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Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization最新文献

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Predicting Emotions From Multimodal Users' Data 从多模式用户数据中预测情绪
Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization Pub Date : 2018-07-03 DOI: 10.1145/3209219.3209264
A. Tato, R. Nkambou, C. Frasson
{"title":"Predicting Emotions From Multimodal Users' Data","authors":"A. Tato, R. Nkambou, C. Frasson","doi":"10.1145/3209219.3209264","DOIUrl":"https://doi.org/10.1145/3209219.3209264","url":null,"abstract":"Prediction of emotions is important for understanding human be-havior and modeling users in learning environments. In this paper,we present a deep multi-modal architecture for emotions predic-tion, which takes advantage of deep learning, user multimodal dataand the hierarchy of human memory. The architecture consists ofthe combination of Long Short-Term memory (LSTMs). One of thenovelty of our approach is that, we enhance the LSTM with anexplicit memory since in brain studies, the memory is often dividedinto two further main types: explicit (or declarative) memory andimplicit (or procedural) memory, the last one being the main pur-pose of LSTMs architectures. The resulting model has been testedon a public multi-modal dataset.","PeriodicalId":110331,"journal":{"name":"Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126391088","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
Session details: Doctoral Consortium II 会议详情:博士联盟II
Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization Pub Date : 2018-07-03 DOI: 10.1145/3258616
S. Berkovsky, V. Dimitrova
{"title":"Session details: Doctoral Consortium II","authors":"S. Berkovsky, V. Dimitrova","doi":"10.1145/3258616","DOIUrl":"https://doi.org/10.1145/3258616","url":null,"abstract":"","PeriodicalId":110331,"journal":{"name":"Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134253057","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
Session details: Personalized Recommender Systems II 会议细节:个性化推荐系统
Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization Pub Date : 2018-07-03 DOI: 10.1145/3258606
D. Jannach
{"title":"Session details: Personalized Recommender Systems II","authors":"D. Jannach","doi":"10.1145/3258606","DOIUrl":"https://doi.org/10.1145/3258606","url":null,"abstract":"","PeriodicalId":110331,"journal":{"name":"Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133227464","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
Recommendation of Activity Sequences during Distributed Events 分布式事件期间活动序列的推荐
Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization Pub Date : 2018-07-03 DOI: 10.1145/3209219.3213592
Diana Nurbakova
{"title":"Recommendation of Activity Sequences during Distributed Events","authors":"Diana Nurbakova","doi":"10.1145/3209219.3213592","DOIUrl":"https://doi.org/10.1145/3209219.3213592","url":null,"abstract":"Leisure activities constitute an important part of our life. Nowadays, the offer of activities to undertake is constantly growing. This can be easily seen not only by the increasing number of social events created and promoted on Facebook, Couchsurfing, etc., but also by the appearance of specialised online services and event-based social networks, such as Meetup, Eventbrite, etc. Moreover, multi-day events (e.g. conventions, festivals, cruise trips, exhibitions), to which we refer to as distributed events, attract thousands of participants. Their attendees are often overwhelmed with the amount of available options. Recommender systems appear as a common solution in such a context. In this project, we formulate the problem of recommendation of activity sequences and aim at providing an integrated support for users to create a personalised itinerary of activities in order to facilitate their decision making process which events to join. Such assistance is expected to bring a positive impact on well-being and satisfaction with life of individuals.","PeriodicalId":110331,"journal":{"name":"Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128487428","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
Using the Explicit User Profile to Predict User Engagement in Active Video Watching 使用显式用户配置文件预测主动视频观看中的用户参与度
Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization Pub Date : 2018-07-03 DOI: 10.1145/3209219.3209262
A. Piotrkowicz, V. Dimitrova, A. Mitrovic, L. Lau
{"title":"Using the Explicit User Profile to Predict User Engagement in Active Video Watching","authors":"A. Piotrkowicz, V. Dimitrova, A. Mitrovic, L. Lau","doi":"10.1145/3209219.3209262","DOIUrl":"https://doi.org/10.1145/3209219.3209262","url":null,"abstract":"In this paper we leverage the explicit user profile (relating to experience, knowledge, and self-regulation) to predict user engagement in active video watching. Data from two user studies for informal learning of presentation skills in a Higher Education context is used to develop and validate the prediction models. Our results show that these user characteristics can reasonably predict the overall engagement (inactive, passive and constructive learners). Our approach can be used to inform adaptive interventions that prevent disengagement and enhance the learning experience.","PeriodicalId":110331,"journal":{"name":"Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122791082","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
Group Recommender Systems 小组推荐系统
Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization Pub Date : 2018-07-03 DOI: 10.1145/3209219.3209272
Amra Delic, J. Masthoff
