User Modeling and User-Adapted Interaction最新文献_第6页

IF 3.6 3区计算机科学

User Modeling and User-Adapted Interaction Pub Date : 2023-02-01 DOI: 10.1007/s11257-009-9070-8

F. Bohnert, C. Busso, C. Conati, Ella Haig, M. Desmarais, V. Dimitrova, H. Dybkjær, D. Heckmann, V. Hollink, V. L. Jaquero, Patrick Jermann, S. McNee, C. Papatheodorou, Rupa Parameswaran, Dimitris Pierrakos, P. Pu, C. Rich, D. Rosaci, Anthony Savidis, S. Schiaffino, N. Sebe, Mayumi Ueda, D. Vogiatzis, Stefan Weibelzahl, Yi Zhang

引用次数: 0

Acknowledgment to reviewers 评审员致谢

IF 3.6 3区计算机科学

User Modeling and User-Adapted Interaction Pub Date : 2023-02-01 DOI: 10.1007/s11257-017-9197-y

T. Hammond, Simon Harper, Christoffer Holmgård, R. Jäschke, Markus Kächele, Helena Lindgren, G. Miklau, Yashar Moshfeghi, Radek Pelánek, Sergey Sosnovsky, M. Specht, Stephan Weibelzahl, M. Yudelson

引用次数: 0

Use of topical and temporal profiles and their hybridisation for content-based recommendation 在基于内容的推荐中使用主题和时间概况及其混合

IF 3.6 3区计算机科学

User Modeling and User-Adapted Interaction Pub Date : 2023-01-23 DOI: 10.1007/s11257-022-09354-7

Luis M. de Campos, J. M. Fernández-Luna, J. Huete

引用次数: 0

Enhancing user awareness on inferences obtained from fitness trackers data. 提高用户对从健身追踪器数据中获得的推论的认识。

IF 3.6 3区计算机科学

User Modeling and User-Adapted Interaction Pub Date : 2023-01-17 DOI: 10.1007/s11257-022-09353-8

Alexia Dini Kounoudes, Georgia M Kapitsaki, Ioannis Katakis

{"title":"Enhancing user awareness on inferences obtained from fitness trackers data.","authors":"Alexia Dini Kounoudes, Georgia M Kapitsaki, Ioannis Katakis","doi":"10.1007/s11257-022-09353-8","DOIUrl":"10.1007/s11257-022-09353-8","url":null,"abstract":"In the IoT era, sensitive and non-sensitive data are recorded and transmitted to multiple service providers and IoT platforms, aiming to improve the quality of our lives through the provision of high-quality services. However, in some cases these data may become available to interested third parties, who can analyse them with the intention to derive further knowledge and generate new insights about the users, that they can ultimately use for their own benefit. This predicament raises a crucial issue regarding the privacy of the users and their awareness on how their personal data are shared and potentially used. The immense increase in fitness trackers use has further increased the amount of user data generated, processed and possibly shared or sold to third parties, enabling the extraction of further insights about the users. In this work, we investigate if the analysis and exploitation of the data collected by fitness trackers can lead to the extraction of inferences about the owners routines, health status or other sensitive information. Based on the results, we utilise the PrivacyEnhAction privacy tool, a web application we implemented in a previous work through which the users can analyse data collected from their IoT devices, to educate the users about the possible risks and to enable them to set their user privacy preferences on their fitness trackers accordingly, contributing to the personalisation of the provided services, in respect of their personal data.","PeriodicalId":49388,"journal":{"name":"User Modeling and User-Adapted Interaction","volume":" ","pages":"1-48"},"PeriodicalIF":3.6,"publicationDate":"2023-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9843666/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9131438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How do item features and user characteristics affect users’ perceptions of recommendation serendipity? A cross-domain analysis 项目特征和用户特征如何影响用户对推荐偶然性的感知？跨领域分析

IF 3.6 3区计算机科学

User Modeling and User-Adapted Interaction Pub Date : 2023-01-17 DOI: 10.1007/s11257-022-09356-5

Ningxia Wang, L. Chen

引用次数: 1

What we see is what we do: a practical Peripheral Vision-Based HMM framework for gaze-enhanced recognition of actions in a medical procedural task 我们所看到的就是我们所做的：一个实用的基于外围视觉的HMM框架，用于在医疗程序任务中增强对动作的凝视识别

IF 3.6 3区计算机科学

User Modeling and User-Adapted Interaction Pub Date : 2023-01-04 DOI: 10.1007/s11257-022-09352-9

F. Wang, Thomas Kreiner, Alexander Lutz, Q. Lohmeyer, M. Meboldt

引用次数: 3

A dichotomic approach to adaptive interaction for socially assistive robots. 社会辅助机器人自适应交互的二分类方法。

