Matching large schemas: Approaches and evaluation

Current schema matching approaches still have to improve for large and complex Schemas. The large search space increases the likelihood for false matches as well as execution times. Further difficulties for Schema matching are posed by the high expressive power and versatility of modern schema languages, in particular user-defined types and classes, component reuse capabilities, and support for distributed schemas and namespaces. To better assist the user in matching complex schemas, we have developed a new generic schema matching tool, COMA++, providing a library of individual matchers and a flexible infrastructure to combine the matchers and refine their results. Different match strategies can be applied including a new scalable approach to identify context-dependent correspondences between schemas with shared elements and a fragment-based match approach which decomposes a large match task into smaller tasks. We conducted a comprehensive evaluation of the match strategies using large e-Business standard schemas. Besides providing helpful insights for future match implementations, the evaluation demonstrated the practicability of our system for matching large schemas.     

Element similarity measures in XML schema matching

Schema matching plays a central role in a myriad of XML-based applications. There has been a growing need for developing high-performance matching systems in order to identify and discover semantic correspondences across XML data. XML schema matching methods face several challenges in the form of definition, adoption, utilization, and combination of element similarity measures. In this paper, we classify, review, and experimentally compare major methods of element similarity measures and their combinations. We aim at presenting a unified view which is useful when developing a new element similarity measure, when implementing an XML schema matching component, when using an XML schema matching system, and when comparing XML schema matching systems.     

A composite approach to automating direct and indirect schema mappings

Automating schema mapping is challenging. Previous approaches to automating schema mapping focus mainly on computing direct matches between two schemas. Schemas, however, rarely match directly. Thus, to complete the task of schema mapping, we must also compute indirect matches. In this paper, we present a composite approach for generating a source-to-target mapping that contains both direct and many indirect matches between a source schema and a target schema. Recognizing expected-data values associated with schema elements and applying schema-structure heuristics are the key ideas needed to compute indirect matches. Experiments we have conducted over several real-world application domains show encouraging results, yielding about 90% precision and recall measures for both direct and indirect matches.     

一种基于部分已验证匹配关系的模式匹配模型

模式匹配是模式集成、语义WEB及电子商务等领域的重点及难点问题. 为了有效利用专家知识提高匹配质量, 提出了一种基于部分已验证匹配关系的模式匹配模型. 在该模型中, 首先,人工验证待匹配模式元素间的少量对应关系, 进而推理出当前任务下部分已知的匹配关系及单独匹配器的缺省权重; 然后,基于上述已收集到的先验知识对多种匹配器所生成的相似度矩阵进行合并及调整, 并在全局范围内进行优化; 最后,对优化矩阵的选择性进行评估, 从而为不同匹配任务推荐最合理的候选匹配生成方案. 实验结果表明, 部分已验证匹配关系的使用有助于模式匹配质量的提高.     

Tuning the ensemble selection process of schema matchers

Schema matching is the task of providing correspondences between concepts describing the meaning of data in various heterogeneous, distributed data sources. It is recognized to be one of the basic operations required by the process of data and schema integration and its outcome serves in many tasks such as targeted content delivery and view integration. Schema matching research has been going on for more than 25 years now. An interesting research topic, that was largely left untouched involves the automatic selection of schema matchers to an ensemble, a set of schema matchers. To the best of our knowledge, none of the existing algorithmic solutions offer such a selection feature. In this paper we provide a thorough investigation of this research topic. We introduce a new heuristic, Schema Matcher Boosting (SMB). We show that SMB has the ability to choose among schema matchers and to tune their importance. As such, SMB introduces a new promise for schema matcher designers. Instead of trying to design a perfect schema matcher, a designer can instead focus on finding better than random schema matchers. For the effective utilization of SMB, we propose a complementary approach to the design of new schema matchers. We separate schema matchers into first-line and second-line matchers. First-line schema matchers were designed by-and-large as applications of existing works in other areas (e.g., machine learning and information retrieval) to schemata. Second-line schema matchers operate on the outcome of other schema matchers to improve their original outcome. SMB selects matcher pairs, where each pair contains a first-line matcher and a second-line matcher. We run a thorough set of experiments to analyze SMB ability to effectively choose schema matchers and show that SMB performs better than other, state-of-the-art ensemble matchers.     

模式匹配方法研究*

从模式匹配的定义开始介绍,对已有的模式匹配方法进行分类,探讨了这些方法适用的领域和所能发掘的信息,区分了实例级和模式级、元素级和结构级以及基于自然语言和基于约束的匹配程序,以期在比较不同模式匹配方法或研究新匹配算法以及实现模式匹配组件时有所帮助。     

不确定模式匹配研究综述

模式匹配是数据集成、语义Web等研究领域的重要研究内容,需要依据一定的启发式信息发现模式元素之间的对应关系。鉴于启发式信息处理方法的不同,对模式匹配方法进行了分类,并从模式匹配结果集结方法的角度,介绍了综合模式匹配方法。不确定性是模式匹配过程固有的特性,介绍了建模模式匹配过程中不确定性的数据模型,在此基础上介绍了处理模式匹配过程中不确定性的模式匹配方法。最后对模式匹配研究进行了展望。     

基于语言和约束匹配器融合的元素匹配研究

在模式匹配方面已经出现了许多使用于特定应用领域的部分自动匹配方法,这种匹配方法结合了多种匹配技术以便能够在大规模的多样匹配环境中得到高的匹配率。提出了一种基于模式的元素匹配方法,它融合了语言和约束匹配器,使用了复合元素名称匹配器和神经网络匹配器,结合基于语言的匹配算法和最大优先策略的原则,以多重标准条件下复合名称匹配器的结果作为约束对模式元素进行归类。通过组合使用复合名称匹配器和神经网络匹配器,使得本方法可以应用于更复杂的匹配环境。     

Metaphors and Context-Aware Information Access

Metaphors are often used to provide the user with a mental model to ease the use of computers. An example of such a metaphor is the commonly used “Desktop Metaphor”. Metaphors also can be used to ease context-aware information access for the users of mobile information systems. In this paper we present a taxonomy that allows the categorisation of such metaphors. Furthermore, we give an overview of existing metaphors and their implementations. After introducing some new metaphors we conclude our considerations with a classification of new and existing metaphors using our taxonomy.     

A framework for superscalar microprocessor correctness statements

Most verifications of superscalar, out-of-order microprocessors compare state-machine-based implementations and specifications, where the specification is based on the instruction-set architecture. The different efforts use a variety of correctness statements, implementations, and verification approaches. We present a framework for classifying correctness statements about safety properties of superscalar microprocessors. Our framework is independent of the implementation representation and verification approach, and is parameterized by the width of the processor. We characterize the relationships between the correctness statements of many different efforts and also illustrate how classical approaches to microprocessor verification fit within our framework. Published online: 17 December 2002