Recent research in fairness in machine learning has identified situations in which biases in input data can cause harmful or unwanted effects. Researchers in the areas of personalization and recommendation have begun to study similar types of bias. What these lines of research share is a fixed representation of the protected groups relative to which bias must be monitored. However, in some real-world application contexts, such groups cannot be defined apriori, but must be derived from the data itself. Furthermore, as we show, it may be insufficient in such cases to examine global system properties to identify protected groups. Thus, we demonstrate that fairness may be local, and the identification of protected groups only possible through consideration of local conditions.
{"title":"Localized Fairness in Recommender Systems","authors":"Nasim Sonboli, R. Burke","doi":"10.1145/3314183.3323845","DOIUrl":"https://doi.org/10.1145/3314183.3323845","url":null,"abstract":"Recent research in fairness in machine learning has identified situations in which biases in input data can cause harmful or unwanted effects. Researchers in the areas of personalization and recommendation have begun to study similar types of bias. What these lines of research share is a fixed representation of the protected groups relative to which bias must be monitored. However, in some real-world application contexts, such groups cannot be defined apriori, but must be derived from the data itself. Furthermore, as we show, it may be insufficient in such cases to examine global system properties to identify protected groups. Thus, we demonstrate that fairness may be local, and the identification of protected groups only possible through consideration of local conditions.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124466112","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}
Human space exploration creates unique challenges and opportunities for many scientific disciplines. From the human-agent interaction perspective, these require significant advances in the way that agents model, adapt and personalize their behavior to individual astronauts and groups of astronauts. In this paper, we highlight the key challenges and opportunities that human space exploration provides to the agent and UMAP communities and present two avenues for future research. We further propose a viable way to explore these challenges and opportunities through the world-wide analogue space programs which solicit research proposals from all scientific disciplines.
{"title":"Human-Agent Interaction for Human Space Exploration","authors":"Ariel Rosenfeld","doi":"10.1145/3314183.3323452","DOIUrl":"https://doi.org/10.1145/3314183.3323452","url":null,"abstract":"Human space exploration creates unique challenges and opportunities for many scientific disciplines. From the human-agent interaction perspective, these require significant advances in the way that agents model, adapt and personalize their behavior to individual astronauts and groups of astronauts. In this paper, we highlight the key challenges and opportunities that human space exploration provides to the agent and UMAP communities and present two avenues for future research. We further propose a viable way to explore these challenges and opportunities through the world-wide analogue space programs which solicit research proposals from all scientific disciplines.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131841986","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}
Recommender systems (RS) have been introduced to educations as an effective technology-enhanced learning technique. Traditional RS produce recommendations by considering the preferences of the end users only. Multi-stakeholder recommender systems (MSRS) claim that it is necessary to consider the utility of the items from the perspective of other stakeholders in order to balance the needs of multiple stakeholders. Take book recommendations for example, the utility of items from the view of parents, instructors and even publishers may be also important in addition to the student preferences. In this paper, we propose and exploit utility-based MSRS for personalized learning. Particularly, we attempt to address the challenge of over-/under-expectations in the utility-based MSRS. Our experimental results based on an educational data demonstrate the effectiveness of our proposed models and solutions.
{"title":"Personalized Educational Learning with Multi-Stakeholder Optimizations","authors":"Yong Zheng, Nastaran Ghane, Milad Sabouri","doi":"10.1145/3314183.3323843","DOIUrl":"https://doi.org/10.1145/3314183.3323843","url":null,"abstract":"Recommender systems (RS) have been introduced to educations as an effective technology-enhanced learning technique. Traditional RS produce recommendations by considering the preferences of the end users only. Multi-stakeholder recommender systems (MSRS) claim that it is necessary to consider the utility of the items from the perspective of other stakeholders in order to balance the needs of multiple stakeholders. Take book recommendations for example, the utility of items from the view of parents, instructors and even publishers may be also important in addition to the student preferences. In this paper, we propose and exploit utility-based MSRS for personalized learning. Particularly, we attempt to address the challenge of over-/under-expectations in the utility-based MSRS. Our experimental results based on an educational data demonstrate the effectiveness of our proposed models and solutions.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129303665","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}
This tutorial will introduce User Modeling (UM) researchers to the techniques of empirical evaluation of user modeling systems. No background in statistics is required. The target audience is UM researchers, especially students, who have a background in computer science or some other field that does not normally include designing and running human-subject experiments. Topics include designing experiments (choosing independent/dependent variables, covariant and nuisance variables, between vs. within subjects designs, factorial designs, estimating sensitivity, layered evaluation), running experiments (recruiting participants, controlling the environment, recording data), data analysis (statistical tests, ANOVA, checking assumptions of statistical methods, multiple testing correction, explained variance), and common surveys/tests for gathering covariate data.
