The purely manual specification of semantic correspondences between schemas is almost infeasible for very large schemas or when many different schemas have to be matched. Hence, solving such large-scale match tasks asks for automatic or semi-automatic schema matching approaches. Large-scale matching needs especially be supported for XML schemas and different kinds of ontologies due to their inc...

This paper addresses the problem of multiple pattern matching for motifs encoded by Position Weight Matrices. We first present an algorithm that uses a multi-index table to preprocess the set of motifs, allowing a dramatically decrease of computation time. We then show how to take benefit from simlar motifs to prevent useless computations.

Context matching algorithms automatically discover semantic relations between two autonomously developed conceptual representations of two overlapping domains. Although significant work has been carried on the theoretical ground, the empirical evaluation of matching algorithms is still an open area for research. In this paper we introduce CTXMATCH, a matching algorithm which applies to symbolic...

During the process of citation matching links from bibliography entries to referenced publications are created. Such links are indicators of topical similarity between linked texts, are used in assessing the impact of the referenced document and improve navigation in the user interfaces of digital libraries. In this paper we present a citation matching method and show how to scale it up to hand...

We present a logic-based framework for automated skill matching, able to return a ranked referral list and the related ranking explanation. Thanks to a Knowledge Compilation approach, a knowledge base in Description Logics is translated into a relational database, without loss of information. Skill matching inference services are then efficiently executed via SQL queries. Experimental results f...

Recently, we are witnessing an explosive growth of data in the business and scientific area. In fact, there are many databases and information sources available through the web covering different domains: semantic Web, deep Web, e-business, biology, digital libraries, etc. In such domains, the data generated are heterogeneous and voluminous e.g schemas with several thousand elements are common ...

Nowadays, we are facing a proliferation of heterogeneous biomedical data sources accessible through various knowledgebased applications. These data are annotated by more and more large and disseminated knowledge organization systems ranging from simple terminologies and structured vocabularies to very formal ontologies. In order to solve the interoperability issue which arises due to the hetero...