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57
Adaptive interfaces and agents
, 2003
"... As its title suggests, this chapter covers a broad range of in-teractive systems. But they all have one idea in common: that it can be worthwhile for a system to learn something about each individual user and adapt its behavior to them in ..."
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Cited by 101 (10 self)
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As its title suggests, this chapter covers a broad range of in-teractive systems. But they all have one idea in common: that it can be worthwhile for a system to learn something about each individual user and adapt its behavior to them in
Social Matching: A Framework and Research Agenda • 433
, 2000
"... Social matching systems bring people together in both physical and online spaces. They have the potential to increase social interaction and foster collaboration. However, social matching systems lack a clear intellectual foundation: the nature of the design space, the key research challenges, and t ..."
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Cited by 99 (4 self)
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Social matching systems bring people together in both physical and online spaces. They have the potential to increase social interaction and foster collaboration. However, social matching systems lack a clear intellectual foundation: the nature of the design space, the key research challenges, and the roster of appropriate methods are all ill-defined. This article begins to remedy the situation. It clarifies the scope of social matching systems by distinguishing them from other recommender systems and related systems and techniques. It identifies a set of issues that characterize the design space of social matching systems and shows how existing systems explore different points within the design space. It also reviews selected social science results that can provide input into system design. Most important, the article presents a research agenda organized around a set of claims. The claims embody our understanding of what issues are most important to investigate, our beliefs about what is most likely to be true, and our suggestions of specific research directions to pursue.
Introduction to Recommender Systems Handbook
- RECOMMENDER SYSTEMS HANDBOOK
, 2011
"... 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 ..."
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Cited by 56 (5 self)
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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
Case-Based Recommendation
, 2007
"... Recommender systems try to help users access complex information spaces. A good example is when they are used to help users to access online product catalogs, where recommender systems have proven to be especially useful for making product suggestions in response to evolving user needs and preferen ..."
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Cited by 50 (12 self)
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Recommender systems try to help users access complex information spaces. A good example is when they are used to help users to access online product catalogs, where recommender systems have proven to be especially useful for making product suggestions in response to evolving user needs and preferences. Case-based recommendation is a form of content-based recommendation that is well suited to many product recommendation domains where individual products are described in terms of a well defined set of features (e.g., price, colour, make, etc.). These representations allow case-based recommenders to make judgments about product similarities in order to improve the quality of their recommendations and as a result this type of approach has proven to be very successful in many e-commerce settings, especially when the needs and preferences of users are ill-defined, as they often are. In this chapter we will describe the basic approach to case-based recommendation, highlighting how it differs from other recommendation technologies, and introducing some recent advances that have led to more powerful and flexible recommender systems.
Ontology-based user modeling for Knowledge Management Systems
- in Proceedings of "UM2003 User Modeling: Proceedings of the Ninth International Conference
, 2003
"... Abstract This paper is presenting a generic ontology-based user modeling architecture, (OntobUM), applied in the context of a Knowledge Management System (KMS). Due to their powerful knowledge representation formalism and associated inference mechanisms, ontology-based systems are emerging as a natu ..."
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Cited by 46 (6 self)
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Abstract This paper is presenting a generic ontology-based user modeling architecture, (OntobUM), applied in the context of a Knowledge Management System (KMS). Due to their powerful knowledge representation formalism and associated inference mechanisms, ontology-based systems are emerging as a natural choice for the next generation of KMSs operating in organizational, interorganizational as well as community contexts. User models, often addressed as user profiles, have been included in KMSs mainly as simple ways of capturing the user preferences and/or competencies. We extend this view by including other characteristics of the users relevant in the KM context and we explain the reason for doing this. The proposed user modeling system relies on a user ontology, using Semantic Web technologies, based on the IMS LIP specifications, and it is integrated in an ontology-based KMS called Ontologging. We are presenting a generic framework for implicit and explicit ontology-based user modeling. 1.
Personalization in e-commerce applications
, 2007
"... 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 ..."
