distribution of regional adipose tissue using manual segmentation is a challenging problem due to the high variation between manual delineations. Manual segmentation also requires highly trained experts with knowledge of anatomy. We present a hybrid segmentation method that provides robust delineation results for adipose tissue from whole body MRI scans. A formal evaluation of accuracy of the segmentation method is performed. This semi-automatic segmentation algorithm reduces significantly the time required for quantification of adipose tissue, and the accuracy measurements show that the results are close to the ground truth obtained from manual segmentations.