IF 3.6 3区计算机科学

User Modeling and User-Adapted Interaction Pub Date : 2023-01-01 DOI: 10.1007/s11257-022-09347-6

Riccardo De Benedictis, Alessandro Umbrico, Francesca Fracasso, Gabriella Cortellessa, Andrea Orlandini, Amedeo Cesta

{"title":"A dichotomic approach to adaptive interaction for socially assistive robots.","authors":"Riccardo De Benedictis, Alessandro Umbrico, Francesca Fracasso, Gabriella Cortellessa, Andrea Orlandini, Amedeo Cesta","doi":"10.1007/s11257-022-09347-6","DOIUrl":"https://doi.org/10.1007/s11257-022-09347-6","url":null,"abstract":"Socially assistive robotics (SAR) aims at designing robots capable of guaranteeing social interaction to human users in a variety of assistance scenarios that range, e.g., from giving reminders for medications to monitoring of Activity of Daily Living, from giving advices to promote an healthy lifestyle to psychological monitoring. Among possible users, frail older adults deserve a special focus as they present a rich variability in terms of both alternative possible assistive scenarios (e.g., hospital or domestic environments) and caring needs that could change over time according to their health conditions. In this perspective, robot behaviors should be customized according to properly designed user models. One of the long-term research goals for SAR is the realization of robots capable of, on the one hand, personalizing assistance according to different health-related conditions/states of users and, on the other, adapting behaviors according to heterogeneous contexts as well as changing/evolving needs of users. This work proposes a solution based on a user model grounded on the international classification of functioning, disability and health (ICF) and a novel control architecture inspired by the dual-process theory. The proposed approach is general and can be deployed in many different scenarios. In this paper, we focus on a social robot in charge of the synthesis of personalized training sessions for the cognitive stimulation of older adults, customizing the adaptive verbal behavior according to the characteristics of the users and to their dynamic reactions when interacting. Evaluations with a restricted number of users show good usability of the system, a general positive attitude of users and the ability of the system to capture users personality so as to adapt the content accordingly during the verbal interaction.","PeriodicalId":49388,"journal":{"name":"User Modeling and User-Adapted Interaction","volume":"33 2","pages":"293-331"},"PeriodicalIF":3.6,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9670074/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9380760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

An adaptive decision-making system supported on user preference predictions for human-robot interactive communication. 基于用户偏好预测的自适应决策系统，用于人机互动交流。

IF 3 3区计算机科学

User Modeling and User-Adapted Interaction Pub Date : 2023-01-01 Epub Date: 2022-04-09 DOI: 10.1007/s11257-022-09321-2

Marcos Maroto-Gómez, Álvaro Castro-González, José Carlos Castillo, María Malfaz, Miguel Ángel Salichs

{"title":"An adaptive decision-making system supported on user preference predictions for human-robot interactive communication.","authors":"Marcos Maroto-Gómez, Álvaro Castro-González, José Carlos Castillo, María Malfaz, Miguel Ángel Salichs","doi":"10.1007/s11257-022-09321-2","DOIUrl":"10.1007/s11257-022-09321-2","url":null,"abstract":"Adapting to dynamic environments is essential for artificial agents, especially those aiming to communicate with people interactively. In this context, a social robot that adapts its behaviour to different users and proactively suggests their favourite activities may produce a more successful interaction. In this work, we describe how the autonomous decision-making system embedded in our social robot Mini can produce a personalised interactive communication experience by considering the preferences of the user the robot interacts with. We compared the performance of Top Label as Class and Ranking by Pairwise Comparison, two promising algorithms in the area, to find the one that best predicts the user preferences. Although both algorithms provide robust results in preference prediction, we decided to integrate Ranking by Pairwise Comparison since it provides better estimations. The method proposed in this contribution allows the autonomous decision-making system of the robot to work on different modes, balancing activity exploration with the selection of the favourite entertaining activities. The operation of the preference learning system is shown in three real case studies where the decision-making system works differently depending on the user the robot is facing. Then, we conducted a human-robot interaction experiment to investigate whether the robot users perceive the personalised selection of activities more appropriate than selecting the activities at random. The results show how the study participants found the personalised activity selection more appropriate, improving their likeability towards the robot and how intelligent they perceive the system. query Please check the edit made in the article title.","PeriodicalId":49388,"journal":{"name":"User Modeling and User-Adapted Interaction","volume":"33 2","pages":"359-403"},"PeriodicalIF":3.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8994572/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9372877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing a student productivity model for adaptive problem-solving assistance. 增强学生生产力模型以适应问题解决的协助。

