RSS-based Interoperability for User Adaptive Systems
Yiwen Wang2, Federica Cena1, Francesca Carmagnola1, Omar Cortassa1, Cristina Gena1, Natalia Stash2, and Lora Aroyo23
1 Dipartimento di Informatica, Universit`
a di Torino Corso Svizzera 185, Torino, Italy {carmagnola, cena, cgena}@di.unito.it
2 Eindhoven University of Technology, Computer Science
{n.v.stash, y.wang}@tue.nl
3 VU University Amsterdam, Computer Science
l.m.aroyo@cs.vu.nl
- Abstract. This paper presents an approach to exploit widely used tag
annotations to address two important issues in user-adaptive systems: the cold-start problem and the integration of distributed user models. The paper provides an example of re-use of user interaction data (tags) generated by one application into another one in similar domains for providing cross-system recommendations.
1 Introduction
The Web 2.0 phenomenon introduced various social applications enabling on- line collaboration and encouraging the participation and contribution of spon- taneous social networks. Users are increasingly involved in multiple Web 2.0 environments, such as Facebook.com, Flickr.com, Del.icio.us, etc. However these applications are still “digital islands” in terms of personalized experience - not truly interconnected in a way which allows users to capitalize on the full potential
- f a distributed multi-application environment. Most of those services maintain
a different identity, e.g. login information, preferences or profile of users with a limited integration of these data between different applications. However, tags inserted by users could be extremely useful for adaptive web applications [2], e.g. to enrich and extend the user model. User usually tags to highlight and organize the items she is interested in, in order to retrieve them later. Thus the action
- f tagging can be be analyzed in order to make interesting inferences on the
user model [3]. The exploitation of tags for improving the user model, requires that systems could understand the semantics of the tags (e.g., applying suitable strategies borrowed from automatic Word Senses Disambiguation). The focus of this paper is to illustrate how existing fragments of user data in the form of tags can be brought together with the help of explicit semantics, and in this way allow for an adequate personalized experience across the boundaries of particular applications. This poses a considerable number of technological de-
- mands. Working in a distributed setting implies that personalization considers