In this position paper, we address the question of how to make music search and discovery more appealing, more exciting, and more joyful. In particular, we argue to research methods that foster serendipitous encounters with music items and to integrate ways for social interaction while exploring music collections and discovering the gems in today's huge catalogs available through online streaming platforms. We identify two major challenges here: the need for (i) highly efficient clustering and information visualization techniques that scale to these music catalogs and (ii) novel user interfaces that explain the clustering of music items and provide means to make the exploration of music a social event.
{"title":"Intelligent User Interfaces for Social Music Discovery and Exploration of Large-scale Music Repositories","authors":"M. Schedl","doi":"10.1145/3039677.3039678","DOIUrl":"https://doi.org/10.1145/3039677.3039678","url":null,"abstract":"In this position paper, we address the question of how to make music search and discovery more appealing, more exciting, and more joyful. In particular, we argue to research methods that foster serendipitous encounters with music items and to integrate ways for social interaction while exploring music collections and discovering the gems in today's huge catalogs available through online streaming platforms. We identify two major challenges here: the need for (i) highly efficient clustering and information visualization techniques that scale to these music catalogs and (ii) novel user interfaces that explain the clustering of music items and provide means to make the exploration of music a social event.","PeriodicalId":436414,"journal":{"name":"Proceedings of the 2017 ACM Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces","volume":"54 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131829482","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}
As more people turn to online resources to learn, there will be an increasing need for systems to understand and adapt to the needs of their users. Engagement is an important aspect to keep users committed to learning. Learning approaches for online systems can benefit from personalization to engage their users. However, many approaches for personalization currently rely on methods (e.g., historical behavioral data, questionnaires, quizzes) that are unable to provide a personalized experience from the start-of-use of a system. As users in a learning environment are exposed to new content, the first impression that they receive from the system influences their commitment with the program. In this position paper we propose a quantitative approach for personalization in online learning environments to overcome current problems for personalization in such environments.
{"title":"Personalizing Online Educational Tools","authors":"M. Lee, B. Ferwerda","doi":"10.1145/3039677.3039680","DOIUrl":"https://doi.org/10.1145/3039677.3039680","url":null,"abstract":"As more people turn to online resources to learn, there will be an increasing need for systems to understand and adapt to the needs of their users. Engagement is an important aspect to keep users committed to learning. Learning approaches for online systems can benefit from personalization to engage their users. However, many approaches for personalization currently rely on methods (e.g., historical behavioral data, questionnaires, quizzes) that are unable to provide a personalized experience from the start-of-use of a system. As users in a learning environment are exposed to new content, the first impression that they receive from the system influences their commitment with the program. In this position paper we propose a quantitative approach for personalization in online learning environments to overcome current problems for personalization in such environments.","PeriodicalId":436414,"journal":{"name":"Proceedings of the 2017 ACM Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces","volume":"529 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124503998","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}
Vikas Kumar, Saeideh Bakhshi, L. Kennedy, David A. Shamma
In the past decade, location-based services have grown through geo-tagging and place-tagging. Proliferation of GPS-enabled mobile devices further enabled exponential growth in geo-tagged user content. On the other hand, location-based applications harness the abundance of geo-tagged content to further improve user experience and more relevant localized content. We show in this paper that geo-tagged content can vary significantly based on whether they are captured by a local versus a tourist to the location. Using photos shared by online users, we also show how we can learn unique characteristics about a given location. We finally discuss an effective metric to rank the most representative photos for a given location by combining visual contents and their social engagement potential.
