Editorial

Semantic Web and Web 2.0

This paper provides empirical and experimental assessments of thematic knowledge discourses based on two case studies in the US Virgin Islands and Florida. We utilize a latent semantic indexing analysis over natural language corpus to classify and categorize knowledge categories. We computed TF*IDF scores and associated co-occurrence Jaccard similarity scores to construct semantic knowledge networks. Using network analysis, we computed structural metrics over four composite groups: neighbor-based, centrality, equivalence and position. The analysis show that structural network characteristics of environmental knowledge can exponentially predict associations between knowledge categories. We show that connectivity play a critical role on acquisition, representation, and diffusion patterns of knowledge within local communities. We provide evidence of a global prevalence of a shared knowledge core. We show that core social-ecological attributes of knowledge follow scale-free, power law distributions and stable, equilibrium network structures. We identify two distinct models of bidirectional translation: a bottom-up and a top-down.

The present paper introduces and reviews existing technology and research works in the field of e-Procurement. More specifically this survey aims to collect those relevant approaches that have tackled the challenge of delivering more advanced and intelligent e-Procurement management systems due to its relevance in the industry to afford more timely, adaptable and flexible decisions in purchasing processes. Although existing tools and techniques have demonstrated their ability to manage e-Procurement processes as a part of a supply management system there is a lack of interoperability among tools, tangled dependencies between processes or difficulties to exploit existing data and information to name a few that are preventing a proper use of the new dynamic and data-based environment. On the other hand semantic-based technologies emerge to provide the adequate building blocks to represent domain-knowledge and elevate the meaning of information resources through a common and shared data model (RDF) with a formal query language (SPARQL) and accessible via the Internet Protocols. In this sense the Linked Data effort has gained momentum to apply the principles of the aforementioned initiative to boost the re-use of information and data across different tools and processes. That is why authors review both existing open issues in the context e-Procurement with special focus on public procurement and semantic-based approaches to address them. To do so a preliminary research study is conducted to assess the state of the art in the context of e-Procurement and semantic-based systems. Afterwards main drawbacks of existing e-Procurement systems are presented to narrow down in semantic-based approaches applied to this field. Once the current status in both areas is reviewed, authors purpose the use and creation of an e-Procurement index to evaluate the quality of service of procurement systems. In this light the Analytical Hierarchy Process (AHP) method is used to set up an initial weight for each indicator in the index and to perform a first comparison between traditional and semantic-based approaches. Finally some discussion, conclusions and future challenges are also outlined.

Social Networks constitute the key ingredient for the huge success of the so called Social Web or Web 2.0. In social networks, a user has the possibility to interact with other users without the need of meeting them. The value of social applications benefits from the network effect, which states that the value of a service to a user arises from the number of people using the service. However, the associated semantics for this kind of applications, delivered through tagging, is generally scarce, thus narrowing the range of permissible operations for exploiting these data. In this paper, we present a semantic-based social platform that incorporates the benefits of semantic Web technologies into traditional social environments. The value of the proposed framework is twofold. First, the interaction of the users with the system gives rise to semantic content that can populate a knowledge base. Then, the social-side of the platform is improved by taking advantage of the captured semantics. SocialBROKER is a prototype implementation of the proposed platform customized for the eFinance domain. It allows for creating collaborative groups that define financial-related initiatives and proposals. The integration of Semantic Web concepts and Social Networks enables our system to automatically create semantically-empowered relationships between the investors registered within the platform based on their interactions. This further allows the system to analyze the social behavior of the network members and to generate a customized profile for each of them.