Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
QARLA: a framework for the evaluation of text summarization systems
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
The automatic creation of literature abstracts
IBM Journal of Research and Development
Second workshop on information heterogeneity and fusion in recommender systems (HetRec2011)
Proceedings of the fifth ACM conference on Recommender systems
RELIN: relatedness and informativeness-based centrality for entity summarization
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
Towards exploratory video search using linked data
Multimedia Tools and Applications
The notion of diversity in graphical entity summarisation on semantic knowledge graphs
Journal of Intelligent Information Systems
Information Processing and Management: an International Journal
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In recent years, strategies for Linked Data consumption have caught attention in Semantic Web research. For direct consumption by users, Linked Data mashups, interfaces, and visualizations have become a popular research area. Many approaches in this field aim to make Linked Data interaction more user friendly to improve its accessibility for non-technical users. A subtask for Linked Data interfaces is to present entities and their properties in a concise form. In general, these summaries take individual attributes and sometimes user contexts and preferences into account. But the objective evaluation of the quality of such summaries is an expensive task. In this paper we introduce a game-based approach aiming to establish a ground truth for the evaluation of entity summarization. We exemplify the applicability of the approach by evaluating two recent summarization approaches.