In this paper we introduce ENP-regex, a prototype of a regular expression matcher developed for Expressive Notation Package (ENP). ENP-regex allows us to use the regular expression syntax to match against several score attributes, such as pitch and rhythm. Instead of writing the regular expression matcher from scratch we implement a scheme where a thin conversion layer is inserted between an ex...

A generic semantic-driven data matching framework (SDD-Matcher) has been designed and developed for matching data objects across organizations. It contains matching algorithms at three different levels: string, lexical and graph. The level of graph is also called ontological or conceptual level. Those matching algorithms are the basic building blocks of an SDDMatcher matching strategy, each of ...

Ontology matching produces correspondences between entities of two ontologies. The OMReasoner is unique in that it creates an extensible framework for combination of multiple individual matchers, and reasons about ontology matching by using description logic reasoner. It handles ontology matching in semantic level and makes full use of the semantic part of OWL-DL instead of structure. This pape...

This paper presents a framework for verifying compilation tools for parametrised hardware libraries with placement information. Such libraries are captured in Pebble, a simple declarative language based on Structural VHDL, and can contain placement information to guide circuit layout. Relative placement information enables control of circuit layout at a higher level of abstraction than placemen...

Abstract We show how to systematically derive an efficient regular expression (regex) matcher using a variety of program transformation techniques, but very little specialized formal language and automata theory. Starting from the standard specification set-theoretic semantics expressions, we proceed via continuation-based backtracking matcher, classical, table-driven state machine. All steps d...

Discovering correspondences between schema elements is a crucial task for data integration. Most schema matching tools are semiautomatic, e.g., an expert must tune certain parameters (thresholds, weights, etc.). They mainly use aggregation methods to combine similarity measures. The tuning of a matcher, especially for its aggregation function, has a strong impact on the matching quality of the ...

Transformation of business messages from one trading partner’s definition to another, or from one business message type to another is a common requirement for enterprise data integration applications. Transforming these business messages entails resolving issues of structural and semantic heterogeneity between their schemas. In this paper, we propose an automatic schema matching approach called...

We present a model of similarity-based retrieval which attempts to capture three psychological phenomena : (1) people are extremely good at judging similarity and analogy when given items to compare. (2) Superficial remindings are much more frequent than structural remindings . (3) People sometimes experience and use purely structural analogical remindings . Our model, called MAC/FAC (for "many...

We present a model of similarity-based retrieval which attempts to capture three psychological phenomena: (1) people are extremely good at judging similarity and analogy when given items to compare. (2) Super cial remindings are much more frequent than structural remindings. (3) People sometimes experience and use purely structural analogical remindings. Our model, called MAC/FAC (for \many are...

Discovering correspondences between schema elements is a crucial task for data integration. Most matching tools are semi-automatic, e.g. an expert must tune some parameters (thresholds, weights, etc.). They mainly use several methods to combine and aggregate similarity measures. However, their quality results often decrease when one requires to integrate a new similarity measure or when matchin...