Ruben Verborgh’s data

Matches in Ruben’s data for { ?s ?p "Finding relevant content automatically is still not straightforward due to the unstructured nature of large text corpora. Moreover, traditional techniques to extract structured information out of these corpora are mostly very fine-grained, which deteriorates the needed high-level overview to be able to compare publications. Also, publishing this information as Linked Data can provide for very important context information. This demo paper describes StoryBlink, a Web application that enables the discovery of stories through linked books. By finding paths between compact semantic summaries of stories, it provides the user with relevant stories, based on previously selected publications. By also returning the semantic similarities between these stories, it gives the user a quick insight into how certain stories are connected. As such, StoryBlink enables an automatic content-based discovery journey between linked stories."@en }

• publication abstract "Finding relevant content automatically is still not straightforward due to the unstructured nature of large text corpora. Moreover, traditional techniques to extract structured information out of these corpora are mostly very fine-grained, which deteriorates the needed high-level overview to be able to compare publications. Also, publishing this information as Linked Data can provide for very important context information. This demo paper describes StoryBlink, a Web application that enables the discovery of stories through linked books. By finding paths between compact semantic summaries of stories, it provides the user with relevant stories, based on previously selected publications. By also returning the semantic similarities between these stories, it gives the user a quick insight into how certain stories are connected. As such, StoryBlink enables an automatic content-based discovery journey between linked stories.".