No abstract

Abstract. We describe the user modeling and personalization techniques adopted in SETA, a shell supporting the construction of adaptive Web stores which customize the interactions with users, suggesting the items best fitting their needs, and adapting the description of the store catalog to their preferences and expertise. SETA uses stereotypical information to handle the user models and applies personalization rules to dynamically generate the hypertextual pages presenting products: the system adapts the graphical aspect, length and terminology used in the descriptions to the user's receptivity, expertise and interests. Moreover, it maintains a profile associated to each person the goods are selected for, to provide multiple criteria for the selection of items, tailored to the beneficiaries' preferences.

Abstract.This paper aims to demonstrate that the principles of adaptation and user modeling, especially social annotation, can be integrated fruitfully with those of the Web 2.0 paradigm and thereby enhance in the domain of cultural heritage. We propose a framework for improving recommender systems through exploiting the users tagging activity. We maintain that Web 2.0's participative features can be exploited by adaptive web-based systems in order to enrich and extend the user model, improve social navigation and enrich information from a bottom-up perspective. Thus our approach stresses social annotation as a new and powerful kind of feedback and as a way to infer knowledge about users. The prototype implementation of our framework in the domain of cultural heritage is named iCITY. It is serving to demonstrate the validity of our approach and to highlight the benefits of this approach specifically for cultural heritage. iCITY is an adaptive, social, multi-device recommender guide that provides information about the cultural resources and events promoting the cultural heritage in the city of Torino. Our paper first describes this system and then discusses the results of a set of evaluations that were carried out at different stages of the systems development and aimed at validating the framework and implementation of this specific prototype. In particular, we carried out a heuristic evaluation and two sets of usability tests, aimed at checking the usability of the user interface, specifically of the adaptive behavior of the system. Moreover, we conducted evaluations aimed at investigating the role of tags in the definition of the user model and the impact of tags on the accuracy of recommendations. Our results are encouraging.

Abstract. This chapter is about personalization and adaptation in electronic commerce (e-commerce) applications. In the first part, we briefly introduce the challenges posed by e-commerce and we discuss how personalization strategies can help companies to face such challenges. Then, we describe the aspects of personalization, taken as a general technique for the customization of services to the user, which have been successfully employed in e-commerce Web sites. To conclude, we present some emerging trends and and we discuss future perspectives.

Fault management in Web Services composed by individual services from multiple suppliers currently relies on a local analysis, that does not span across individual services, thus limiting the effectiveness of recovery strategies. We propose to address this limitation of current standards for Web Service composition by employing Model-Based Diagnosis to enhance fault analysis. We propose to add Diagnostic Web Services to the set of Web Services providing the overall service, acting as supervisors of their execution, by identifying anomalies and explaining them in terms of faults to be repaired. This approach poses the basis for the development of specialized recovery and compensation techniques aimed at addressing different problems, which could not be otherwise discriminated.

The emerging standards for the publication of Web Services enable the invocation of services having simple interaction protocols, but they fail to support complex e-business interactions, where the peers exchange several messages. In order to extend the classes of services which can be invoked by the consumers, we propose a conversational model supporting the management of complex interactions between clients and Web Services. Our model supports the consumer in the management of a conversation which respects the business logic of the service without imposing the explicit management of the conversational context.

No abstract

Although personalization and ubiquity are key properties for on-line services, they challenge the development of these systems due to the complexity of the required architectures. In particular, the current infrastructures for the development of personalized, ubiquitous services are not flexible enough to accommodate the configuration requirements of the various application domains. To address such issues, highly configurable infrastructures are needed.In this article, we describe Seta2000, an infrastructure for the development of recommender systems that support personalized interactions with their users and are accessible from different types of devices (e.g., desktop computers and mobile phones). The Seta2000 infrastructure offers a built-in recommendation engine, based on a multi-agent architecture. Moreover, the infrastructure supports the integration of heterogeneous software and the development of agents that can be configured to offer specialized facilities within a recommender system, but also to dynamically enable and disable such facilities, depending on the requirements of the application domain. The Seta2000 infrastructure has been exploited to develop two prototypes: SeTA is an adaptive Web store personalizing the recommendation and presentation of products in the Web. INTRIGUE is a personalized, ubiquitous information system suggesting attractions to possibly heterogeneous tourist groups.