SharedLife: Towards Selective Sharing of Augmented Personal Memories

Wahlster, Wolfgang; Kröner, Alexander; Heckmann, Dominik

doi:10.1007/11829263_18

Cited by 9 publications

(4 citation statements)

References 14 publications

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“…For example, [9] deals with UM mediation between Trip@dvice trip planning system [62] and PIL personalized museum visitor's guide [41]. The issues of cross-context mediation will be extensively studied within practical scenarios in the SharedLife project, focusing on multi-user shopping scenarios complemented by everyday activities [72], and the Passepartout project focusing on search, browsing and viewing activities of individual and group users with a personalized digital TV guide [5].…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Mediation of user models for enhanced personalization in recommender systems

Berkovsky

Kuflik

Ricci

2007

User Model User-Adap Inter

171

124

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Abstract. Provision of personalized recommendations to users requires accurate modeling of their interests and needs. This paper proposes a general framework and specific methodologies for enhancing the accuracy of user modeling in recommender systems by importing and integrating data collected by other recommender systems. Such a process is defined as user models mediation. The paper discusses the details of such a generic user modeling mediation framework. It provides a generic user modeling data representation model, demonstrates its compatibility with existing recommendation techniques, and discusses the general steps of the mediation. Specifically, four major types of mediation are presented: cross-user, cross-item, cross-context, and crossrepresentation. Finally, the paper reports the application of the mediation framework and illustrates it with practical mediation scenarios. Evaluations of these scenarios demonstrate the potential benefits of user modeling data mediation, as in certain conditions it allows improving the quality of the recommendations provided to the users.

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Section: Conclusion and Future Researchmentioning

confidence: 99%

Mediation of user models for enhanced personalization in recommender systems

Berkovsky

Kuflik

Ricci

2007

User Model User-Adap Inter

171

124

View full text Add to dashboard Cite

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“…Although there has been research conducted into user-modelling (see [8] for a state-of-the-art survey), recommender strategies [12], and even scrutability [7,2,13], there is a gap between research with these individual themes and the practical application of these themes in working prototypes that have been evaluated by end-users.…”

Section: Related Workmentioning

confidence: 98%

Scrutable User Models and Personalised Item Recommendation in Mobile Lifestyle Applications

Wasinger

Wallbank

Pizzato

et al. 2013

User Modeling, Adaptation, and Personalization

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Abstract. This paper presents our work on supporting scrutable user models for use in mobile applications that provide personalised item recommendations. In particular, we describe a mobile lifestyle application in the fine-dining domain, designed to recommend meals at a particular restaurant based on a person's user model. The contributions of this work are three-fold. First is the mobile application and its personalisation engine for item recommendation using a content and critique-based hybrid recommender. Second, we illustrate the control and scrutability that a user has in configuring their user model and browsing a content list. Thirdly, this is validated in a user experiment that illustrates how new digital features may revolutionise the way that paper-based systems (like restaurant menus) currently work. Although this work is based on restaurant menu recommendations, its approach to scrutability and mobile client-side personalisation carry across to a broad class of commercial applications.

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“…Our project can be seen as an evolution of augmented memories systems, which enrich the human capabilities in recording and organizing experiences. SharedLife [Wahlster et al 2006] shows how the sharing of personal, augmented memories automatically built from context information may support users in different situations. Our approach focuses on the interaction with intelligent objects A:30 Piemonte Team that record experiences and non-linear stories explicitly added by users, and on the social communication that can be stimulated by similar experiences.…”

Section: Related Workmentioning

confidence: 99%

Interacting with social networks of intelligent things and people in the world of gastronomy

Console

Antonelli

Biamino

et al. 2013

ACM Trans. Interact. Intell. Syst.

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This article introduces a framework for creating rich augmented environments based on a social web of intelligent things and people. We target outdoor environments, aiming to transform a region into a smart environment that can share its cultural heritage with people, promoting itself and its special qualities. Using the applications developed in the framework, people can interact with things, listen to the stories that these things tell them, and make their own contributions. The things are intelligent in the sense that they aggregate information provided by users and behave in a socially active way. They can autonomously establish social relationships on the basis of their properties and their interaction with users. Hence when a user gets in touch with a thing, she is also introduced to its social network consisting of other things and of users; she can navigate this network to discover and explore the world around the thing itself. Thus the system supports serendipitous navigation in a network of things and people that evolves according to the behavior of users. An innovative interaction model was defined that allows users to interact with objects in a natural, playful way using smartphones without the need for a specially created infrastructure. The framework was instantiated into a suite of applications called WantEat, in which objects from the domain of tourism and gastronomy (such as cheese wheels or bottles of wine) are taken as testimonials of the cultural roots of a region. WantEat includes an application that allows the definition and registration of things, a mobile application that allows users to interact with things, and an application that supports stakeholders in getting feedback about the things that they have registered in the system. WantEat was developed and tested in a real-world context which involved a region and gastronomy-related items from it (such as products, shops, restaurants, and recipes), through an early evaluation with stakeholders and a final evaluation with hundreds of users.

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SharedLife: Towards Selective Sharing of Augmented Personal Memories

Cited by 9 publications

References 14 publications

Mediation of user models for enhanced personalization in recommender systems

Mediation of user models for enhanced personalization in recommender systems

Scrutable User Models and Personalised Item Recommendation in Mobile Lifestyle Applications

Interacting with social networks of intelligent things and people in the world of gastronomy

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