Semantic pervasive advertising

Abstract. Pervasive advertising targets consumers on-the-move with ads displayed on their mobile devices. As for web advertising, ads are distributed by embedding them into websites and apps, easily flooding consumers with a large number of uninteresting offers. As the pervasive setting amplifies traditional issues such as targeting, cost, and privacy, we argue the need for a new perspective on the problem. We introduce PervADs, a privacy-preserving, user-centric, and pervasive ads-distribution platform which uses semantic technologies to reason about the consumer's context and the intended target of the ads

An ontology system for rehabilitation robotics

Representing the available information about rehabilitation robots in a structured form, like ontologies, facilitates access to various kinds of information about the existing robots, and thus it is important both from the point of view of rehabilitation robotics and from the point of view of physical medicine. Rehabilitation robotics researchers can learn various properties of the existing robots and access to the related publications to further improve the state-of-the-art. Physical medicine experts can find information about rehabilitation robots and related publications (possibly including results of clinical studies) to better identify the right robot for a particular therapy or patient population. Therefore, considering also the advantages of ontologies and ontological reasoning, such as interoperability of various heterogenous knowledge resources (e.g., patient databases or disease ontologies), such an ontology provides the underlying mechanisms for translational physical medicine, from bench-to-bed and back, and personalized rehabilitation robotics. In this thesis, we introduce the first formal rehabilitation robotics ontology, called RehabRobo-Onto, to represent information about rehabilitation robots and their properties. We have designed and developed RehabRobo-Onto in OWL, collaborating with experts in robotics and in physical medicine. We have also built a software (called RehabRobo- Query) with an easy-to-use intelligent user-interface that allows robot designers to add/modify information about their rehabilitation robots to/from RehabRobo-Onto. With RehabRobo-Query, the experts do not need to know about the logic-based ontology languages, or have experience with the existing Semantic Web technologies or logic-based ontological reasoners. RehabRobo-Query is made available on the cloud, utilizing Amazon Web services, so that rehabilitation robot designers around the world can add/modify information about their robots in RehabRobo-Onto, and rehabilitation robot designers and physical medicine experts around the world can access the knowledge in RehabRobo-Onto by means of questions about robots, in natural language, with the guide of the intelligent userinterface of RehabRobo-Query. The ontology system consisting of RehabRobo-Onto and RehabRobo- Query is of great value to robot designers as well as physical therapists and medical doctors. On the one hand, robot designers can access various properties of the existing robots and to the related publications to further improve the state-of-the-art. On the other hand, physical therapists and medical doctors can utilize the ontology to compare rehabilitation robots and to identify the ones that serve best to cover their needs, or to evaluate the effects of various devices for targeted joint exercises on patients with specific disorders

Context Based Querying of Dynamic and Heterogeneous Information Sources

The proliferation of freely-accessible data-intensive websites, the growing availability of pervasive and mobile applications, as well as initiatives for open-accessible linked data in the Web, provided the users with potential sources of valuable information. These data also represent new business opportunities for industries, while their processing and management is a rich research field for academics. In addition, pervasiveness and mobility make information available everywhere and at any time; therefore, user-centred, dynamic and on-the-fly integration of heterogeneous becomes extremely useful in practical situations such as mobile data management, in particular with devices as tablets, pads and smartphones. We present a methodology and a set of technologies for ontology-driven, context-aware data-integration systems capable of seamlessly handling heterogeneous and dynamic data sources in a dynamic environment where the possibly mobile, transient and evolving data sources are not known in advance. In such Nomadic Data-Integration Systems (N-DIS), query answering is driven by an ontology and the context is used to formally represent the situations in which the users or the applications need to operate. In our work, we re-think query-answering techniques coming from description logics and database theory, and we apply them to an evolving scenario, composed by heterogeneous data sources with the additional constraint of the context-based personalisation of queries and, as a consequence, of their answers. The concept of N-DIS and the corresponding design methodology has been applied to various application fields such as decision support for medical-emergency situations, Semantic-Web meta-data management, Semantic Search and pervasive advertisement, with promising results

Context Based Querying of Dynamic and Heterogeneous Information Sources

The proliferation of freely-accessible data-intensive websites, the growing availability of pervasive and mobile applications, as well as initiatives for open-accessible linked data in the Web, provided the users with potential sources of valuable information. These data also represent new business opportunities for industries, while their processing and management is a rich research field for academics. In addition, pervasiveness and mobility make information available everywhere and at any time; therefore, user-centred, dynamic and on-the-fly integration of heterogeneous becomes extremely useful in practical situations such as mobile data management, in particular with devices as tablets, pads and smartphones. We present a methodology and a set of technologies for ontology-driven, context-aware data-integration systems capable of seamlessly handling heterogeneous and dynamic data sources in a dynamic environment where the possibly mobile, transient and evolving data sources are not known in advance. In such Nomadic Data-Integration Systems (N-DIS), query answering is driven by an ontology and the context is used to formally represent the situations in which the users or the applications need to operate. In our work, we re-think query-answering techniques coming from description logics and database theory, and we apply them to an evolving scenario, composed by heterogeneous data sources with the additional constraint of the context-based personalisation of queries and, as a consequence, of their answers. The concept of N-DIS and the corresponding design methodology has been applied to various application fields such as decision support for medical-emergency situations, Semantic-Web meta-data management, Semantic Search and pervasive advertisement, with promising results