User Portrait Based on Artificial Intelligence

Yuan, Tongqing

doi:10.1007/978-981-99-1428-9_44

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…Understanding the context of use of a digital solution is particularly important, as in essence it entails understanding who the targeted user is and what is their personal context, how, when and where they may use the digital solution and what might be done to improve their experience of interacting with said solution (Korhonen et al, 2010). Often, this information gets captured and analysed through user personas or user portraits, on the basis of available datasets (Yuan, 2023), and it is then used to inform low fidelity prototyping of interfaces and products (Christoforakos & Diefenbach, 2019). Therefore, studies that focus on this aspect of the design process (summarised in Table 2) propose AI tools and methods for automating those parts of the design process that are geared towards proving a better understanding of the context of use of the digital solution.…”

Section: Ai Uses For Understanding the Context Of Usementioning

confidence: 99%

Artificial intelligence (AI) for user experience (UX) design: a systematic literature review and future research agenda

Stige,

Zamani,

Mikalef

et al. 2023

ITP

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PurposeThe aim of this article is to map the use of AI in the user experience (UX) design process. Disrupting the UX process by introducing novel digital tools such as artificial intelligence (AI) has the potential to improve efficiency and accuracy, while creating more innovative and creative solutions. Thus, understanding how AI can be leveraged for UX has important research and practical implications.Design/methodology/approachThis article builds on a systematic literature review approach and aims to understand how AI is used in UX design today, as well as uncover some prominent themes for future research. Through a process of selection and filtering, 46 research articles are analysed, with findings synthesized based on a user-centred design and development process.FindingsThe authors’ analysis shows how AI is leveraged in the UX design process at different key areas. Namely, these include understanding the context of use, uncovering user requirements, aiding solution design, and evaluating design, and for assisting development of solutions. The authors also highlight the ways in which AI is changing the UX design process through illustrative examples.Originality/valueWhile there is increased interest in the use of AI in organizations, there is still limited work on how AI can be introduced into processes that depend heavily on human creativity and input. Thus, the authors show the ways in which AI can enhance such activities and assume tasks that have been typically performed by humans.

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Section: Ai Uses For Understanding the Context Of Usementioning

confidence: 99%

Artificial intelligence (AI) for user experience (UX) design: a systematic literature review and future research agenda

Stige,

Zamani,

Mikalef

et al. 2023

ITP

View full text Add to dashboard Cite

show abstract

“…The concept of user portraits was initially introduced by Alan Cooper [19], considered the pioneer of interaction design. User portraits are created by leveraging extensive user behavior data to generate a comprehensive and detailed description of their characteristics, transforming the data into a valuable tool for problem-solving purposes [20]. The wide application of user portraits has also made positive contributions in intrusion detection [21], personalized recommendation [22], medical [18], public opinion analysis [23], and other fields.…”

Section: Introductionmentioning

confidence: 99%

Consumer Default Risk Portrait: An Intelligent Management Framework of Online Consumer Credit Default Risk

Zhu,

Shia,

et al. 2024

Mathematics

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Online consumer credit services play a vital role in the contemporary consumer market. To foster their sustainable development, it is essential to establish and strengthen the relevant risk management mechanism. This study proposes an intelligent management framework called the consumer default risk portrait (CDRP) to mitigate the default risks associated with online consumer loans. The CDRP framework combines traditional credit information and Internet platform data to depict the portrait of consumer default risks. It consists of four modules: addressing data imbalances, establishing relationships between user characteristics and the default risk, analyzing the influence of different variables on default, and ultimately presenting personalized consumer profiles. Empirical findings reveal that “Repayment Periods”, “Loan Amount”, and “Debt to Income Type” emerge as the three variables with the most significant impact on default. “Re-payment Periods” and “Debt to Income Type” demonstrate a positive correlation with default probability, while a lower “Loan Amount” corresponds to a higher likelihood of default. Additionally, our verification highlights that the significance of variables varies across different samples, thereby presenting a personalized portrait from a single sample. In conclusion, the proposed framework provides valuable suggestions and insights for financial institutions and Internet platform managers to improve the market environment of online consumer credit services.

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User Portrait Based on Artificial Intelligence

Cited by 2 publications

References 8 publications

Artificial intelligence (AI) for user experience (UX) design: a systematic literature review and future research agenda

Artificial intelligence (AI) for user experience (UX) design: a systematic literature review and future research agenda

Consumer Default Risk Portrait: An Intelligent Management Framework of Online Consumer Credit Default Risk

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