Ismael Rivera

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Today's personal devices provide a stream of information which, if processed adequately, can provide a better insight into their owner's current activities, environment, location, etc. In treating these devices as part of a personal sensor network, we exploit raw and interpreted context information in order to enable the automatic recognition of personal(More)
Depression and anxiety are of the most commonly occurring mental health disorders in the United States. Despite a variety of efficacious interventions for depression and anxiety, it is clear that ethnic minorities experience mental health care disparities in their access to mental health services and the quality of treatment they receive. Research indicates(More)
Taking into consideration the steady shift towards information digitisation, an increasing number of approaches are targeting the unification of the user’s digital “Personal Information Sphere”to increase user awareness, provide singlepoint management, and enable context-driven recommendation. The Personal Information Sphere refers to both conventional(More)
The transfer of the mashup paradigm in corporate environments needs additional capabilities beyond those typically associated with consumer mashups. In this paper, we present the architecture of the FAST platform which allows creating enterprise-class and multi-channel visual building blocks (so called gadgets) in an ad-hoc manner. The design of complex(More)
Efforts by the pervasive, context-aware system development community have over the years produced a wide variety of context-aware techniques and frameworks. However, a bulk of this technology tends to be strictly tied to a native system, thus largely limiting its external adoption. In addressing this limitation, we introduce an interoperable context(More)
Users are currently required to create and separately manage duplicated personal data in heterogeneous online accounts. Our approach targets the crawling, retrieval and integration of this data, based on a comprehensive ontology framework which serves as a standard format. The motivation for this integration is to enable single point management of the(More)
Nowadays, smart devices perceive a large amount of information from device sensors, usage, and other sources which contribute to defining the user’s context and situations. The main problem is that although the data is available, it is not processed to help the user deal with this information easily. Our approach is based on the assumption that, given that(More)
Instance matching targets the extraction, integration and matching of instances referring to the same real-world entity. In this paper we present a weighted ontology-based user profile resolution technique which targets the discovery of multiple online profiles that refer to the same person identity. The elaborate technique takes into account profile(More)