�ݺ�ߣshows by User: davidelsweiler

�ݺ�ߣshows by User: davidelsweiler / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: davidelsweiler / Mon, 14 Apr 2014 00:37:24 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: davidelsweiler CaRR Workshop Keynote �ݺ�ߣs /slideshow/carr-workshop-keynote-slides/33485461 carr2014elsweiler-140414003724-phpapp02
Recommender Systems and IR are technically very similar problems, but are typically treated separately and often investigated by different groups of researchers. Looking at how people behave with such systems can be one way of unifying the problem, as well as the researchers, and can also be a useful, complementary evaluation method. When examining user behaviour, context is crucial. By focusing on the user behaviour and the encapsulating context, we can ask questions about tools that combine search and recsys like: when do people prefer to search and when do they prefer recommendations? What does this mean for what they are trying to achieve? In this talk I will try to answer such questions with examples from leisure and health domains. Finally, looking towards the future, I will argue that the relationship between search and recommender systems and behaviour can go full circle i.e., that both have the potential to impact on user behaviour in positive ways, and will present some ideas that I together with collaborators are doing to explore this.]]>
Recommender Systems and IR are technically very similar problems, but are typically treated separately and often investigated by different groups of researchers. Looking at how people behave with such systems can be one way of unifying the problem, as well as the researchers, and can also be a useful, complementary evaluation method. When examining user behaviour, context is crucial. By focusing on the user behaviour and the encapsulating context, we can ask questions about tools that combine search and recsys like: when do people prefer to search and when do they prefer recommendations? What does this mean for what they are trying to achieve? In this talk I will try to answer such questions with examples from leisure and health domains. Finally, looking towards the future, I will argue that the relationship between search and recommender systems and behaviour can go full circle i.e., that both have the potential to impact on user behaviour in positive ways, and will present some ideas that I together with collaborators are doing to explore this.]]> Mon, 14 Apr 2014 00:37:24 GMT /slideshow/carr-workshop-keynote-slides/33485461 davidelsweiler@slideshare.net(davidelsweiler) CaRR Workshop Keynote �ݺ�ߣs davidelsweiler Recommender Systems and IR are technically very similar problems, but are typically treated separately and often investigated by different groups of researchers. Looking at how people behave with such systems can be one way of unifying the problem, as well as the researchers, and can also be a useful, complementary evaluation method. When examining user behaviour, context is crucial. By focusing on the user behaviour and the encapsulating context, we can ask questions about tools that combine search and recsys like: when do people prefer to search and when do they prefer recommendations? What does this mean for what they are trying to achieve? In this talk I will try to answer such questions with examples from leisure and health domains. Finally, looking towards the future, I will argue that the relationship between search and recommender systems and behaviour can go full circle i.e., that both have the potential to impact on user behaviour in positive ways, and will present some ideas that I together with collaborators are doing to explore this. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/carr2014elsweiler-140414003724-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Recommender Systems and IR are technically very similar problems, but are typically treated separately and often investigated by different groups of researchers. Looking at how people behave with such systems can be one way of unifying the problem, as well as the researchers, and can also be a useful, complementary evaluation method. When examining user behaviour, context is crucial. By focusing on the user behaviour and the encapsulating context, we can ask questions about tools that combine search and recsys like: when do people prefer to search and when do they prefer recommendations? What does this mean for what they are trying to achieve? In this talk I will try to answer such questions with examples from leisure and health domains. Finally, looking towards the future, I will argue that the relationship between search and recommender systems and behaviour can go full circle i.e., that both have the potential to impact on user behaviour in positive ways, and will present some ideas that I together with collaborators are doing to explore this.

CaRR Workshop Keynote �ݺ�ߣs from David Elsweiler

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