IF 3.6 3区计算机科学

User Modeling and User-Adapted Interaction Pub Date : 2023-01-01 DOI: 10.1007/s11257-022-09338-7

Mehak Maniktala, Min Chi, Tiffany Barnes

{"title":"Enhancing a student productivity model for adaptive problem-solving assistance.","authors":"Mehak Maniktala, Min Chi, Tiffany Barnes","doi":"10.1007/s11257-022-09338-7","DOIUrl":"https://doi.org/10.1007/s11257-022-09338-7","url":null,"abstract":"Research on intelligent tutoring systems has been exploring data-driven methods to deliver effective adaptive assistance. While much work has been done to provide adaptive assistance when students seek help, they may not seek help optimally. This had led to the growing interest in proactive adaptive assistance, where the tutor provides unsolicited assistance upon predictions of struggle or unproductivity. Determining when and whether to provide personalized support is a well-known challenge called the assistance dilemma. Addressing this dilemma is particularly challenging in open-ended domains, where there can be several ways to solve problems. Researchers have explored methods to determine when to proactively help students, but few of these methods have taken prior hint usage into account. In this paper, we present a novel data-driven approach to incorporate students' hint usage in predicting their need for help. We explore its impact in an intelligent tutor that deals with the open-ended and well-structured domain of logic proofs. We present a controlled study to investigate the impact of an adaptive hint policy based on predictions of HelpNeed that incorporate students' hint usage. We show empirical evidence to support that such a policy can save students a significant amount of time in training and lead to improved posttest results, when compared to a control without proactive interventions. We also show that incorporating students' hint usage significantly improves the adaptive hint policy's efficacy in predicting students' HelpNeed, thereby reducing training unproductivity, reducing possible help avoidance, and increasing possible help appropriateness (a higher chance of receiving help when it was likely to be needed). We conclude with suggestions on the domains that can benefit from this approach as well as the requirements for adoption.","PeriodicalId":49388,"journal":{"name":"User Modeling and User-Adapted Interaction","volume":"33 1","pages":"159-188"},"PeriodicalIF":3.6,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9362072/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10772089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Personalised socially assistive robot for cardiac rehabilitation: Critical reflections on long-term interactions in the real world. 心脏康复的个性化社会辅助机器人:对现实世界中长期互动的批判性反思。

IF 3.6 3区计算机科学

User Modeling and User-Adapted Interaction Pub Date : 2023-01-01 DOI: 10.1007/s11257-022-09323-0

Bahar Irfan, Nathalia Céspedes, Jonathan Casas, Emmanuel Senft, Luisa F Gutiérrez, Mónica Rincon-Roncancio, Carlos A Cifuentes, Tony Belpaeme, Marcela Múnera

{"title":"Personalised socially assistive robot for cardiac rehabilitation: Critical reflections on long-term interactions in the real world.","authors":"Bahar Irfan, Nathalia Céspedes, Jonathan Casas, Emmanuel Senft, Luisa F Gutiérrez, Mónica Rincon-Roncancio, Carlos A Cifuentes, Tony Belpaeme, Marcela Múnera","doi":"10.1007/s11257-022-09323-0","DOIUrl":"https://doi.org/10.1007/s11257-022-09323-0","url":null,"abstract":"Lack of motivation and low adherence rates are critical concerns of long-term rehabilitation programmes, such as cardiac rehabilitation. Socially assistive robots are known to be effective in improving motivation in therapy. However, over longer durations, generic and repetitive behaviours by the robot often result in a decrease in motivation and engagement, which can be overcome by personalising the interaction, such as recognising users, addressing them with their name, and providing feedback on their progress and adherence. We carried out a real-world clinical study, lasting 2.5 years with 43 patients to evaluate the effects of using a robot and personalisation in cardiac rehabilitation. Due to dropouts and other factors, 26 patients completed the programme. The results derived from these patients suggest that robots facilitate motivation and adherence, enable prompt detection of critical conditions by clinicians, and improve the cardiovascular functioning of the patients. Personalisation is further beneficial when providing high-intensity training, eliciting and maintaining engagement (as measured through gaze and social interactions) and motivation throughout the programme. However, relying on full autonomy for personalisation in a real-world environment resulted in sensor and user recognition failures, which caused negative user perceptions and lowered the perceived utility of the robot. Nonetheless, personalisation was positively perceived, suggesting that potential drawbacks need to be weighed against various benefits of the personalised interaction.","PeriodicalId":49388,"journal":{"name":"User Modeling and User-Adapted Interaction","volume":"33 2","pages":"497-544"},"PeriodicalIF":3.6,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294801/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9437126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5