Christoph Trattner

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Twitter is often referred to as a backchannel for conferences. While the main conference takes place in a physical setting, attendees and virtual attendees socialize, introduce new ideas or broadcast information by microblogging on Twitter. In this paper we analyze the scholars' Twitter use in 16 Computer Science conferences over a timespan of five years.(More)
In this work we present a novel item recommendation approach that aims at improving Collaborative Filtering (CF) in social tagging systems using the information about tags and time. Our algorithm follows a two-step approach, where in the first step a potentially interesting candidate item-set is found using user-based CF and in the second step this(More)
Research in recommender systems has traditionally focused on improving the predictive accuracy of recommendations by developing new algorithms or by incorporating new sources of data. However, several studies have shown that accuracy does not always correlate with a better user experience, leading to recent research that puts emphasis on Human-Computer(More)
Decentralized search in networks is an activity that is often performed in online tasks. It refers to situations where a user has no global knowledge of a network's topology, but only local knowledge. On Wikipedia for instance, humans typically have local knowledge of the links emanating from a given Wikipedia article, but no global knowledge of the entire(More)
It is a widely held belief among designers of social tagging systems that tag clouds represent a useful tool for navigation. This is evident in, for example, the increasing number of tagging systems offering tag clouds for navigational purposes, which hints towards an implicit assumption that tag clouds support efficient navigation. In this paper, we(More)
Although many social tagging systems share a common tripartite graph structure, the collaborative processes that are generating these structures can differ significantly. For example, while resources on Delicious are usually tagged by all users who bookmark the web page, photos on Flickr are usually tagged just by a single user who uploads the(More)
In this paper, we present work-in-progress of a recently started research effort that aims at understanding the hidden temporal dynamics in online food communities. In this context, we have mined and analyzed temporal patterns in terms of recipe production and consumption in a large German community platform. As our preliminary results reveal, there are(More)
In recent years, several successful tag recommendation mechanisms have been developed that, among others, built upon Collaborative Filtering, Tensor Factorization, graph-based algorithms and simple “most popular tags” approaches. From an economic perspective, the latter approach has been convincing as calculating frequencies is computationally efficient and(More)
Workplace learning happens in the process and context of work, is multi-episodic, often informal, problem based and takes place on a just-in-time basis. While this is a very effective means of delivery, it also does not scale very well beyond the immediate context. We review three types of technologies that have been suggested to scale learning and three(More)