Recommender Systems (RSs) are software tools and techniques providing suggestions for items to be of use to a user. In this introductory chapter we briefly discuss basic RS ideas and concepts. Our main goal is to delineate, in a coherent and structured way, the chapters included in this handbook and to help the reader navigate the extremely rich and detailed content that the handbook offers.

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Introduction to Recommender Systems Handbook

One distinctive feature of any adaptive system is the user model that represents essential information about each user This chapter complements other chapters of this book in reviewing user models and user modeling approaches applied in adaptive Web systems The presentation is structured along three dimensions: what is being modeled, how it is modeled, and how the models are maintained After a broad overview of the nature of the information presented in these various user models, the chapter focuses on two groups of approaches to user model representation and maintenance: the overlay approach to user model representation and the uncertainty-based approach to user modeling

User models for adaptive hypermedia and adaptive educational systems

The paper reviews the development of generic user modeling systems over the past twenty years. It describes their purposes, their services within user-adaptive systems, and the different design requirements for research prototypes and commercially deployed servers. It discusses the architectures that have been explored so far, namely shell systems that form part of the application, central server systems that communicate with several applications, and possible future user modeling agents that physically follow the user. Several implemented research prototypes and commercial systems are briefly described.

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Generic User Modeling Systems

The definition of context experienced an evolution in the research area of context-aware computing, but still suffers from either generality or incompleteness. Furthermore, many definitions are driven by the ease of implementation. This paper introduces two extensions to available context definitions that provide a natural understanding of this concept to users of context-aware applications and facilitates the engineering of this concept for software developers of such applications.

An operational definition of context

We introduce the general user model ontology Gumo for the uniform interpretation of distributed user models in intelligent semantic web enriched environments. We discuss design decisions, show the relation to the user model markup language UserML and present the integration of ubiquitous applications with the u2m.org user model service.

Gumo: the general user model ontology

Ubiquitous computing offers new chances and challenges to the field of user modeling. With the markup language UserML, we try to contribute a platform for the communication about partial user models in a ubiquitous computing environment, where all different kinds of systems work together to satisfy the user's needs. We also present an implementation architecture of a general user model editor which is based on UserML. The keywords are ubiquitous computing, distributed user modeling and markup languages.

A user modeling markup language (userML) for ubiquitous computing

We present a new architecture for decentralized user modeling and briefly discuss the user model markup language USERML, the general user model ontology GUMO for the uniform interpretation of decentralized user models, and the integration of ubiquitous applications with the u2m.org user model service. The motivation is that ubiquitous evaluation of user behavior with a variety of systems in the web or the physical world might lead to attractive new services. 1 Approach and Architecture We developed the RDF-based user model exchange language UserML to enable decentralized systems to communicate over user models. The idea is to spread the information among all adaptive systems, either with a mobile device or via ubiquitous networks. UserML statements can be arranged and stored in distributed repositories in XML, RDF or SQL. Each mobile and stationary device has an own repository of situational statements, either local or global, dependent on the network accessability. A mobile device can perfectly be integrated via wireless lan or bluetooth into the intelligent environment, while a stationary device could be isolated without network access. The different applications or agents produce or use UserML statements Fig. 1. The syntax-semantics interplay between USERML and GUMO to represent the user model information. UserML forms the syntactic description in the knowledge exchange process, see figure 1. Each concept like the user model auxiliary 62 Dominik Heckmann et al. hasProperty and the user model dimension timePressure points to a semantical definition of this concept which is either defined in the general user model ontology GUMO, the UbisWorld ontology, which is specialized for ubiquitous computing, or the general SUMO/MILO ontology, see [1]. The merging of partial, decentralized user models is realized by combining the different user model repositories, while the inferential integration is done by filters and conflict resolution strategies as shown in figure 2(b). Figure 2(a) and figure 2(c) show the upward and downward inference from repositories or journals to the user model and vice versa.

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Decentralized User Modeling with UserML and GUMO

We revisit the top-level ontology Gumo for the uniform management of user and context models in a semantic web environment. We discuss design decisions, while putting the focus on ontological issues. The structural integration into user model servers, especially into the U2M-UserModel&ContextService, is also presented. We show ubiquitous applications using the user model ontology Gumo together with the user model markup language UserML. Finally, we ask how data from Web 2.0 and especially from a social tagging application like del.icio.us as a basis for user adaptation and context-awareness could influence the ontology.

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The User Model and Context Ontology GUMO Revisited for Future Web 2.0 Extensions.

In this chapter we discuss various aspects of adaptive mobile guide applications. After having motivated the need for web based mobile applications, we will discuss technologies that are needed to enable adaptive mobile web applications, including not only positioning technologies but also sensor technologies needed to determine additional information on the context and situation of usage. We will also address issues of modeling context and situations before giving an overview on existing systems coming from three important classes of mobile guides: museum guides, navigation systems and shopping assistants. The chapter closes with an extensive discussion of relevant attributes of web based mobile guides.

Dominik Heckmann

Papers

Gumo: the general user model ontology

A user modeling markup language (userML) for ubiquitous computing

Decentralized User Modeling with UserML and GUMO

The User Model and Context Ontology GUMO Revisited for Future Web 2.0 Extensions.

Adaptive mobile guides