{"title":"Modeling Characteristics of Location from User Photos","authors":"Vikas Kumar, Saeideh Bakhshi, L. Kennedy, David A. Shamma","doi":"10.1145/3039677.3039683","DOIUrl":"https://doi.org/10.1145/3039677.3039683","url":null,"abstract":"In the past decade, location-based services have grown through geo-tagging and place-tagging. Proliferation of GPS-enabled mobile devices further enabled exponential growth in geo-tagged user content. On the other hand, location-based applications harness the abundance of geo-tagged content to further improve user experience and more relevant localized content. We show in this paper that geo-tagged content can vary significantly based on whether they are captured by a local versus a tourist to the location. Using photos shared by online users, we also show how we can learn unique characteristics about a given location. We finally discuss an effective metric to rank the most representative photos for a given location by combining visual contents and their social engagement potential.","PeriodicalId":436414,"journal":{"name":"Proceedings of the 2017 ACM Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122645047","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}
{"title":"Session details: Personality-Based Personalization","authors":"M. Schedl","doi":"10.1145/3252645","DOIUrl":"https://doi.org/10.1145/3252645","url":null,"abstract":"","PeriodicalId":436414,"journal":{"name":"Proceedings of the 2017 ACM Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121820678","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}
Mark P. Graus, B. Ferwerda, M. Schedl, M. Tkalcic, M. Willemsen, Panagiotis Germanakos
It is our great pleasure to welcome you to the first workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces (HUMANIZE), organized in conjunction with ACM's 2017 Intelligent User Interfaces (IUI) conference. This workshop provided a place for researchers and practitioners in the field of intelligent user interfaces to present and discuss research on personalization and tailoring of interfaces based on psychological theoretical models. The goal of the workshop is to leverage the theoretical knowledge about interfaces and their users, with data-driven methods, in order to be able to personalize and tailor interfaces in a way grounded in theory. The call for papers attracted submissions from Europe, Asia, Oceania, and the United States.
{"title":"Proceedings of the 2017 ACM Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces","authors":"Mark P. Graus, B. Ferwerda, M. Schedl, M. Tkalcic, M. Willemsen, Panagiotis Germanakos","doi":"10.1145/3039677","DOIUrl":"https://doi.org/10.1145/3039677","url":null,"abstract":"It is our great pleasure to welcome you to the first workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces (HUMANIZE), organized in conjunction with ACM's 2017 Intelligent User Interfaces (IUI) conference. \u0000 \u0000This workshop provided a place for researchers and practitioners in the field of intelligent user interfaces to present and discuss research on personalization and tailoring of interfaces based on psychological theoretical models. The goal of the workshop is to leverage the theoretical knowledge about interfaces and their users, with data-driven methods, in order to be able to personalize and tailor interfaces in a way grounded in theory. \u0000 \u0000The call for papers attracted submissions from Europe, Asia, Oceania, and the United States.","PeriodicalId":436414,"journal":{"name":"Proceedings of the 2017 ACM Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces","volume":"E-7 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121007010","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}
Game-like environments are increasingly used for conducting research due to the affordances that such environments offer. However, the problem remains that such environments treat their users equally. In order to address this, personalization is necessary. In this paper we discuss the need to personalize gamified research environments to motivate participation by illustrating a playful platform called Mad Science, which is being developed to allow users to create social and behavioral studies. This discussion is both informed by the platform's affordances and use thus far as well as existing theories on player motivation, and contributes to theory-informed approaches to (gamified) personalization technologies.
{"title":"Personalized Gaming for Motivating Social and Behavioral Science Participation","authors":"C. Harteveld, Steven C. Sutherland","doi":"10.1145/3039677.3039681","DOIUrl":"https://doi.org/10.1145/3039677.3039681","url":null,"abstract":"Game-like environments are increasingly used for conducting research due to the affordances that such environments offer. However, the problem remains that such environments treat their users equally. In order to address this, personalization is necessary. In this paper we discuss the need to personalize gamified research environments to motivate participation by illustrating a playful platform called Mad Science, which is being developed to allow users to create social and behavioral studies. This discussion is both informed by the platform's affordances and use thus far as well as existing theories on player motivation, and contributes to theory-informed approaches to (gamified) personalization technologies.","PeriodicalId":436414,"journal":{"name":"Proceedings of the 2017 ACM Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126865563","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}
We propose the use of physical objects and hypothetical mock-ups in the conceptual development of algorithms and system functionality. This extends approaches like participatory design beyond the design process of interfaces, but rather allows for imagination of future algorithm functionality and reveals desiderata of systems outside the boundaries of existing systems. We demonstrate this approach using the outcomes of a series of interviews with users in the creative domain, more specifically, music production experts. We show three exemplary props built from cardboard embodying ideas emerged from interview sessions and how these, in turn, inspire conversations on future recommender systems, sound search engines, and sound manipulation interfaces.
