Semantic mashup applications allow automating the process of services and data integration to create a composite application with a new user interface. Nevertheless, existing mashup applications need to improve the matching methods for discovering semantic services. Moreover, they have to create or modify workflows in mashup applications without the assistance of the original developers. Automating the combination of user interfaces is another challenge in the context of semantic mashups construction. In this chapter, the authors propose an approach that allows automating the combination of data, services, and user interfaces to provide a composite application with an enhanced user interface. The construction of the semantic mashup application is based on the use of domain ontology, a matching tool, and a collection of patterns. In order to demonstrate the effectiveness of this proposal, the authors present a use case to construct a semantic mashup application for a travel agency.
This article describes how the Linked Open Data Cloud project allows data providers to publish structured data on the web according to the Linked Data principles. In this context, several link discovery frameworks have been developed for connecting entities contained in knowledge bases. In order to achieve a high effectiveness for the link discovery task, a suitable link configuration is required to specify the similarity conditions. Unfortunately, such configurations are specified manually; which makes the link discovery task tedious and more difficult for the users. In this article, the authors address this drawback by proposing a novel approach for the automatic determination of link specifications. The proposed approach is based on a neural network model to combine a set of existing metrics into a compound one. The authors evaluate the effectiveness of the proposed approach in three experiments using real data sets from the LOD Cloud. In addition, the proposed approach is compared against link specifications approaches to show that it outperforms them in most experiments.
With the coming of Web 2.0, several technologies are developed to facilitate creating, sharing and reusing of web resources. In this context, the mashup is a novel approach that allows the user to aggregate multiples services to create a single one with a new user interface. However, a key limitation of existing mashups applications is the need to compute semantic and syntactic similarities between data in different services and create or modify workflows in applications mashups without enlisting the talents of the original developers or vendor. In fact, automatic matching tools help users to facilitate automatic integration of both data and APIs without knowing their structure and semantics. In this paper, the authors suggest a novel approach which consists in building a semantic mashup using a matching tool, domain ontology and a set of patterns to facilitate and automate services and data integration. As a study use case, they develop a semantic mashup application for a travel agency that provides a single interface to users.
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