6 research outputs found
Final results of the Ontology Alignment Evaluation Initiative 2011
euzenat2011dInternational audienceOntology matching consists of finding correspondences between entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. Test cases can use ontologies of different nature (from simple directories to expressive OWL ontologies) and use different modalities, e.g., blind evaluation, open evaluation, consensus. OAEI-2011 builds over previous campaigns by having 4 tracks with 6 test cases followed by 18 participants. Since 2010, the campaign introduces a new evaluation modality in association with the SEALS project. A subset of OAEI test cases is included in this new modality which provides more automation to the evaluation and more direct feedback to the participants. This paper is an overall presentation of the OAEI 2011 campaign
EXPRESS: Resource-oriented and RESTful Semantic Web services
This thesis investigates an approach that simplifies the development of Semantic Web services (SWS) by removing the need for additional semantic descriptions.The most actively researched approaches to Semantic Web services introduce explicit semantic descriptions of services that are in addition to the existing semantic descriptions of the service domains. This increases their complexity and design overhead. The need for semantically describing the services in such approaches stems from their foundations in service-oriented computing, i.e. the extension of already existing service descriptions. This thesis demonstrates that adopting a resource-oriented approach based on REST will, in contrast to service-oriented approaches, eliminate the need for explicit semantic service descriptions and service vocabularies. This reduces the development efforts while retaining the significant functional capabilities.The approach proposed in this thesis, called EXPRESS (Expressing RESTful Semantic Services), utilises the similarities between REST and the Semantic Web, such as resource realisation, self-describing representations, and uniform interfaces. The semantics of a service is elicited from a resource’s semantic description in the domain ontology and the semantics of the uniform interface, hence eliminating the need for additional semantic descriptions. Moreover, stub-generation is a by-product of the mapping between entities in the domain ontology and resources.EXPRESS was developed to test the feasibility of eliminating explicit service descriptions and service vocabularies or ontologies, to explore the restrictions placed on domain ontologies as a result, to investigate the impact on the semantic quality of the description, and explore the benefits and costs to developers. To achieve this, an online demonstrator that allows users to generate stubs has been developed. In addition, a matchmaking experiment was conducted to show that the descriptions of the services are comparable to OWL-S in terms of their ability to be discovered, while improving the efficiency of discovery. Finally, an expert review was undertaken which provided evidence of EXPRESS’s simplicity and practicality when developing SWS from scratch
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PowerAqua: Open Question Answering on the Semantic Web
With the rapid growth of semantic information in the Web, the processes of searching and querying these very large amounts of heterogeneous content have become increasingly challenging. This research tackles the problem of supporting users in querying and exploring information across multiple and heterogeneous Semantic Web (SW) sources.
A review of literature on ontology-based Question Answering reveals the limitations of existing technology. Our approach is based on providing a natural language Question Answering interface for the SW, PowerAqua. The realization of PowerAqua represents a considerable advance with respect to other systems, which restrict their scope to an ontology-specific or homogeneous fraction of the publicly available SW content. To our knowledge, PowerAqua is the only system that is able to take advantage of the semantic data available on the Web to interpret and answer user queries posed in natural language. In particular, PowerAqua is uniquely able to answer queries by combining and aggregating information, which can be distributed across heterogeneous semantic resources.
Here, we provide a complete overview of our work on PowerAqua, including: the research challenges it addresses; its architecture; the techniques we have realised to map queries to semantic data, to integrate partial answers drawn from different semantic resources and to rank alternative answers; and the evaluation studies we have performed, to assess the performance of PowerAqua. We believe our experiences can be extrapolated to a variety of end-user applications that wish to open up to large scale and heterogeneous structured datasets, to be able to exploit effectively what possibly is the greatest wealth of data in the history of Artificial Intelligence