UMAP 2017 Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems: Organizers' Welcome & Organization

Peter Knees, Kristina Andersen, A. Said, M. Tkalcic
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Abstract

It is our great pleasure to welcome you to the UMAP 2017 Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems (SOAP). Following the successful first edition of the workshop at UMAP 2016, we are happy to see a continuing and increasing interest in the workshop's topics. As with the first edition, for the second edition we were able to accept four highly relevant submissions, allowing us to discuss the challenges of recommending unexpected, nonetheless relevant and impactful artifacts during a focused half-day workshop. With the workshop being originally motivated by interviews with music creators and producers who articulated a strong rejection of "more-of-the-same" search engines and recommender systems as they challenge their notion of originality and, ultimately, pose a threat to their artistic identity, we realized that a demand for adaptive and personalized systems that not only have the capability to surprise, but also to oppose and even obstruct can be found in a wider field. In fact, this coincides with ongoing trends to deal with and escape generally negatively connoted effects of automatic recommender systems, such as the so-called "filter-bubble". Apart from the potential dangers of such effects on the unreflecting user, there seems to be a growing impression that collaborative, as well as content-based recommender systems keep making obvious, uninspiring, and therefore disengaging suggestions based on previous interactions. Over the last years, this has emphasized the value of system qualities beyond pure accuracy, e.g., diversity, novelty, serendipity, or unexpectedness, to keep the user satisfied. In fact, these approaches to kicking the user out of his or her "comfort zone" seem to be highly promising methods to increase satisfaction with a system in the long run.
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2017年UMAP研讨会:适应性和个性化系统中的惊喜、反对和阻碍:组织者的欢迎和组织
我们非常高兴地欢迎您参加UMAP 2017自适应和个性化系统(SOAP)中的意外、反对和障碍研讨会。继2016年UMAP第一届研讨会成功举办之后,我们很高兴看到人们对研讨会主题的兴趣不断增加。与第一版一样,对于第二版,我们能够接受四个高度相关的提交,允许我们在集中的半天研讨会中讨论推荐意想不到的,尽管如此相关且有影响力的工件的挑战。工作坊最初的动机是对音乐创作者和制作人的采访,他们明确表示强烈反对“更多相同”的搜索引擎和推荐系统,因为它们挑战了他们的原创性概念,并最终对他们的艺术身份构成威胁,我们意识到,对适应性和个性化系统的需求不仅具有惊喜的能力,而且还反对甚至阻碍可以在更广泛的领域找到。事实上,这与当前处理和避免自动推荐系统(如所谓的“过滤泡沫”)通常隐含的负面影响的趋势是一致的。除了这种影响对不思考的用户的潜在危险之外,似乎有一个越来越多的印象是,协作的,以及基于内容的推荐系统不断地根据之前的交互做出明显的,无趣的,因此不吸引人的建议。在过去的几年里,这强调了系统质量的价值,超越了纯粹的准确性,例如,多样性,新颖性,意外性,或意外性,以保持用户满意。事实上,从长远来看,这些将用户赶出“舒适区”的方法似乎是非常有希望提高系统满意度的方法。
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