{"title":"Empirical Evaluation of User Modeling Systems","authors":"David N. Chin","doi":"10.1145/3314183.3340265","DOIUrl":"https://doi.org/10.1145/3314183.3340265","url":null,"abstract":"This tutorial will introduce User Modeling (UM) researchers to the techniques of empirical evaluation of user modeling systems. No background in statistics is required. The target audience is UM researchers, especially students, who have a background in computer science or some other field that does not normally include designing and running human-subject experiments. Topics include designing experiments (choosing independent/dependent variables, covariant and nuisance variables, between vs. within subjects designs, factorial designs, estimating sensitivity, layered evaluation), running experiments (recruiting participants, controlling the environment, recording data), data analysis (statistical tests, ANOVA, checking assumptions of statistical methods, multiple testing correction, explained variance), and common surveys/tests for gathering covariate data.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123897419","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}
Before the advent of internet technologies, African merchants have always had indigenous none techno-driven strategies with which they use to engage, maintain and satisfy customers within their communities. However, due to the cross-border marketing/economic opportunities that the internet provides, many African merchants are setting up eCommerce sites for their businesses. Research shows that successful eCommerce sites are operationalized with various persuasive techniques to promote customer engagement and improve user experiences. This is also true for African based eCommerce sites. Various researchers have evaluated and compared persuasive techniques operationalized on indigenous African eCommerce sites. However, none of those studies sought to understand the implications of the age-long traditional marketing strategies in the design of African based eCommerce platforms. Therefore, this paper analyzes the persuasive techniques employed in conventional African marketplaces to uncover the design requirements that could be operationalized on the eCommerce version. To achieve this objective, we conducted a mixed method study on 151 participants. We conducted qualitative studies (comprising interviews, observations, and conceptual investigations) on 50 African merchants to uncover the techniques they use to attract, satisfy and retain their customers in the conventional market. Secondly, we conducted quantitative studies on 101 customers to uncover the effects of those techniques on them. Among other things, the results from the studies revealed various techniques, which traditional African merchants use to attract and retain customers. The results also revealed the effects of those techniques on customers' purchasing behaviors. We offer design guidelines to operationalize and tailor those techniques to attract, recruit, satisfy, retain and promote repeated purchases on eCommerce that target customers from developing countries.
{"title":"Socially Responsive eCommerce Platforms: Design Implications for Online Marketplaces in Developing African Nation","authors":"M. Nkwo, Rita Orji","doi":"10.1145/3314183.3324984","DOIUrl":"https://doi.org/10.1145/3314183.3324984","url":null,"abstract":"Before the advent of internet technologies, African merchants have always had indigenous none techno-driven strategies with which they use to engage, maintain and satisfy customers within their communities. However, due to the cross-border marketing/economic opportunities that the internet provides, many African merchants are setting up eCommerce sites for their businesses. Research shows that successful eCommerce sites are operationalized with various persuasive techniques to promote customer engagement and improve user experiences. This is also true for African based eCommerce sites. Various researchers have evaluated and compared persuasive techniques operationalized on indigenous African eCommerce sites. However, none of those studies sought to understand the implications of the age-long traditional marketing strategies in the design of African based eCommerce platforms. Therefore, this paper analyzes the persuasive techniques employed in conventional African marketplaces to uncover the design requirements that could be operationalized on the eCommerce version. To achieve this objective, we conducted a mixed method study on 151 participants. We conducted qualitative studies (comprising interviews, observations, and conceptual investigations) on 50 African merchants to uncover the techniques they use to attract, satisfy and retain their customers in the conventional market. Secondly, we conducted quantitative studies on 101 customers to uncover the effects of those techniques on them. Among other things, the results from the studies revealed various techniques, which traditional African merchants use to attract and retain customers. The results also revealed the effects of those techniques on customers' purchasing behaviors. We offer design guidelines to operationalize and tailor those techniques to attract, recruit, satisfy, retain and promote repeated purchases on eCommerce that target customers from developing countries.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125525124","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}
Ioana Ghergulescu, Arghir-Nicolae Moldovan, C. Muntean, Gabriel-Miro Muntean
Virtual labs enable inquiry-based learning where students can implement their own experiments using virtual objects and apparatus. Although the benefits of adaptive and personalised learning are well recognised, these were not thoroughly investigated in virtual labs. This paper presents the architecture of an interactive science virtual lab that personalises the learning journey based on the student's self-directed learning (SDL) and self-efficacy (SE) levels. The results of a pilot in two secondary schools showed that both students with low and high SDL and SE level improved their knowledge, but students with low SDL and SE had a higher number of incorrect attempts before completing the experiment.
