Publication

Here you can find scientific publications of Know-Center employees

Utilizing Online Social Network and Location-Based Data to Recommend Products and Categories in Online Marketplaces

E Lacic, D Kowald, L Eberhard, C Trattner, D Parra, L Marinho – MSM-MUSE PostProceedings, 2015

Recent research has unveiled the importance of online social networks for improving the quality of recommender systems and encouraged the research community to investigate better ways of exploiting the social information for recommendations. To contribute to this sparse field of research, in this paper we exploit users’ interactions along three…

Twitter in Academic Conferences: Usage, Networking and Participation over Time

X Wen, Y Lin, C Trattner, D Parra – In Proceedings of the 25th ACM Conference on Hypertext and Social Media, 2014

Recommending Items in Social Tagging Systems Using Tag and Time Information

E Lacic, D Kowald, P Seitlinger, C Trattner, D Parra – In Proceedings of the 1st Social Personalization Workshop co-loca…, 2014

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…

How groups of people interact with each other on Twitter during academic conferences

X Wen, D Parra, C Trattner – In Proceedings of the 2014 ACM Conference on Computer Supported Cooperative Work , 2014

User Controllability in an Hybrid Talk Recommender System

D Parra, P Brusilovsky, C Trattner – In Proceedings of the ACM 2014 International Conference on Intelligent User Interfa…, 2014

Towards a Scalable Social Recommender Engine for Online Marketplaces: The Case of Apache Solr

E Lacic, D Kowald, D Parra, M Kahr, C Trattner – Proceedings o…, 2014 – International World Wide Web Conferences Steering …

Recent research has unveiled the importance of online social networks for improving the quality of recommenders in several domains, what has encouraged the research community to investigate ways to better exploit the social information for recommendations. However, there is a lack of work that offers details of frameworks that allow…

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