Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization最新文献_第5页

Workshop on Personalized Access to Cultural Heritage: PATCH'20 文化遗产个性化访问研讨会:PATCH'20

Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization Pub Date : 2020-07-07 DOI: 10.1145/3340631.3398670

L. Ardissono, Noemi Mauro, G. Raptis, A. Wecker

引用次数: 0

Challenges, Strategies and Adaptations on Interactive Dashboards 交互式仪表板的挑战、策略和适应

Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization Pub Date : 2020-07-07 DOI: 10.1145/3340631.3398678

M. Alhamadi

引用次数: 6

Investigating Multi-Modal Measures for Cognitive Load Detection in E-Learning 网络学习中认知负荷检测的多模态方法研究

Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization Pub Date : 2020-07-07 DOI: 10.1145/3340631.3394861

Nico Herbig, Tim Düwel, M. Helali, Lea Eckhart, P. Schuck, Subhabrata Choudhury, A. Krüger

{"title":"Investigating Multi-Modal Measures for Cognitive Load Detection in E-Learning","authors":"Nico Herbig, Tim Düwel, M. Helali, Lea Eckhart, P. Schuck, Subhabrata Choudhury, A. Krüger","doi":"10.1145/3340631.3394861","DOIUrl":"https://doi.org/10.1145/3340631.3394861","url":null,"abstract":"In this paper, we analyze a wide range of physiological, behavioral, performance, and subjective measures to estimate cognitive load (CL) during e-learning. To the best of our knowledge, the analyzed sensor measures comprise the most diverse set of features from a variety of modalities that have to date been investigated in the e-learning domain. Our focus lies on predicting the subjectively reported CL and difficulty as well as intrinsic content difficulty based on the explored features. A study with 21 participants, who learned through videos and quizzes in a Moodle environment, shows that classifying intrinsic content difficulty works better for quizzes than for videos, where participants actively solve problems instead of passively consuming videos. Regression analysis for predicting the subjectively reported level of CL and difficulty also works with very low error within content topics. Among the explored feature modalities, eye-based features yield the best results, followed by heart-based and then skin-based measures. Furthermore, combining multiple modalities results in better performance compared to using a single modality. The presented results can guide researchers and developers of cognition-aware e-learning environments by suggesting modalities and features that work particularly well for estimating difficulty and CL.","PeriodicalId":417607,"journal":{"name":"Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122584856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Exploring the Need for Transparency in Educational Recommender Systems 探索教育推荐系统透明度的必要性

Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization Pub Date : 2020-07-07 DOI: 10.1145/3340631.3398676

Jordan Barria-Pineda

引用次数: 4

Workshop on Explainable User Models and Personalized Systems (ExUM 2020) 可解释用户模型和个性化系统研讨会(ExUM 2020)

Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization Pub Date : 2020-07-07 DOI: 10.1145/3340631.3398673

C. Musto, N. Tintarev, O. Inel, Marco Polignano, G. Semeraro, J. Ziegler

{"title":"Workshop on Explainable User Models and Personalized Systems (ExUM 2020)","authors":"C. Musto, N. Tintarev, O. Inel, Marco Polignano, G. Semeraro, J. Ziegler","doi":"10.1145/3340631.3398673","DOIUrl":"https://doi.org/10.1145/3340631.3398673","url":null,"abstract":"Adaptive and personalized systems have become pervasive technologies which are gradually playing an increasingly important role in our daily lives. Indeed, we are now used to interact every day with algorithms that help us in several scenarios, ranging from services that suggest us music to be listened to or movies to be watched, to personal assistants able to proactively support us in complex decision-making tasks. As the importance of such technologies in our everyday lives grows, it is fundamental that the internal mechanisms that guide these algorithms are as clear as possible. Unfortunately, the current research tends to go in the opposite direction, since most of the approaches try to maximize the effectiveness of the personalization strategy (e.g., recommendation accuracy) at the expense of the explainability and the transparency of the model. The main research questions which arise from this scenario is simple and straightforward: How can we deal with such a dichotomy between the need for effective adaptive systems and the right to transparency and interpretability? The workshop aims to provide a forum for discussing such problems, challenges and innovative research approaches in the area, by investigating the role of transparency and explainability on the recent methodologies for building user models or for developing personalized and adaptive systems.","PeriodicalId":417607,"journal":{"name":"Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114641115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Studying Personalized Just-in-time Auditory Breathing Guides and Potential Safety Implications during Simulated Driving 在模拟驾驶过程中研究个性化的即时听觉呼吸指南和潜在的安全影响

Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization Pub Date : 2020-07-07 DOI: 10.1145/3340631.3394854

Sebastian Zepf, Neska El Haouij, Jinmo Lee, Asma Ghandeharioun, Javier Hernández, Rosalind W. Picard