{"title":"Interactive Personalised STEM Virtual Lab Based on Self-Directed Learning and Self-Efficacy","authors":"Ioana Ghergulescu, Arghir-Nicolae Moldovan, C. Muntean, Gabriel-Miro Muntean","doi":"10.1145/3314183.3323678","DOIUrl":"https://doi.org/10.1145/3314183.3323678","url":null,"abstract":"Virtual labs enable inquiry-based learning where students can implement their own experiments using virtual objects and apparatus. Although the benefits of adaptive and personalised learning are well recognised, these were not thoroughly investigated in virtual labs. This paper presents the architecture of an interactive science virtual lab that personalises the learning journey based on the student's self-directed learning (SDL) and self-efficacy (SE) levels. The results of a pilot in two secondary schools showed that both students with low and high SDL and SE level improved their knowledge, but students with low SDL and SE had a higher number of incorrect attempts before completing the experiment.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116885291","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}
Research in the areas of User Modelling, Adaptation and Personalization faces a number of significant scientific challenges. One of the most significant of these challenges is the issue of comparative evaluation. It has always been difficult to rigorously compare different approaches to personalization, as the function of the resulting systems is, by their nature, heavily influenced by the behavior of the users involved in trialing the systems. Developing comparative evaluations in this space would be a huge advancement as it would enable shared comparison across research. This workshop aims to develop initial shared task(s) that will be published ahead of UMAP 2020, providing opportunity for participants to test and tune their systems and complete the task in order for comparative results and associated publications to be prepared for and presented at UMAP 2020.
{"title":"EvalUMAP 2019 Chairs' Welcome & Organization","authors":"Bilal Yousuf, Liadh Kelly","doi":"10.1145/3314183.3323714","DOIUrl":"https://doi.org/10.1145/3314183.3323714","url":null,"abstract":"Research in the areas of User Modelling, Adaptation and Personalization faces a number of significant scientific challenges. One of the most significant of these challenges is the issue of comparative evaluation. It has always been difficult to rigorously compare different approaches to personalization, as the function of the resulting systems is, by their nature, heavily influenced by the behavior of the users involved in trialing the systems. Developing comparative evaluations in this space would be a huge advancement as it would enable shared comparison across research. This workshop aims to develop initial shared task(s) that will be published ahead of UMAP 2020, providing opportunity for participants to test and tune their systems and complete the task in order for comparative results and associated publications to be prepared for and presented at UMAP 2020.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115477662","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}
Soojeong Yoo, Jisu Jung, Cécile Paris, B. Kummerfeld, J. Kay
A user model that is built from the data of multiple physical activity sensors has the potential to enable people to answer important questions about their long-term physical activity. Our work provides a way to do this for the case of exercise from virtual reality gaming and from incidental daily walking. Our approach is based two parts: 1) a carefully designed a user model ontology, Exer-model; 2) an interface for navigating the model and comparing components of the model. We evaluated the Exer-model ontology and the scrutiny interface in a study with 16 users: 8 viewing their own user models, from 8 weeks of their sensor data, and the other 8 scrutinising the model of a hypothetical user. Our core contributions are the insights about designing the ontologies and interfaces for scrutable user models from multiple physical activity sensors.