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Cited by 17 (0 self)
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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 per-sonalization, taken as a general technique for the customization of services to the user, which have been successfully employed in e-commerce Web sites. To con-clude, we present some emerging trends and and we discuss future perspectives. Electronic commerce includes different types of activities related to the online sales of goods and services. For instance, the ameris glossary defines e-commerce (EC) as follows [10]: “The conducting of business communication and transactions over net-works and through computers. As most restrictively defined, electronic commerce is
Survey of Data Mining Approaches to User Modeling for Adaptive Hypermedia
- IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART C: APPLICATIONS AND REVIEWS
, 2006
"... The ability of an adaptive hypermedia system to create tailored environments depends mainly on the amount and accuracy of information stored in each user model. Some of the difficulties that user modeling faces are the amount of data available to create user models, the adequacy of the data, the noi ..."
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Cited by 15 (3 self)
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The ability of an adaptive hypermedia system to create tailored environments depends mainly on the amount and accuracy of information stored in each user model. Some of the difficulties that user modeling faces are the amount of data available to create user models, the adequacy of the data, the noise within that data, and the necessity of capturing the imprecise nature of human behavior. Data mining and machine learning techniques have the ability to handle large amounts of data and to process uncertainty. These characteristics make these techniques suitable for automatic generation of user models that simulate human decision making. This paper surveys different data mining techniques that can be used to efficiently and accurately capture user behavior. The paper also presents guidelines that show which techniques may be used more efficiently according to the task implemented by the application. Index Terms—Adaptive hypermedia (AH), data mining, machine learning, user modeling (UM). I.
V.: A user modeling server for contemporary adaptive hypermedia: An evaluation of the push approach to evidence propagation
- In: 11th International Conference on User Modeling
, 2007
"... Abstract. Despite the growing popularity of user modeling servers, little attention has been paid to optimizing and evaluating the performance of these servers. We argue that implementation issues and their influence on server performance should become the central focus of the user modeling communit ..."
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Cited by 14 (2 self)
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Abstract. Despite the growing popularity of user modeling servers, little attention has been paid to optimizing and evaluating the performance of these servers. We argue that implementation issues and their influence on server performance should become the central focus of the user modeling community, since there is a sharply increasing real-life load on user modeling servers, This paper focuses on a specific implementation-level aspect of user modeling servers – the choice of push or pull approaches to evidence propagation. We present a new push-based implementation of our user modeling server CUMULATE and compare its performance with the performance of the original pull-based CUMULATE server. 1
F.: Cross-technique mediation of user models
- In: Proceedings of International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems [AH2006
, 2006
"... Abstract. Nowadays, personalization is considered a powerful approach for designing more precise and easy to use information search and recommendation tools. Since the quality of the personalization provided depends on the accuracy of the user models (UMs) managed by the system, it would be benefic ..."
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Cited by 11 (1 self)
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Abstract. Nowadays, personalization is considered a powerful approach for designing more precise and easy to use information search and recommendation tools. Since the quality of the personalization provided depends on the accuracy of the user models (UMs) managed by the system, it would be beneficial enriching these models through mediating partial UMs, built by other services. This paper proposes a cross-technique mediation of the UMs from collaborative to content-based services. According to this approach, content-based recommendations are built for the target users having no content-based user model, knowing his collaborative-based user model only. Experimental evaluation conducted in the domain of movies, shows that for small UMs, the personalization provided using the mediated content-based UMs outperforms the personalization provided using the original collaborative UMs.
R.: PersonisJ: Mobile, Client-Side User Modelling
- In: Proceedings of the International Conference on User Modeling, Adaptation and Personalization (UMAP
, 2010
"... Abstract. The increasing trend towards powerful mobile phones opens many possibilities for valuable personalised services to be available on the phone. Client-side personalisation for these services has important benefits when connectivity to the cloud is restricted or unavailable. The user may also ..."
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Cited by 10 (3 self)
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Abstract. The increasing trend towards powerful mobile phones opens many possibilities for valuable personalised services to be available on the phone. Client-side personalisation for these services has important benefits when connectivity to the cloud is restricted or unavailable. The user may also find it desirable when they prefer that their user model be kept only on their phone and under their own control, rather than un-der the control of the cloud-based service provider. This paper describes PersonisJ, a user modelling framework that can support client-side per-sonalisation on the Android phone platform. We discuss the particular challenges in creating a user modelling framework for this platform. We have evaluated PersonisJ at two levels: we have created a demonstrator application that delivers a personalised museum tour based on client-side personalisation; we also report on evaluations of its scalability. Contribu-tions of this paper are the description of the architecture, the implemen-tation, and the evaluation of a user modelling framework for client-side personalisation on mobile phones. 1
