Narrow Results

This paper aims to describe a public procurement information platform which provides a unified pan-European system that exploits the aggregation of tender notices using linking open data and semantic web technologies. This platform requires a step-based method to deal with the requirements of the public procurement sector and the open government data initiative: (1) modeling the unstructured information included in public procurement notices (contracting authorities, organizations, contracts awarded, etc.); (2) enriching that information with the existing product classification systems and the linked data vocabularies; (3) publishing relevant information extracted out of the notices following the linking open data approach; (4) implementing enhanced services based on advanced algorithms and techniques like query expansion methods to exploit the information in a semantic way. Taking into account that public procurement notices contain different kinds of data like types of contract, region, duration, total amount, target enterprise, etc., various methods can be applied to expand user queries easing the access to the information and providing a more accurate information retrieval system. Nevertheless expanded user queries can involve an extra-time in the process of retrieving notices. That is why a performance evaluation is outlined to tune up the semantic methods and the generated queries providing a scalable and time-efficient system. Moreover, this platform is supposed to be especially relevant for SMEs that want to tender in the European Union (EU), easing their access to the information of the notices and fostering their participation in cross-border public procurement processes across Europe. Finally an example of use is provided to evaluate and compare the goodness and the improvement of the proposed platform with regard to the existing ones.

The ability to efficiently and effectively reuse ontologies is commonly acknowledged to play a crucial role in the large scale dissemination of ontologies and ontology-driven technology, being thus a pre-requisite for the ongoing realization of the Semantic Web. In this article, we give an account of ontology reuse from a process point of view. We present a methodology that can be utilized to systematize and monitor ontology engineering processes in scenarios reusing available ontological knowledge in the context of a particular application. Notably, and by contrast to existing approaches in this field, our aim is to provide means to overcome the poor reusability of existing resources — rather than to solve the more general issue of building new, more reusable knowledge components. To do so we investigate the impact of the application context of an ontology — in terms of tasks this ontology has been created for and will be utilized in — has on the feasibility of a reuse-oriented ontology development strategy and provide guidelines that take these aspects into account. The applicability of the methodology is demonstrated through a case study performed in collaboration with an international eRecruitment solution provider.

A novel approach to trend monitoring and the identification of promising high-tech solutions is presented in the chapter. It is based on the ontology of a technology/market trend, Hype Cycles methodology, and semantic indicators which provide evidence of a maturity level of a technology as well as of emerging user needs (customer pains) in high-tech industries. This approach forms the basis for text mining software tools implemented in Semantic Hub platform. The algorithms behind these tools allow users to escape from getting too general or garbage results which make it impossible to identify promising technologies at early stages (early detection, weak signals). Besides, these algorithms provide high-quality results in the extraction of complex multiword terms which correspond to technological concepts and user pains forming a trend. The methodology and software developed as a result of this study are applicable to various industries with minor adjustments.