{"title":"Exer-model: A User Model for Scrutinising Long-term Models of Physical Activity from Multiple Sensors","authors":"Soojeong Yoo, Jisu Jung, Cécile Paris, B. Kummerfeld, J. Kay","doi":"10.1145/3314183.3324986","DOIUrl":"https://doi.org/10.1145/3314183.3324986","url":null,"abstract":"A user model that is built from the data of multiple physical activity sensors has the potential to enable people to answer important questions about their long-term physical activity. Our work provides a way to do this for the case of exercise from virtual reality gaming and from incidental daily walking. Our approach is based two parts: 1) a carefully designed a user model ontology, Exer-model; 2) an interface for navigating the model and comparing components of the model. We evaluated the Exer-model ontology and the scrutiny interface in a study with 16 users: 8 viewing their own user models, from 8 weeks of their sensor data, and the other 8 scrutinising the model of a hypothetical user. Our core contributions are the insights about designing the ontologies and interfaces for scrutable user models from multiple physical activity sensors.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114926144","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}
The use of behavior change systems and persuasive technologies to promote desirable behavior is increasingly gaining attention. Most existing Persuasive Technologies (PTs) are targeted at promoting Physical Activity (PA) using three common socially-oriented persuasive strategies: competition, social comparison, and cooperation. This paper provides an empirical review of 19 years (54 papers) of literature on persuasive technology for physical activity promotion. The review aims to (1.) evaluate the effectiveness of PTs employing social influence strategies to promote PA; (2.) summarize and highlight trends in the outcomes and employed technological platforms; (3.) reveal some weaknesses of existing PTs for promoting PA; and finally, (4.) offer suggestions for improvements, and opportunities for future research in this area.
{"title":"How Effective Are Social Influence Strategies in Persuasive Apps for Promoting Physical Activity?: A Systematic Review","authors":"Najla Almutari, Rita Orji","doi":"10.1145/3314183.3323855","DOIUrl":"https://doi.org/10.1145/3314183.3323855","url":null,"abstract":"The use of behavior change systems and persuasive technologies to promote desirable behavior is increasingly gaining attention. Most existing Persuasive Technologies (PTs) are targeted at promoting Physical Activity (PA) using three common socially-oriented persuasive strategies: competition, social comparison, and cooperation. This paper provides an empirical review of 19 years (54 papers) of literature on persuasive technology for physical activity promotion. The review aims to (1.) evaluate the effectiveness of PTs employing social influence strategies to promote PA; (2.) summarize and highlight trends in the outcomes and employed technological platforms; (3.) reveal some weaknesses of existing PTs for promoting PA; and finally, (4.) offer suggestions for improvements, and opportunities for future research in this area.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127023692","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}
Vladimir Janjic, J. Bowles, Marios Belk, A. Pitsillides
We describe the recently-started EU H2020 Serums: Securing Medical Data in Smart Patient-Centric Healthcare Systems project that aims to develop novel techniques for safe and secure collection, storage, exchange and analysis of medical data, allowing the patients of the next-generation smart healthcare centers to get the best pos- sible treatment while respecting privacy and ownership of their sensitive personal data. Our goal is to signi cantly enhance trust in the new medical systems. We outline the techniques that will be extended/developed over the course of the project and describe the use cases that will be used to verify the e ectiveness of these technologies in practice.
{"title":"Security And Privacy Of Medical Data: Challenges For Next-Generation Patient-Centric Healthcare Systems","authors":"Vladimir Janjic, J. Bowles, Marios Belk, A. Pitsillides","doi":"10.1145/3314183.3326364","DOIUrl":"https://doi.org/10.1145/3314183.3326364","url":null,"abstract":"We describe the recently-started EU H2020 Serums: Securing Medical Data in Smart Patient-Centric Healthcare Systems project that aims to develop novel techniques for safe and secure collection, storage, exchange and analysis of medical data, allowing the patients of the next-generation smart healthcare centers to get the best pos- sible treatment while respecting privacy and ownership of their sensitive personal data. Our goal is to signi cantly enhance trust in the new medical systems. We outline the techniques that will be extended/developed over the course of the project and describe the use cases that will be used to verify the e ectiveness of these technologies in practice.","PeriodicalId":240482,"journal":{"name":"Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116540992","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}
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