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Semantic models of data sources describe the meaning of the data in terms of the concepts and relationships defined by a domain ontology. Building such models is an important step toward integrating data from different sources, where we need to provide the user with a unified view of underlying sources. In this paper, we present a scalable approach to automatically learn semantic models of a structured...
Drug-drug interaction (DDI) study is an important aspect of therapy management and drug efficacy. DDI study investigates how drugs interact with each other and determine whether these interactions may lead to dire effects or nullify the therapeutic effects of each other. In this paper we model metabolic pathways of drugs that include the reaction effects between drugs and the related enzymes. By modeling...
To inform citizens when they can use government services, governments publish the services' opening hours on their website. When opening hours would be published in a machine interpretable manner, software agents would be able to answer queries about when it is possible to contact a certain service. We introduce an ontology for describing opening hours and use this ontology to create an input form...
Incorporating structured data in the Linked Data cloud is still complicated, despite the numerous existing tools. In particular, hierarchical structured data (e.g., JSON) are underrepresented, due to their processing complexity. A uniform mapping formalization for data in different formats, which would enable reuse and exchange between tools and applied data, is missing. This paper describes a novel...
Detection of human behavior in On-line Social Networks (OSNs) has become more and more important for a wide range of applications, such as security, marketing, parent controls and so on, opening a wide range of novel research areas, which have not been fully addressed yet. In this paper, we present a two-stage method for anomaly detection in humans' behavior while they are using a social network....
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