{"title":"Group Recommender Systems","authors":"Amra Delic, J. Masthoff","doi":"10.1145/3209219.3209272","DOIUrl":"https://doi.org/10.1145/3209219.3209272","url":null,"abstract":"Recommender systems for groups are becoming increasingly popular since many information needs originate from group and social activities, such as listening to music, watching movies, traveling, etc. There has been substantial progress on systems which recommend items to groups of users. However, many challenges remain. The goal of this tutorial is to introduce group recommendation and group modeling to the UMAP audience. First we will introduce the problem of making recommendations to groups and adapting to groups, and give an overview of the state-of-the art approaches to group recommendation. Next, we will also analyze more challenging topics, such as including different behavioral aspects into group modeling, and evaluation of group recommendations. Throughout, hands-on activities will be included. The tutorial will conclude with a summary of challenges and open issues.","PeriodicalId":110331,"journal":{"name":"Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121916689","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: 11
Modeling and Predicting News Consumption on Twitter Twitter上新闻消费的建模和预测
Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization Pub Date : 2018-07-03 DOI: 10.1145/3209219.3209245
Claudia Orellana-Rodriguez, Mark T. Keane
{"title":"Modeling and Predicting News Consumption on Twitter","authors":"Claudia Orellana-Rodriguez, Mark T. Keane","doi":"10.1145/3209219.3209245","DOIUrl":"https://doi.org/10.1145/3209219.3209245","url":null,"abstract":"While much is known about how people tweet and interact on Twitter, surprisingly little is known about how the news items tweeted by journalists -- news tweets -- act as a distribution channel for the news that is spread by social media reading and sharing. This paper aims to fill this gap by analyzing the dynamics of news on Twitter, by revealing what drives users to consume news, and by developing a news consumption prediction model. We present the Twitter News Model (TNM), a computational data-driven approach to elucidate the dynamics of news consumption on Twitter. We apply the TNM to a dataset of interactions between users and journalists/newspapers to reveal what drives users' consumption of news on Twitter, and predictively relate users' news beliefs, motivations, and attitudes to their consumption of news. Our findings reveal that news motivations, followed by news attitudes and news beliefs, impact users' behavior of news consumption on Twitter.","PeriodicalId":110331,"journal":{"name":"Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114773061","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: 1
Modeling Student Persistence in a Learning-By-Teaching Environment 在“教中学”的环境中塑造学生的毅力
Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization Pub Date : 2018-07-03 DOI: 10.1145/3209219.3213596
Cristina E. Dumdumaya
{"title":"Modeling Student Persistence in a Learning-By-Teaching Environment","authors":"Cristina E. Dumdumaya","doi":"10.1145/3209219.3213596","DOIUrl":"https://doi.org/10.1145/3209219.3213596","url":null,"abstract":"Persistence is a non-cognitive attribute referring to one's disposition to attain a specific goal despite challenges and difficulties. Persistence is of particular interest and importance because of its relationship to students' academic achievement and other individual and societal outcomes. Despite claims that persistence is a highly valuable skill, quantitative studies on persistence in technology enhanced learning environments are limited. This study will attempt to build a quantitative model of persistence utilizing machine learning and related methodologies using features distilled from students' domain knowledge assessments and system logs from their use of an Intelligent Tutoring System. The results of the study could potentially provide additional insights on learners' persistence, the factors that influence student persistence, and what interventions to employ to induce learners to persist in tasks.","PeriodicalId":110331,"journal":{"name":"Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115778800","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
Exploring Adaptive Strategies for Providing Learning Activities 探索提供学习活动的适应性策略
Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization Pub Date : 2018-07-03 DOI: 10.1145/3209219.3209221
Xingliang Chen, A. Mitrovic, Moffat Mathews
{"title":"Exploring Adaptive Strategies for Providing Learning Activities","authors":"Xingliang Chen, A. Mitrovic, Moffat Mathews","doi":"10.1145/3209219.3209221","DOIUrl":"https://doi.org/10.1145/3209219.3209221","url":null,"abstract":"Research shows that Worked Examples (WE) and Erroneous Examples (ErrEx) provide learning benefits, particularly when presented alternatively with problems to solve. We previously proposed an adaptive strategy for selecting WE, ErrEx, and Problem Solving (PS) adaptively based on the student's problem-solving score and found that the adaptive strategy was beneficial for students in comparison to learning from a fixed sequence of alternating WE/PS pairs and ErrEx/PS pairs [1]. Students who received learning activities adaptively achieved the same learning outcomes as their peers in a fixed condition, but with fewer learning activities [2]. In this paper, we investigate a different adaptive strategy, which provides WEs and ErrExs to novices, and ErrEx and PS to advanced students. We found that the original adaptive strategy [2] is more effective than the new adaptive strategy. Furthermore, both novices and advanced students who learned with the original adaptive strategy demonstrated better performance on the post-test.","PeriodicalId":110331,"journal":{"name":"Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127805593","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: 1
Session details: Personalized Recommender Systems III 会议详情:个性化推荐系统
Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization Pub Date : 2018-07-03 DOI: 10.1145/3258610
C. Musto
{"title":"Session details: Personalized Recommender Systems III","authors":"C. Musto","doi":"10.1145/3258610","DOIUrl":"https://doi.org/10.1145/3258610","url":null,"abstract":"","PeriodicalId":110331,"journal":{"name":"Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131953942","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
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