Challenges in User Modeling and Personalization

Bra, Paul De

doi:10.1109/mis.2017.3711638

Cited by 16 publications

(7 citation statements)

References 7 publications

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“…Finally, a set of challenges for user modeling and personalization are outlined in [79]; in particular, the scrutable user modeling and adaptation, which becomes very hard when the adaptation is based on collective behavior: data mining, machine learning techniques, and deep neural networks are not still capable of explaining the conclusions that lead to a specific recommendation. A second issue is the repeatability of the research results in different contexts.…”

Section: User's Profilingmentioning

confidence: 99%

Site Experience Enhancement and Perspective in Cultural Heritage Fruition—A Survey on New Technologies and Methodologies Based on a “Four-Pillars” Approach

et al. 2021

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This paper deals with innovative fruition modalities of cultural heritage sites. Based on two ongoing experiments, four pillars are considered, that is, User Localization, Multimodal Interaction, User Understanding and Gamification. A survey of the existing literature regarding one or more issues related to the four pillars is proposed. It aims to put in evidence the exploitation of these contributions to cultural heritage. It is discussed how a cultural site can be enriched, extended and transformed into an intelligent multimodal environment in this perspective. This new augmented environment can focus on the visitor, analyze his activity and behavior, and make his experience more satisfying, fulfilling and unique. After an in-depth overview of the existing technologies and methodologies for the fruition of cultural interest sites, the two experiments are described in detail and the authors’ vision of the future is proposed.

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Section: User's Profilingmentioning

confidence: 99%

Site Experience Enhancement and Perspective in Cultural Heritage Fruition—A Survey on New Technologies and Methodologies Based on a “Four-Pillars” Approach

et al. 2021

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“…The topic has gained significant attention in research on web engineering and intelligent systems [5,6], and the main artificial intelligence -based methods have been examined in the context of personalization. Rule-based approaches have been proposed for presenting content -e.g., for choosing the ordering, emphasis, or scaling of content or how to frame messages or use colors [7,9,12]. One clear challenge is to articulate a rule system that can account for numerous individual-specific characteristics and diverse design spaces.…”

Section: Web Personalizationmentioning

confidence: 99%

Responsive and Personalized Web Layouts with Integer Programming

Laine

Santala

Jokinen

et al. 2021

Proc. ACM Hum.-Comput. Interact.

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Over the past decade, responsive web design (RWD) has become the de facto standard for adapting web pages to a wide range of devices used for browsing. While RWD has improved the usability of web pages, it is not without drawbacks and limitations: designers and developers must manually design the web layouts for multiple screen sizes and implement associated adaptation rules, and its "one responsive design fits all" approach lacks support for personalization. This paper presents a novel approach for automated generation of responsive and personalized web layouts. Given an existing web page design and preferences related to design objectives, our integer programming -based optimizer generates a consistent set of web designs. Where relevant data is available, these can be further automatically personalized for the user and browsing device. The paper includes presentation of techniques for runtime adaptation of the designs generated into a fully responsive grid layout for web browsing. Results from our ratings-based online studies with end users (N = 86) and designers (N = 64) show that the proposed approach can automatically create high-quality responsive web layouts for a variety of real-world websites.

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“…Figure 1: The user modelling-adaptation loop (De Bra, 2017) In essence, the idea of personalized nudges inherently encloses the application of AI techniques and methods for understanding and anticipating the privacy needs of each particular user. For this, it is necessary to define what is commonly known as the "user model" of the system.…”

Section: The Role Of Aimentioning

confidence: 99%

“…For this, it is necessary to define what is commonly known as the "user model" of the system. That is, a set of adaptation variables that will guide the personalization process of behavioural interventions (De Bra, 2017). For instance, people's privacy attitude has been often proposed as an adaptation means in the design of privacy wizards.…”

Section: The Role Of Aimentioning

confidence: 99%

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Persuasion Meets AI: Ethical Considerations for the Design of Social Engineering Countermeasures

Ferreyra,

Aïmeur,

Hage

et al. 2020

Preprint

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Privacy in Social Network Sites (SNSs) like Facebook or Instagram is closely related to people's selfdisclosure decisions and their ability to foresee the consequences of sharing personal information with large and diverse audiences. Nonetheless, online privacy decisions are often based on spurious risk judgements that make people liable to reveal sensitive data to untrusted recipients and become victims of social engineering attacks. Artificial Intelligence (AI) in combination with persuasive mechanisms like nudging is a promising approach for promoting preventative privacy behaviour among the users of SNSs. Nevertheless, combining behavioural interventions with high levels of personalization can be a potential threat to people's agency and autonomy even when applied to the design of social engineering countermeasures. This paper elaborates on the ethical challenges that nudging mechanisms can introduce to the development of AI-based countermeasures, particularly to those addressing unsafe self-disclosure practices in SNSs. Overall, it endorses the elaboration of personalized risk awareness solutions as i) an ethical approach to counteract social engineering, and ii) as an effective means for promoting reflective privacy decisions.

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Challenges in User Modeling and Personalization

Cited by 16 publications

References 7 publications

Site Experience Enhancement and Perspective in Cultural Heritage Fruition—A Survey on New Technologies and Methodologies Based on a “Four-Pillars” Approach

Site Experience Enhancement and Perspective in Cultural Heritage Fruition—A Survey on New Technologies and Methodologies Based on a “Four-Pillars” Approach

Responsive and Personalized Web Layouts with Integer Programming

Persuasion Meets AI: Ethical Considerations for the Design of Social Engineering Countermeasures

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