{"title":"Building Physical Props for Imagining Future Recommender Systems","authors":"Peter Knees, Kristina Andersen","doi":"10.1145/3039677.3039682","DOIUrl":"https://doi.org/10.1145/3039677.3039682","url":null,"abstract":"We propose the use of physical objects and hypothetical mock-ups in the conceptual development of algorithms and system functionality. This extends approaches like participatory design beyond the design process of interfaces, but rather allows for imagination of future algorithm functionality and reveals desiderata of systems outside the boundaries of existing systems. We demonstrate this approach using the outcomes of a series of interviews with users in the creative domain, more specifically, music production experts. We show three exemplary props built from cardboard embodying ideas emerged from interview sessions and how these, in turn, inspire conversations on future recommender systems, sound search engines, and sound manipulation interfaces.","PeriodicalId":436414,"journal":{"name":"Proceedings of the 2017 ACM Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128233117","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}
{"title":"Session details: Research Methodology","authors":"B. Ferwerda","doi":"10.1145/3252646","DOIUrl":"https://doi.org/10.1145/3252646","url":null,"abstract":"","PeriodicalId":436414,"journal":{"name":"Proceedings of the 2017 ACM Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123976061","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}
{"title":"Session details: Exploiting Big Data","authors":"Mark P. Graus","doi":"10.1145/3252644","DOIUrl":"https://doi.org/10.1145/3252644","url":null,"abstract":"","PeriodicalId":436414,"journal":{"name":"Proceedings of the 2017 ACM Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121542132","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}
Rachel Yahel Halfon, O. Shehory, David G. Schwartz
The volume of information users are exposed to on the web is overwhelming. To increase effectiveness of information delivery to users, providers employ personalization strategies. In a highly competitive environment, simplistic strategies do not suffice, and high-quality personalization is required. These can be based on users' decision making models. To build such models, we need to extract factors of direct influence on users' decision making. Personality factors are known to have this direct influence. They are stable over time and across situations, and they assist in predicting future behavior of individuals in a scientific way. In this paper, we introduce a novel methodology for extracting users' personality factors without holding any prior information on the users' behavior and, notably, without administering any psychological questionnaires. This allows us to build a designated model for each user or users' group, and in turn facilitates effective personalized information delivery.
{"title":"Game-Based Extraction of Web Users' Personality Factors for Personalization","authors":"Rachel Yahel Halfon, O. Shehory, David G. Schwartz","doi":"10.1145/3039677.3039679","DOIUrl":"https://doi.org/10.1145/3039677.3039679","url":null,"abstract":"The volume of information users are exposed to on the web is overwhelming. To increase effectiveness of information delivery to users, providers employ personalization strategies. In a highly competitive environment, simplistic strategies do not suffice, and high-quality personalization is required. These can be based on users' decision making models. To build such models, we need to extract factors of direct influence on users' decision making. Personality factors are known to have this direct influence. They are stable over time and across situations, and they assist in predicting future behavior of individuals in a scientific way. In this paper, we introduce a novel methodology for extracting users' personality factors without holding any prior information on the users' behavior and, notably, without administering any psychological questionnaires. This allows us to build a designated model for each user or users' group, and in turn facilitates effective personalized information delivery.","PeriodicalId":436414,"journal":{"name":"Proceedings of the 2017 ACM Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129530479","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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