Social Media have emerged as an additional interaction channel for companies with their partners, employees and customers. However, the pace of interaction in this channel is as high as the data volume that may be relevant for businesses. Therefore, mechanisms other than manually monitoring and analyzing this data are needed. Basic approaches have emerged in the areas of Social Search and Socia...

Recommender algorithms have been quite successfully employed in a variety of scenarios from filtering applications to recommendations of movies and books at Amazon.com. However, all these algorithms focus on single item recommendations and do not consider any more complex recommendation structures. This paper explores how semantically rich complex recommendation structures, represented as RDF g...

The Gene Ontology captures information at a very small scale, namely: molecular function, biological process, and cellular components. At this level, the Gene Ontology project should be capable of developing a semantics for every relation of genomic data to protein synthesis to the biological processes that result. In essence, the Gene Ontology should be able to describe the complete biomechani...

Context-aware systems must be interoperable and work across different platforms at any time and in any place. Context data collected from wireless body area networks (WBAN) may be heterogeneous and imperfect, which makes their design and implementation difficult. In this research, we introduce a model which takes the dynamic nature of a context-aware system into consideration. This model is con...

In the recent years, the number of social network users has increased dramatically. The resulting amount of data associated with users of social networks has created great opportunities for data mining problems. One data mining problem of interest for social networks is the friendship link prediction problem. Intuitively, a friendship link between two users can be predicted based on their commo...

The development and verification of software models that are applicable across multiple domains remains a difficult problem. We propose a novel approach to model-driven software development based on ontologies and Semantic Web technology. Our approach uses three ontologies to define software models: a task ontology, a domain ontology and a top-level ontology. The task ontology serves as the con...

In the FEARLUS (Framework for the Evaluation and Assessment of Regional Land Use Scenarios) project, we have developed a methodology for experimenting with our agent-based model of land use change. In a collaboration with the University of Aberdeen (one of the ESRC’s e-Social Science Initiative Pilot Demonstrator Projects), we have developed an ontology for this methodology, and enabled access ...

The field of multiagent systems has experienced an important growth and evolution in the past few years. Due to the agent autonomy and their need for cooperation, special attention has been paid to reputation mechanism. Several reputation models have appeared in literature offering solutions to this problem. However, each one uses their own concepts, terminology and ways to represent evaluation...

The past year has seen a dramatic increase in the amount of social information published in RDF documents. Our investigations [1, 2] show that the Friend of a Friend (FOAF) ontology [3] is among the most used semantic web ontologies. This is true if we measure the number of semantic web documents (SWDs) that use the FOAF namespace, as Table I shows, or the number of triples using FOAF terms. Th...