PageRank and Generic Entity Summarization for RDF Knowledge Bases

author: Andreas Thalhammer, F. Hoffmann-La Roche Ltd
author: Dennis Diefenbach, University Jean Monnet, St Etienne
published: July 10, 2018,   recorded: June 2018,   views: 864


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Ranking and entity summarization are operations that are tightly connected and recurrent in many different domains. Possible application fields include information retrieval, question answering, named entity disambiguation, co-reference resolution, and natural language generation. Still, the use of these techniques is limited because there are few accessible resources. PageRank computations are resource-intensive and entity summarization is a complex research field in itself. We present two generic and highly reusable resources for RDF knowledge bases: a component for PageRank-based ranking and a component for entity summarization. The two components, namely PageRankRDF and SummaServer, are provided in form of open source code along with example datasets and deployments. In addition, this work outlines the application of the components for PageRank-based RDF ranking and entity summarization in the question answering project WDAqua.

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Reviews and comments:

Comment1 Electa Walter, October 26, 2020 at 1:50 p.m.:

Thanks to Andreas Thalhammer and Dennis Diefenbach, I have learned fundamental concepts of Generic Entity Summarization as well as PageRank. I have also worked on some exercises to increase the strength of my newly learned concepts and in this case, I have written a research paper along with my writer that I hired by reading reviews on about EduBirdie after reading this article I felt happy that I provided the right information in my research paper.

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