Applying Reasoning to Instance Transformation
نویسندگان
چکیده
Significant effort has been invested by the Semantic Web community in methodologies and tools for creating ontology mappings. Various techniques for mapping creation have been developed; however less interest has been shown in the actual usage of the created mappings and their application in concrete mediation scenarios. In this paper we show how mappings can be converted to logical rules and evaluated by a Datalog reasoner in order to produced the desired mediation result. The mediation scenario discussed in this work is instance transformation: data expressed as ontology instances is transformed from the terms of one ontology in to the terms of another ontology based on mappings created in a design-time phase. We analyze the required reasoning task and describe how the mappings created at design-time can be grounded at runtime. We also explore strategies and techniques that we employed in order to improve the efficiency of the overall process.
منابع مشابه
OPENGIS PROJECT DOCUMENT 99 - 078 TITLE : Topological Operators for the Grid Coverage
Egenhofer's nine-intersection, well-known for vector representations, is de ned here on a raster, using a hybrid raster model, and then systematically transformed to yield functions which can be used in a convolution operation applied to a regular raster representation. Applying functions, the hybrid raster elements need not be stored. It becomes thus possible to determine the topological relat...
متن کاملManual for EAR4 and CAAR Weka Plugins
EAR4 and CAAR are lazy learners applying the case-based reasoning (CBR) paradigm to numerical prediction tasks. Both augment standard instance-based learning methods by applying automatically generated case adaptation rules to adjust solutions of prior cases, and both apply ensembles of the generated rules. CAAR augments the EAR approach with a richer treatment of case context, more context-awa...
متن کاملResolution-Based Execution of Description Logics Programs for Instance-Retrieval
This paper compares two resolution-based ABox reasoning techniques over the description logic language ALC. Queries are executed in a Prolog-framework using the PTTP (Prolog Technology Theorem Proving) approach. The aim of these reasoning algorithms is to efficiently answer instance-check and instance-retrieval queries when large amounts of data are stored in the ABox. We describe two approache...
متن کاملINTEGRATING CASE-BASED REASONING, KNOWLEDGE-BASED APPROACH AND TSP ALGORITHM FOR MINIMUM TOUR FINDING
Imagine you have traveled to an unfamiliar city. Before you start your daily tour around the city, you need to know a good route. In Network Theory (NT), this is the traveling salesman problem (TSP). A dynamic programming algorithm is often used for solving this problem. However, when the road network of the city is very complicated and dense, which is usually the case, it will take too long fo...
متن کاملAutomated Reasoning Support for SUMO/KIF
Formal ontologies play an increasingly important role in demanding knowledge representation applications like the Semantic Web. Although there exist extensive formal ontologies written in the Knowledge Interchange Format (KIF), such as for instance the Suggested Upper Merged Ontology (SUMO), automated reasoning support for SUMO has so far been limited. We propose a novel transformation scheme f...
متن کامل