引用次数: 13

Physical and Social Human-robot Interaction 物理和社会人机交互

Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization Pub Date : 2020-07-07 DOI: 10.1145/3340631.3395383

G. Metta

{"title":"Physical and Social Human-robot Interaction","authors":"G. Metta","doi":"10.1145/3340631.3395383","DOIUrl":"https://doi.org/10.1145/3340631.3395383","url":null,"abstract":"This talk covers two main research directions based on the iCub humanoid robot. The iCub is a humanoid robot designed to support research in embodied AI. At 104 cm tall, the iCub has the size of a five-year-old child. It can crawl on all fours, walk, and sit up to manipulate objects. Its hands have been designed to support sophisticate manipulation skills. The iCub is distributed as Open Source following the GPL license and can now count on a worldwide community of enthusiastic developers. There are more than 40 robots available in laboratories across the globe. The iCub sensory system allows seeing, hearing and feeling physical contacts. It is one of the few platforms in the world with a sensitive full-body skin. The iCub is being used at the Italian Institute of Technology as a model platform to develop the technology of future interactive service robots. In particular, I will describe our work in the field of physical and social interaction. For example, through extensive use of machine learning, we developed algorithms to interpret and use external contact information in a variety of tasks as well as contactless cues - vision, sound - to ease interaction between the user and the robot.","PeriodicalId":417607,"journal":{"name":"Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization","volume":"252 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117300357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Group Recommender User Interfaces for Improving Requirements Prioritization 改进需求优先级的组推荐用户界面

Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization Pub Date : 2020-07-07 DOI: 10.1145/3340631.3394851

Ralph Samer, Martin Stettinger, A. Felfernig

{"title":"Group Recommender User Interfaces for Improving Requirements Prioritization","authors":"Ralph Samer, Martin Stettinger, A. Felfernig","doi":"10.1145/3340631.3394851","DOIUrl":"https://doi.org/10.1145/3340631.3394851","url":null,"abstract":"Requirements engineering is one of the most critical phases in the context of software development. Unclear textual specifications of requirements, hidden dependencies between requirements, and suboptimal prioritizations and release plans represent the major reasons for project delays and even cancellation. In this paper, we show how group recommender user interfaces can help to improve the quality of requirements engineering processes. To that end, we developed a novel group recommendation approach that focuses on the aspect of improving requirements prioritization by making preference elicitation processes more flexible as well as by introducing innovative user interfaces that foster information exchange among stakeholders. We conducted a large user study (N=313 participants) to evaluate our approach. The evaluation results indicate that argumentation-based user interfaces in a group setting trigger more rating and communication activity among the group members which significantly improves the quality of the prioritization process. Our main contributions are twofold: (1) more flexibility of the requirements evaluation by supporting the delegation of votes to experts and (2) an increased engagement of the stakeholders responsible for the requirements.","PeriodicalId":417607,"journal":{"name":"Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127611242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Personality Correlates of Music Audio Preferences for Modelling Music Listeners 模拟音乐听众的音乐音频偏好的个性关联

Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization Pub Date : 2020-07-07 DOI: 10.1145/3340631.3394874

Alessandro B. Melchiorre, M. Schedl

引用次数: 17

Recommending Video Games to Adults with Autism Spectrum Disorder for Social-Skill Enhancement 向患有自闭症谱系障碍的成年人推荐电子游戏以提高社交技能

Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization Pub Date : 2020-07-07 DOI: 10.1145/3340631.3394867

Alisha Banskota, Yiu-Kai Ng

{"title":"Recommending Video Games to Adults with Autism Spectrum Disorder for Social-Skill Enhancement","authors":"Alisha Banskota, Yiu-Kai Ng","doi":"10.1145/3340631.3394867","DOIUrl":"https://doi.org/10.1145/3340631.3394867","url":null,"abstract":"Autism spectrum disorder (ASD) is a long-standing mental condition characterized by hindered mental growth and development and is a lifelong disability for the majority of affected individuals. In 2018, 2-3% of children in the USA have been diagnosed with autism. As these children move to adulthood, they have difficulty in developing a well-functioning motor skill. Some of these abnormalities, however, can be gradually improved if they are treated appropriately during their adulthood. Studies have shown that people with ASD enjoy playing video games. Educational games, however, have been primarily developed for children with ASD, which are too primitive for adults with ASD. We have developed a gaming and personalized recommender system that suggests therapeutic games to adults with ASD which can improve their social-interactive skills. The gaming system maintains the entertainment value of the games to ensure that adults are interested in playing them, whereas the recommender system suggests appropriate games for adults with ASD to play. The effectiveness and merit of our gaming and recommender system is backed up by an empirical study.","PeriodicalId":417607,"journal":{"name":"Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124095525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3