Source-aware Entity Matching: A Compositional Approach
Entity matching (a.k.a. record linkage) plays a crucial role in integrating multiple data sources, and numerous matching solutions have been developed. However, the solutions have largely exploited only information available in the mentions and employed a single matching technique. We show how to exploit information about data sources to significantly improve matching accuracy. In particular, we observe that different sources often vary substantially in their level of semantic ambiguity, thus requiring different matching techniques. In addition, it is often beneficial to group and match mentions in related sources first, before considering other sources. These observations lead to a large space of matching strategies, analogous to the space of query evaluation plans considered by a relational optimizer. We propose viewing entity matching as a composition of basic steps into a "match execution plan". We analyze formal properties of the plan space, and show how to find a good match plan. To do so, we employ ideas from social network analysis to infer the ambiguity and related-ness of data sources. We conducted extensive experiments on several real-world data sets on the Web and in the domain of personal information management (PIM). The results show that our solution significantly outperforms current best matching methods.

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: Declarative Information Extraction Using Datalog with Embedded Extraction Predicates
abstract: In this paper we argue that developing information extraction (IE) programs using Datalog with embedded procedural extraction predicates is a good way to proceed. First, compared to current ad-hoc composition using, e.g., Perl or C++, Datalog provides a cleaner and more powerful way to compose small extraction modules into larger programs. Thus, writing IE programs this way retains and enhances the important advantages of current approaches: programs are easy to understand, debug, and modify. Second, once we write IE programs in this framework, we can apply query optimization techniques to them. This gives programs that, when run over a variety of data sets, are more efficient than any monolithic program because they are optimized based on the statistics of the data on which they are invoked. We show how optimizing such programs raises challenges specific to text data that cannot be accommodated in the current relational optimization framework, then provide initial solutions. Extensive experiments over real-world data demonstrate that optimization is indeed vital for IE programs and that we can effectively optimize IE programs written in this proposed framework.

title: Community Information Management
abstract: 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: Distributed Manufacturing Scheduling Using Intelligent Agents
abstract: Manufacturing scheduling is an optimization process that allocates limited manufacturing resources over time among parallel and sequential manufacturing activities. This allocation must obey a set of rules or constraints that reflect the temporal relationships between manufacturing activities and the capacity limitations of a set of shared resources. The allocation also affects a schedule's optimality with respect to criteria such as cost, lateness, or throughput. The globalization of manufacturing makes such optimization increasingly important. To survive in this competitive market, manufacturing enterprises must increase their productivity and profitability through greater shop floor agility. Agent-based manufacturing scheduling systems are a promising way to provide this optimization.

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: Improving PDM Systems Integration Using Software Agents
abstract: This paper addresses challenges in integrating distributed and heterogeneous Product Data Management (PDM) systems, introduces a virtual enterprise ori­ ented agents-based integration solution, and presents an infrastructure with in­ teractive and communicative agents as community and domain services to support distributed management of documents, BOMs, workflows and engi­ neering knowledge, and secure communication in a collaborative product de­ velopment environment. Considering the standardized Web· based agents and fundamental product data managed by PDM systems, the proposed paradigm is scalable and can also be used to integrate business systems in manufacturing enterprises.

title: Model-Driven Agent-Based Web Services IDE
abstract: Web services have not exploited sufficient semantics and approaches to dynamic service-oriented operations. Software agents have been developed for these operations. Current efforts on integrating Web services and agents are predominantly concerned with enabling the agents in existing systems to request, provide or broker Web services. This paper presents the notion of agent-based Web services (AWS) and describes an integration framework that utilizes software agents’ model to construct semantic and dynamic Web services. Essential concerns about the integration have been addressed. Basic AWS meta model and model-driven integrated development environment (IDE) have been developed. The IDE has been evaluated by a case study of an e-Marketplace service, reverse auction.

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